From 5fef1434187a39fe28ebc966b019c6d676b7e985 Mon Sep 17 00:00:00 2001 From: Yuri Han <45699207+urihan@users.noreply.github.com> Date: Tue, 6 Jun 2023 04:56:40 +0900 Subject: [PATCH 1/3] fix: Updates for Qiskit to Braket circuit conversion (#97) * Probability to Sample result type * passes tox lint * updates toxlint * fixes observable z error but not passses elint * unit test added * final commit with tests --- qiskit_braket_provider/providers/adapter.py | 7 +++++-- tests/providers/test_adapter.py | 20 +++++++++++++++++++- 2 files changed, 24 insertions(+), 3 deletions(-) diff --git a/qiskit_braket_provider/providers/adapter.py b/qiskit_braket_provider/providers/adapter.py index c24ed383..6706574d 100644 --- a/qiskit_braket_provider/providers/adapter.py +++ b/qiskit_braket_provider/providers/adapter.py @@ -8,6 +8,7 @@ Instruction, gates, result_types, + observables, ) from braket.device_schema import ( DeviceActionType, @@ -364,11 +365,13 @@ def convert_qiskit_to_braket_circuit(circuit: QuantumCircuit) -> Circuit: # TODO: change Probability result type for Sample for proper functioning # pylint:disable=fixme # Getting the index from the bit mapping quantum_circuit.add_result_type( - result_types.Probability( + # pylint:disable=fixme + result_types.Sample( + observable=observables.Z(), target=[ circuit.find_bit(qiskit_gates[1][0]).index, circuit.find_bit(qiskit_gates[2][0]).index, - ] + ], ) ) elif name == "barrier": diff --git a/tests/providers/test_adapter.py b/tests/providers/test_adapter.py index 2f7aebf2..5d34108d 100644 --- a/tests/providers/test_adapter.py +++ b/tests/providers/test_adapter.py @@ -1,7 +1,7 @@ """Tests for Qiskti to Braket adapter.""" from unittest import TestCase -from braket.circuits import Circuit, FreeParameter +from braket.circuits import Circuit, FreeParameter, observables import numpy as np from qiskit import QuantumCircuit from qiskit.circuit import Parameter @@ -59,6 +59,24 @@ def test_convert_parametric_qiskit_to_braket_circuit(self): self.assertEqual(braket_circuit, braket_circuit_ans) + def test_sample_result_type(self): + """Tests sample result type with observables Z""" + + qiskit_circuit = QuantumCircuit(2, 2) + qiskit_circuit.h(0) + qiskit_circuit.cnot(0, 1) + qiskit_circuit.measure(0, 0) + braket_circuit = convert_qiskit_to_braket_circuit(qiskit_circuit) + + circuits = ( + Circuit() # pylint: disable=no-member + .h(0) + .cnot(0, 1) + .sample(observable=observables.Z(), target=0) + ) + + self.assertEqual(braket_circuit, circuits) + class TestVerbatimBoxWrapper(TestCase): """Test wrapping in Verbatim box.""" From 2434a9a29900972e5fe6dace3804384ee08d9df7 Mon Sep 17 00:00:00 2001 From: Kshitij Chhabra Date: Thu, 8 Jun 2023 10:58:31 -0700 Subject: [PATCH 2/3] fix: Fallback to JAQCD for device properties (#104) * fix: Fallback to JAQCD for device properties * fix: reformat --- .../0_how_to_access_AWS_Braket_devices.ipynb | 159 ++++++++++-------- docs/how_tos/4_how_to_verbatim_circuits.ipynb | 8 +- ...rial_qiskit-braket-provider_overview.ipynb | 14 +- qiskit_braket_provider/providers/adapter.py | 6 +- 4 files changed, 108 insertions(+), 79 deletions(-) diff --git a/docs/how_tos/0_how_to_access_AWS_Braket_devices.ipynb b/docs/how_tos/0_how_to_access_AWS_Braket_devices.ipynb index 5518bdd0..32123f1d 100644 --- a/docs/how_tos/0_how_to_access_AWS_Braket_devices.ipynb +++ b/docs/how_tos/0_how_to_access_AWS_Braket_devices.ipynb @@ -13,7 +13,7 @@ }, { "cell_type": "code", - "execution_count": null, + "execution_count": 1, "id": "5e768d55", "metadata": {}, "outputs": [], @@ -25,7 +25,7 @@ }, { "cell_type": "code", - "execution_count": 4, + "execution_count": 2, "id": "200f52ee", "metadata": {}, "outputs": [], @@ -43,26 +43,29 @@ }, { "cell_type": "code", - "execution_count": 52, + "execution_count": 3, "id": "906ecc1a", "metadata": {}, "outputs": [ { "data": { "text/plain": [ - "[BraketBackend[Aspen-10],\n", + "[BraketBackend[Aria 1],\n", + " BraketBackend[Aspen-10],\n", " BraketBackend[Aspen-11],\n", " BraketBackend[Aspen-8],\n", " BraketBackend[Aspen-9],\n", " BraketBackend[Aspen-M-1],\n", - " BraketBackend[IonQ Device],\n", + " BraketBackend[Aspen-M-2],\n", + " BraketBackend[Aspen-M-3],\n", + " BraketBackend[Harmony],\n", " BraketBackend[Lucy],\n", " BraketBackend[SV1],\n", " BraketBackend[TN1],\n", " BraketBackend[dm1]]" ] }, - "execution_count": 52, + "execution_count": 3, "metadata": {}, "output_type": "execute_result" } @@ -74,7 +77,7 @@ }, { "cell_type": "code", - "execution_count": 40, + "execution_count": 4, "id": "8c8672a6", "metadata": {}, "outputs": [ @@ -82,106 +85,136 @@ "name": "stdout", "output_type": "stream", "text": [ + "{'backend version': 2,\n", + " 'description': 'AWS Device: IonQ Aria 1.',\n", + " 'name': 'Aria 1',\n", + " 'number of qubits': 25,\n", + " 'online date': datetime.datetime(2023, 6, 7, 11, 12, 40, tzinfo=datetime.timezone.utc),\n", + " 'operations': [Instruction(name='measure', num_qubits=1, num_clbits=1, params=[]),\n", + " Instruction(name='x', num_qubits=1, num_clbits=0, params=[]),\n", + " Instruction(name='y', num_qubits=1, num_clbits=0, params=[]),\n", + " Instruction(name='z', num_qubits=1, num_clbits=0, params=[]),\n", + " Instruction(name='rx', num_qubits=1, num_clbits=0, params=[Parameter(theta)])]}\n", "{'backend version': 2,\n", " 'description': 'AWS Device: Rigetti Aspen-10.',\n", " 'name': 'Aspen-10',\n", " 'number of qubits': 38,\n", " 'online date': datetime.datetime(2021, 12, 15, 19, 48, 30, tzinfo=datetime.timezone.utc),\n", - " 'operations': [Instruction(name='cz', num_qubits=2, num_clbits=0, params=[]),\n", + " 'operations': [Instruction(name='measure', num_qubits=1, num_clbits=1, params=[]),\n", + " Instruction(name='cz', num_qubits=2, num_clbits=0, params=[]),\n", " Instruction(name='cx', num_qubits=2, num_clbits=0, params=[]),\n", " Instruction(name='cp', num_qubits=2, num_clbits=0, params=[Parameter(theta)]),\n", - " Instruction(name='h', num_qubits=1, num_clbits=0, params=[]),\n", - " Instruction(name='id', num_qubits=1, num_clbits=0, params=[])]}\n", + " Instruction(name='h', num_qubits=1, num_clbits=0, params=[])]}\n", "{'backend version': 2,\n", " 'description': 'AWS Device: Rigetti Aspen-11.',\n", " 'name': 'Aspen-11',\n", " 'number of qubits': 48,\n", - " 'online date': datetime.datetime(2022, 3, 4, 20, 18, 30, tzinfo=datetime.timezone.utc),\n", - " 'operations': [Instruction(name='cz', num_qubits=2, num_clbits=0, params=[]),\n", + " 'online date': datetime.datetime(2022, 8, 17, 21, 25, 7, tzinfo=datetime.timezone.utc),\n", + " 'operations': [Instruction(name='measure', num_qubits=1, num_clbits=1, params=[]),\n", + " Instruction(name='cz', num_qubits=2, num_clbits=0, params=[]),\n", " Instruction(name='cx', num_qubits=2, num_clbits=0, params=[]),\n", " Instruction(name='cp', num_qubits=2, num_clbits=0, params=[Parameter(theta)]),\n", - " Instruction(name='h', num_qubits=1, num_clbits=0, params=[]),\n", - " Instruction(name='id', num_qubits=1, num_clbits=0, params=[])]}\n", + " Instruction(name='h', num_qubits=1, num_clbits=0, params=[])]}\n", "{'backend version': 2,\n", " 'description': 'AWS Device: Rigetti Aspen-8.',\n", " 'name': 'Aspen-8',\n", " 'number of qubits': 38,\n", " 'online date': None,\n", - " 'operations': [Instruction(name='cz', num_qubits=2, num_clbits=0, params=[]),\n", + " 'operations': [Instruction(name='measure', num_qubits=1, num_clbits=1, params=[]),\n", + " Instruction(name='cz', num_qubits=2, num_clbits=0, params=[]),\n", " Instruction(name='cx', num_qubits=2, num_clbits=0, params=[]),\n", " Instruction(name='cp', num_qubits=2, num_clbits=0, params=[Parameter(theta)]),\n", - " Instruction(name='h', num_qubits=1, num_clbits=0, params=[]),\n", - " Instruction(name='id', num_qubits=1, num_clbits=0, params=[])]}\n", + " Instruction(name='h', num_qubits=1, num_clbits=0, params=[])]}\n", "{'backend version': 2,\n", " 'description': 'AWS Device: Rigetti Aspen-9.',\n", " 'name': 'Aspen-9',\n", " 'number of qubits': 38,\n", " 'online date': datetime.datetime(2021, 11, 18, 16, 13, 30, tzinfo=datetime.timezone.utc),\n", - " 'operations': [Instruction(name='cz', num_qubits=2, num_clbits=0, params=[]),\n", + " 'operations': [Instruction(name='measure', num_qubits=1, num_clbits=1, params=[]),\n", + " Instruction(name='cz', num_qubits=2, num_clbits=0, params=[]),\n", " Instruction(name='cx', num_qubits=2, num_clbits=0, params=[]),\n", " Instruction(name='cp', num_qubits=2, num_clbits=0, params=[Parameter(theta)]),\n", - " Instruction(name='h', num_qubits=1, num_clbits=0, params=[]),\n", - " Instruction(name='id', num_qubits=1, num_clbits=0, params=[])]}\n", + " Instruction(name='h', num_qubits=1, num_clbits=0, params=[])]}\n", "{'backend version': 2,\n", " 'description': 'AWS Device: Rigetti Aspen-M-1.',\n", " 'name': 'Aspen-M-1',\n", " 'number of qubits': 148,\n", - " 'online date': datetime.datetime(2022, 4, 18, 17, 3, 38, tzinfo=datetime.timezone.utc),\n", - " 'operations': [Instruction(name='cz', num_qubits=2, num_clbits=0, params=[]),\n", + " 'online date': datetime.datetime(2022, 6, 17, 20, 13, 38, tzinfo=datetime.timezone.utc),\n", + " 'operations': [Instruction(name='measure', num_qubits=1, num_clbits=1, params=[]),\n", + " Instruction(name='cz', num_qubits=2, num_clbits=0, params=[]),\n", " Instruction(name='cx', num_qubits=2, num_clbits=0, params=[]),\n", " Instruction(name='cp', num_qubits=2, num_clbits=0, params=[Parameter(theta)]),\n", - " Instruction(name='h', num_qubits=1, num_clbits=0, params=[]),\n", - " Instruction(name='id', num_qubits=1, num_clbits=0, params=[])]}\n", + " Instruction(name='h', num_qubits=1, num_clbits=0, params=[])]}\n", "{'backend version': 2,\n", - " 'description': 'AWS Device: IonQ IonQ Device.',\n", - " 'name': 'IonQ Device',\n", + " 'description': 'AWS Device: Rigetti Aspen-M-2.',\n", + " 'name': 'Aspen-M-2',\n", + " 'number of qubits': 148,\n", + " 'online date': datetime.datetime(2023, 1, 20, 19, 31, 9, tzinfo=datetime.timezone.utc),\n", + " 'operations': [Instruction(name='measure', num_qubits=1, num_clbits=1, params=[]),\n", + " Instruction(name='cz', num_qubits=2, num_clbits=0, params=[]),\n", + " Instruction(name='cx', num_qubits=2, num_clbits=0, params=[]),\n", + " Instruction(name='cp', num_qubits=2, num_clbits=0, params=[Parameter(theta)]),\n", + " Instruction(name='h', num_qubits=1, num_clbits=0, params=[])]}\n", + "{'backend version': 2,\n", + " 'description': 'AWS Device: Rigetti Aspen-M-3.',\n", + " 'name': 'Aspen-M-3',\n", + " 'number of qubits': 148,\n", + " 'online date': datetime.datetime(2023, 6, 8, 17, 35, 32, tzinfo=datetime.timezone.utc),\n", + " 'operations': [Instruction(name='measure', num_qubits=1, num_clbits=1, params=[]),\n", + " Instruction(name='cz', num_qubits=2, num_clbits=0, params=[]),\n", + " Instruction(name='cx', num_qubits=2, num_clbits=0, params=[]),\n", + " Instruction(name='cp', num_qubits=2, num_clbits=0, params=[Parameter(theta)]),\n", + " Instruction(name='h', num_qubits=1, num_clbits=0, params=[])]}\n", + "{'backend version': 2,\n", + " 'description': 'AWS Device: IonQ Harmony.',\n", + " 'name': 'Harmony',\n", " 'number of qubits': 11,\n", - " 'online date': datetime.datetime(2022, 4, 13, 18, 51, 48, 328000, tzinfo=datetime.timezone.utc),\n", - " 'operations': [Instruction(name='x', num_qubits=1, num_clbits=0, params=[]),\n", + " 'online date': datetime.datetime(2023, 6, 8, 11, 0, 4, tzinfo=datetime.timezone.utc),\n", + " 'operations': [Instruction(name='measure', num_qubits=1, num_clbits=1, params=[]),\n", + " Instruction(name='x', num_qubits=1, num_clbits=0, params=[]),\n", " Instruction(name='y', num_qubits=1, num_clbits=0, params=[]),\n", " Instruction(name='z', num_qubits=1, num_clbits=0, params=[]),\n", - " Instruction(name='rx', num_qubits=1, num_clbits=0, params=[Parameter(theta)]),\n", - " Instruction(name='ry', num_qubits=1, num_clbits=0, params=[Parameter(theta)])]}\n", + " Instruction(name='rx', num_qubits=1, num_clbits=0, params=[Parameter(theta)])]}\n", "{'backend version': 2,\n", " 'description': 'AWS Device: Oxford Lucy.',\n", " 'name': 'Lucy',\n", " 'number of qubits': 8,\n", - " 'online date': datetime.datetime(2022, 4, 18, 17, 0, 8, tzinfo=datetime.timezone.utc),\n", - " 'operations': [Instruction(name='cx', num_qubits=2, num_clbits=0, params=[]),\n", + " 'online date': datetime.datetime(2023, 6, 8, 17, 0, 8, tzinfo=datetime.timezone.utc),\n", + " 'operations': [Instruction(name='measure', num_qubits=1, num_clbits=1, params=[]),\n", + " Instruction(name='cx', num_qubits=2, num_clbits=0, params=[]),\n", " Instruction(name='cp', num_qubits=2, num_clbits=0, params=[Parameter(theta)]),\n", " Instruction(name='cy', num_qubits=2, num_clbits=0, params=[]),\n", - " Instruction(name='cz', num_qubits=2, num_clbits=0, params=[]),\n", - " Instruction(name='h', num_qubits=1, num_clbits=0, params=[])]}\n", + " Instruction(name='cz', num_qubits=2, num_clbits=0, params=[])]}\n", "{'backend version': 2,\n", " 'description': 'AWS Device: Amazon Braket SV1.',\n", " 'name': 'SV1',\n", " 'number of qubits': 34,\n", - " 'online date': datetime.datetime(2022, 1, 28, 17, 18, 44, 525122),\n", - " 'operations': [Instruction(name='cx', num_qubits=2, num_clbits=0, params=[]),\n", + " 'online date': datetime.datetime(2022, 6, 22, 10, 18),\n", + " 'operations': [Instruction(name='measure', num_qubits=1, num_clbits=1, params=[]),\n", + " Instruction(name='cx', num_qubits=2, num_clbits=0, params=[]),\n", " Instruction(name='cp', num_qubits=2, num_clbits=0, params=[Parameter(theta)]),\n", " Instruction(name='cy', num_qubits=2, num_clbits=0, params=[]),\n", - " Instruction(name='cz', num_qubits=2, num_clbits=0, params=[]),\n", - " Instruction(name='h', num_qubits=1, num_clbits=0, params=[])]}\n", + " Instruction(name='cz', num_qubits=2, num_clbits=0, params=[])]}\n", "{'backend version': 2,\n", " 'description': 'AWS Device: Amazon Braket TN1.',\n", " 'name': 'TN1',\n", " 'number of qubits': 50,\n", - " 'online date': datetime.datetime(2022, 1, 28, 17, 19, 33, 143757),\n", - " 'operations': [Instruction(name='cx', num_qubits=2, num_clbits=0, params=[]),\n", + " 'online date': datetime.datetime(2022, 6, 22, 10, 18),\n", + " 'operations': [Instruction(name='measure', num_qubits=1, num_clbits=1, params=[]),\n", + " Instruction(name='cx', num_qubits=2, num_clbits=0, params=[]),\n", " Instruction(name='cp', num_qubits=2, num_clbits=0, params=[Parameter(theta)]),\n", " Instruction(name='cy', num_qubits=2, num_clbits=0, params=[]),\n", - " Instruction(name='cz', num_qubits=2, num_clbits=0, params=[]),\n", - " Instruction(name='h', num_qubits=1, num_clbits=0, params=[])]}\n", + " Instruction(name='cz', num_qubits=2, num_clbits=0, params=[])]}\n", "{'backend version': 2,\n", " 'description': 'AWS Device: Amazon Braket dm1.',\n", " 'name': 'dm1',\n", " 'number of qubits': 17,\n", - " 'online date': datetime.datetime(2022, 3, 1, 22, 53, 1, 476669),\n", - " 'operations': [Instruction(name='cx', num_qubits=2, num_clbits=0, params=[]),\n", + " 'online date': datetime.datetime(2022, 6, 22, 10, 18),\n", + " 'operations': [Instruction(name='measure', num_qubits=1, num_clbits=1, params=[]),\n", + " Instruction(name='cx', num_qubits=2, num_clbits=0, params=[]),\n", " Instruction(name='cp', num_qubits=2, num_clbits=0, params=[Parameter(theta)]),\n", " Instruction(name='cy', num_qubits=2, num_clbits=0, params=[]),\n", - " Instruction(name='cz', num_qubits=2, num_clbits=0, params=[]),\n", - " Instruction(name='h', num_qubits=1, num_clbits=0, params=[])]}\n" + " Instruction(name='cz', num_qubits=2, num_clbits=0, params=[])]}\n" ] } ], @@ -209,7 +242,7 @@ }, { "cell_type": "code", - "execution_count": 42, + "execution_count": 5, "id": "c1e408c4", "metadata": {}, "outputs": [ @@ -219,7 +252,7 @@ "BraketBackend[SV1]" ] }, - "execution_count": 42, + "execution_count": 5, "metadata": {}, "output_type": "execute_result" } @@ -232,30 +265,30 @@ }, { "cell_type": "code", - "execution_count": 45, + "execution_count": 6, "id": "97112d3e", "metadata": {}, "outputs": [ { "data": { "text/plain": [ - "BraketBackend[IonQ Device]" + "BraketBackend[Harmony]" ] }, - "execution_count": 45, + "execution_count": 6, "metadata": {}, "output_type": "execute_result" } ], "source": [ "# IonQ device\n", - "ionq_backend = provider.get_backend(\"IonQ Device\")\n", + "ionq_backend = provider.get_backend(\"Harmony\")\n", "ionq_backend" ] }, { "cell_type": "code", - "execution_count": 46, + "execution_count": 7, "id": "32545fd3", "metadata": {}, "outputs": [ @@ -265,7 +298,7 @@ "BraketBackend[Aspen-11]" ] }, - "execution_count": 46, + "execution_count": 7, "metadata": {}, "output_type": "execute_result" } @@ -278,7 +311,7 @@ }, { "cell_type": "code", - "execution_count": 47, + "execution_count": 8, "id": "9c99034e", "metadata": {}, "outputs": [ @@ -288,7 +321,7 @@ "BraketBackend[Lucy]" ] }, - "execution_count": 47, + "execution_count": 8, "metadata": {}, "output_type": "execute_result" } @@ -311,7 +344,7 @@ }, { "cell_type": "code", - "execution_count": 51, + "execution_count": 9, "id": "f29a72eb", "metadata": {}, "outputs": [ @@ -321,7 +354,7 @@ "[BraketBackend[SV1], BraketBackend[TN1], BraketBackend[dm1]]" ] }, - "execution_count": 51, + "execution_count": 9, "metadata": {}, "output_type": "execute_result" } @@ -330,14 +363,6 @@ "online_simulators_backends = provider.backends(statuses=[\"ONLINE\"], types=[\"SIMULATOR\"])\n", "online_simulators_backends" ] - }, - { - "cell_type": "code", - "execution_count": null, - "id": "648a6638", - "metadata": {}, - "outputs": [], - "source": [] } ], "metadata": { @@ -356,7 +381,7 @@ "name": "python", "nbconvert_exporter": "python", "pygments_lexer": "ipython3", - "version": "3.9.7" + "version": "3.9.6" } }, "nbformat": 4, diff --git a/docs/how_tos/4_how_to_verbatim_circuits.ipynb b/docs/how_tos/4_how_to_verbatim_circuits.ipynb index da87bc41..8c70ae71 100644 --- a/docs/how_tos/4_how_to_verbatim_circuits.ipynb +++ b/docs/how_tos/4_how_to_verbatim_circuits.ipynb @@ -38,7 +38,7 @@ "\n", "Typically, one wants to design circuits using high-level concepts, without worrying about qubit placement or gate compilation. However, in some cases it might be desirable to have a precise control of the circuits being submitted.\n", "\n", - "We will start this how-to by defining a simple circuit comprising `cnot(0, 1)` gate and running it on Aspem-M-2 device.\n" + "We will start this how-to by defining a simple circuit comprising `cnot(0, 1)` gate and running it on Aspem-M-3 device.\n" ], "metadata": { "collapsed": false, @@ -63,7 +63,7 @@ ], "source": [ "provider = AWSBraketProvider()\n", - "aspen = provider.get_backend(\"Aspen-M-2\")\n", + "aspen = provider.get_backend(\"Aspen-M-3\")\n", "\n", "circuit = QuantumCircuit(2)\n", "circuit.cnot(0, 1)\n", @@ -99,7 +99,7 @@ "outputs": [ { "ename": "ValidationException", - "evalue": "An error occurred (ValidationException) when calling the CreateQuantumTask operation: Backend ARN, arn:aws:braket:us-west-1::device/qpu/rigetti/Aspen-M-2, does not support the operation cnot as a native gate. Supported operations for this Backend ARN are ['rz', 'cz', 'xy', 'rx', 'cphaseshift'].", + "evalue": "An error occurred (ValidationException) when calling the CreateQuantumTask operation: Backend ARN, arn:aws:braket:us-west-1::device/qpu/rigetti/Aspen-M-3, does not support the operation cnot as a native gate. Supported operations for this Backend ARN are ['rz', 'cz', 'xy', 'rx', 'cphaseshift'].", "output_type": "error", "traceback": [ "\u001b[0;31m---------------------------------------------------------------------------\u001b[0m", @@ -120,7 +120,7 @@ "File \u001b[0;32m~/.virtualenvs/pyqbench/lib/python3.9/site-packages/braket/aws/aws_session.py:180\u001b[0m, in \u001b[0;36mAwsSession.create_quantum_task\u001b[0;34m(self, **boto3_kwargs)\u001b[0m\n\u001b[1;32m 178\u001b[0m \u001b[38;5;28;01mif\u001b[39;00m job_token:\n\u001b[1;32m 179\u001b[0m boto3_kwargs\u001b[38;5;241m.\u001b[39mupdate({\u001b[38;5;124m\"\u001b[39m\u001b[38;5;124mjobToken\u001b[39m\u001b[38;5;124m\"\u001b[39m: job_token})\n\u001b[0;32m--> 180\u001b[0m response \u001b[38;5;241m=\u001b[39m \u001b[38;5;28;43mself\u001b[39;49m\u001b[38;5;241;43m.\u001b[39;49m\u001b[43mbraket_client\u001b[49m\u001b[38;5;241;43m.\u001b[39;49m\u001b[43mcreate_quantum_task\u001b[49m\u001b[43m(\u001b[49m\u001b[38;5;241;43m*\u001b[39;49m\u001b[38;5;241;43m*\u001b[39;49m\u001b[43mboto3_kwargs\u001b[49m\u001b[43m)\u001b[49m\n\u001b[1;32m 181\u001b[0m \u001b[38;5;28;01mreturn\u001b[39;00m response[\u001b[38;5;124m\"\u001b[39m\u001b[38;5;124mquantumTaskArn\u001b[39m\u001b[38;5;124m\"\u001b[39m]\n", "File \u001b[0;32m~/.virtualenvs/pyqbench/lib/python3.9/site-packages/botocore/client.py:508\u001b[0m, in \u001b[0;36mClientCreator._create_api_method.._api_call\u001b[0;34m(self, *args, **kwargs)\u001b[0m\n\u001b[1;32m 504\u001b[0m \u001b[38;5;28;01mraise\u001b[39;00m \u001b[38;5;167;01mTypeError\u001b[39;00m(\n\u001b[1;32m 505\u001b[0m \u001b[38;5;124mf\u001b[39m\u001b[38;5;124m\"\u001b[39m\u001b[38;5;132;01m{\u001b[39;00mpy_operation_name\u001b[38;5;132;01m}\u001b[39;00m\u001b[38;5;124m() only accepts keyword arguments.\u001b[39m\u001b[38;5;124m\"\u001b[39m\n\u001b[1;32m 506\u001b[0m )\n\u001b[1;32m 507\u001b[0m \u001b[38;5;66;03m# The \"self\" in this scope is referring to the BaseClient.\u001b[39;00m\n\u001b[0;32m--> 508\u001b[0m \u001b[38;5;28;01mreturn\u001b[39;00m \u001b[38;5;28;43mself\u001b[39;49m\u001b[38;5;241;43m.\u001b[39;49m\u001b[43m_make_api_call\u001b[49m\u001b[43m(\u001b[49m\u001b[43moperation_name\u001b[49m\u001b[43m,\u001b[49m\u001b[43m \u001b[49m\u001b[43mkwargs\u001b[49m\u001b[43m)\u001b[49m\n", "File \u001b[0;32m~/.virtualenvs/pyqbench/lib/python3.9/site-packages/botocore/client.py:915\u001b[0m, in \u001b[0;36mBaseClient._make_api_call\u001b[0;34m(self, operation_name, api_params)\u001b[0m\n\u001b[1;32m 913\u001b[0m error_code \u001b[38;5;241m=\u001b[39m parsed_response\u001b[38;5;241m.\u001b[39mget(\u001b[38;5;124m\"\u001b[39m\u001b[38;5;124mError\u001b[39m\u001b[38;5;124m\"\u001b[39m, {})\u001b[38;5;241m.\u001b[39mget(\u001b[38;5;124m\"\u001b[39m\u001b[38;5;124mCode\u001b[39m\u001b[38;5;124m\"\u001b[39m)\n\u001b[1;32m 914\u001b[0m error_class \u001b[38;5;241m=\u001b[39m \u001b[38;5;28mself\u001b[39m\u001b[38;5;241m.\u001b[39mexceptions\u001b[38;5;241m.\u001b[39mfrom_code(error_code)\n\u001b[0;32m--> 915\u001b[0m \u001b[38;5;28;01mraise\u001b[39;00m error_class(parsed_response, operation_name)\n\u001b[1;32m 916\u001b[0m \u001b[38;5;28;01melse\u001b[39;00m:\n\u001b[1;32m 917\u001b[0m \u001b[38;5;28;01mreturn\u001b[39;00m parsed_response\n", - "\u001b[0;31mValidationException\u001b[0m: An error occurred (ValidationException) when calling the CreateQuantumTask operation: Backend ARN, arn:aws:braket:us-west-1::device/qpu/rigetti/Aspen-M-2, does not support the operation cnot as a native gate. Supported operations for this Backend ARN are ['rz', 'cz', 'xy', 'rx', 'cphaseshift']." + "\u001b[0;31mValidationException\u001b[0m: An error occurred (ValidationException) when calling the CreateQuantumTask operation: Backend ARN, arn:aws:braket:us-west-1::device/qpu/rigetti/Aspen-M-3, does not support the operation cnot as a native gate. Supported operations for this Backend ARN are ['rz', 'cz', 'xy', 'rx', 'cphaseshift']." ] } ], diff --git a/docs/tutorials/0_tutorial_qiskit-braket-provider_overview.ipynb b/docs/tutorials/0_tutorial_qiskit-braket-provider_overview.ipynb index fdaea4cf..62159438 100644 --- a/docs/tutorials/0_tutorial_qiskit-braket-provider_overview.ipynb +++ b/docs/tutorials/0_tutorial_qiskit-braket-provider_overview.ipynb @@ -116,13 +116,15 @@ { "data": { "text/plain": [ - "[BraketBackend[Aspen-10],\n", + "[BraketBackend[Aria 1],\n", + " BraketBackend[Aspen-10],\n", " BraketBackend[Aspen-11],\n", " BraketBackend[Aspen-8],\n", " BraketBackend[Aspen-9],\n", " BraketBackend[Aspen-M-1],\n", " BraketBackend[Aspen-M-2],\n", - " BraketBackend[IonQ Device],\n", + " BraketBackend[Aspen-M-3],\n", + " BraketBackend[Harmony],\n", " BraketBackend[Lucy],\n", " BraketBackend[SV1],\n", " BraketBackend[TN1],\n", @@ -163,7 +165,7 @@ { "data": { "text/plain": [ - "BraketBackend[sv_simulator]" + "BraketBackend[default]" ] }, "execution_count": 4, @@ -223,7 +225,7 @@ { "data": { "text/plain": [ - "(BraketBackend[IonQ Device], BraketBackend[Aspen-M-1])" + "(BraketBackend[Harmony], BraketBackend[Aspen-M-1])" ] }, "execution_count": 6, @@ -232,7 +234,7 @@ } ], "source": [ - "ionq_device = provider.get_backend(\"IonQ Device\")\n", + "ionq_device = provider.get_backend(\"Harmony\")\n", "rigetti_device = provider.get_backend(\"Aspen-M-1\")\n", "\n", "ionq_device, rigetti_device" @@ -913,7 +915,7 @@ "name": "python", "nbconvert_exporter": "python", "pygments_lexer": "ipython3", - "version": "3.9.7" + "version": "3.9.6" } }, "nbformat": 4, diff --git a/qiskit_braket_provider/providers/adapter.py b/qiskit_braket_provider/providers/adapter.py index 6706574d..ab889f01 100644 --- a/qiskit_braket_provider/providers/adapter.py +++ b/qiskit_braket_provider/providers/adapter.py @@ -251,8 +251,10 @@ def aws_device_to_target(device: AwsDevice) -> Target: properties, (IonqDeviceCapabilities, RigettiDeviceCapabilities, OqcDeviceCapabilities), ): - action_properties: OpenQASMDeviceActionProperties = properties.action.get( - DeviceActionType.OPENQASM + action_properties: OpenQASMDeviceActionProperties = ( + properties.action.get(DeviceActionType.OPENQASM) + if properties.action.get(DeviceActionType.OPENQASM) + else properties.action.get(DeviceActionType.JAQCD) ) paradigm: GateModelQpuParadigmProperties = properties.paradigm connectivity = paradigm.connectivity From ccd0db7f9e1919496b6b0f4c1ca34ae097741a5a Mon Sep 17 00:00:00 2001 From: robotAstray Date: Wed, 14 Jun 2023 01:45:00 +0100 Subject: [PATCH 3/3] Replacing AWSBraketJob with AmazonBraketTask (#105) * replacing AWSBraketJob with AmazonBraketTask * run the notebooks containing AmazonBraketTask * deprecation warning added for AWSBraketJob class * formatting fixed * re-add * fix breaking changes on /provider/__init__.py and __init__.py * rename job_id to task_id argument for AmazonBraketTask() * rename braket_jobs_states to braket_tasks_states * add task_id method to access the task_id similar to the one we have in the JobV1 class * adding tests for new class 'AmazonBraketTask' and old class 'AWSBraketJob' * formatting test_braket_job.py * correcting definition of AWSBraketJob * rewriting line 184 in braket_job.py * adding class docstring to AWSBraketJob * standard import 'from warnings import warn' placed before 'from braket.aws import AwsQuantumTask' (wrong-import-order) * docstring fix in test_braket_job.py * assert the job id in test_AWS_job() function in test_braket_job.py * running how to notebook #0 * running how to notebook #1 * running how to notebook #2 * running how to notebook #3 * running how to notebook number 5 * running tutorial notebook number 3 * tutorial number 0 --- .../0_how_to_access_AWS_Braket_devices.ipynb | 6 +- ...ow_to_run_circuits_on_Braket_devices.ipynb | 123 ++++--- ...how_to_retrieve_results_from_backend.ipynb | 136 +++---- docs/how_tos/3_how_to_qiskit_hybrid_job.ipynb | 58 +-- docs/how_tos/4_how_to_verbatim_circuits.ipynb | 2 +- ...run_circuits_on_Braket_local_backend.ipynb | 20 +- ...rial_qiskit-braket-provider_overview.ipynb | 342 ++++++++++-------- .../3_tutorial_minimum_eigen_optimizer.ipynb | 194 ++++++---- qiskit_braket_provider/__init__.py | 3 +- qiskit_braket_provider/providers/__init__.py | 3 +- .../providers/braket_backend.py | 26 +- .../providers/braket_job.py | 52 ++- tests/providers/test_braket_backend.py | 8 +- tests/providers/test_braket_job.py | 45 ++- 14 files changed, 602 insertions(+), 416 deletions(-) diff --git a/docs/how_tos/0_how_to_access_AWS_Braket_devices.ipynb b/docs/how_tos/0_how_to_access_AWS_Braket_devices.ipynb index 32123f1d..733610c1 100644 --- a/docs/how_tos/0_how_to_access_AWS_Braket_devices.ipynb +++ b/docs/how_tos/0_how_to_access_AWS_Braket_devices.ipynb @@ -159,7 +159,7 @@ " 'description': 'AWS Device: Rigetti Aspen-M-3.',\n", " 'name': 'Aspen-M-3',\n", " 'number of qubits': 148,\n", - " 'online date': datetime.datetime(2023, 6, 8, 17, 35, 32, tzinfo=datetime.timezone.utc),\n", + " 'online date': datetime.datetime(2023, 6, 13, 21, 35, 32, tzinfo=datetime.timezone.utc),\n", " 'operations': [Instruction(name='measure', num_qubits=1, num_clbits=1, params=[]),\n", " Instruction(name='cz', num_qubits=2, num_clbits=0, params=[]),\n", " Instruction(name='cx', num_qubits=2, num_clbits=0, params=[]),\n", @@ -179,7 +179,7 @@ " 'description': 'AWS Device: Oxford Lucy.',\n", " 'name': 'Lucy',\n", " 'number of qubits': 8,\n", - " 'online date': datetime.datetime(2023, 6, 8, 17, 0, 8, tzinfo=datetime.timezone.utc),\n", + " 'online date': datetime.datetime(2023, 6, 13, 21, 0, 8, tzinfo=datetime.timezone.utc),\n", " 'operations': [Instruction(name='measure', num_qubits=1, num_clbits=1, params=[]),\n", " Instruction(name='cx', num_qubits=2, num_clbits=0, params=[]),\n", " Instruction(name='cp', num_qubits=2, num_clbits=0, params=[Parameter(theta)]),\n", @@ -381,7 +381,7 @@ "name": "python", "nbconvert_exporter": "python", "pygments_lexer": "ipython3", - "version": "3.9.6" + "version": "3.8.10" } }, "nbformat": 4, diff --git a/docs/how_tos/1_how_to_run_circuits_on_Braket_devices.ipynb b/docs/how_tos/1_how_to_run_circuits_on_Braket_devices.ipynb index b0947769..973a48c9 100644 --- a/docs/how_tos/1_how_to_run_circuits_on_Braket_devices.ipynb +++ b/docs/how_tos/1_how_to_run_circuits_on_Braket_devices.ipynb @@ -1,6 +1,7 @@ { "cells": [ { + "attachments": {}, "cell_type": "markdown", "id": "c74932e2", "metadata": {}, @@ -10,7 +11,7 @@ }, { "cell_type": "code", - "execution_count": null, + "execution_count": 1, "id": "f543c651", "metadata": {}, "outputs": [], @@ -23,6 +24,7 @@ ] }, { + "attachments": {}, "cell_type": "markdown", "id": "e306df72", "metadata": {}, @@ -32,40 +34,40 @@ }, { "cell_type": "code", - "execution_count": 12, + "execution_count": 2, "id": "ddc70eea", "metadata": {}, "outputs": [ { "data": { "text/html": [ - "
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-       "       └─────┘
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+       "q_2 -> 2 ───────────────────────■───────────────────────────────────────────────────────────────────┼─────────■────────────────────────────────────────■───┤ P(π/4) ├─────────────■───────────────■──────────────────────────\n",
+       "                         ┌─────────────┐    ┌───┐     ┌────────────┐    ┌───┐     ┌──────────────┐  │         │         ┌──────────┐    ┌────────┐     │   └────────┘             │               │                          \n",
+       "q_3 -> 3 ────────────────┤ P(0.069993) ├────┤ X ├─────┤ Ry(-3.065) ├────┤ X ├─────┤ P(-0.069993) ├──■─────────┼─────────┤ Ry(-π/2) ├────┤ Rz(-π) ├─────┼──────────────────────────┼───────────────┼──────────────────────────\n",
+       "                         └─┬─────────┬─┘    └─┬─┘     ├────────────┤    └─┬─┘     ├─────────────┬┘          ┌─┴─┐     ┌─┴──────────┴┐   └────────┘   ┌─┴─┐┌──────────┐┌────────┐┌─┴─┐┌─────────┐┌─┴─┐┌───────────┐┌─────────┐\n",
+       "q_4 -> 4 ──────────────────┤ Ry(π/2) ├────────■───────┤ Ry(-3.065) ├──────■───────┤ Ry(0.45197) ├───────────┤ X ├─────┤ Ry(-2.0228) ├────────────────┤ X ├┤ Ry(-π/2) ├┤ Rz(-π) ├┤ X ├┤ P(-π/4) ├┤ X ├┤ Rz(-3π/4) ├┤ Ry(π/2) ├\n",
+       "                           └─────────┘                └────────────┘              └─────────────┘           └───┘     └─────────────┘                └───┘└──────────┘└────────┘└───┘└─────────┘└───┘└───────────┘└─────────┘
" ], "text/plain": [ - "global phase: 4.8274\n", - " ┌───┐┌───┐┌─────┐┌───┐┌───┐┌───┐┌─────┐┌───┐┌───┐ ┌───┐ \n", - "q_0 -> 0 ───────────X────────────────────■─────────────────────────────■──┤ H ├┤ X ├┤ Tdg ├┤ X ├┤ T ├┤ X ├┤ Tdg ├┤ X ├┤ T ├─┤ H ├──────\n", - " │ ┌─────┐ │ ┌────────────┐ │ └───┘└─┬─┘└─────┘└─┬─┘└───┘└─┬─┘└─────┘└─┬─┘└───┘ └───┘ \n", - "q_1 -> 1 ───────────X───────────┤ Sdg ├──┼────────┤ Rx(3.9689) ├───────┼─────────┼───────────┼─────────┼───────────┼───────────────────\n", - " ┌─────────────────────┐└─────┘ │ └────────────┘ │ │ │ │ │ ┌───┐ \n", - "q_2 -> 2 ┤ P(6.13001602516006) ├───X─────┼─────────────────────────────┼─────────┼───────────■─────────┼───────────■────■───┤ T ├───■──\n", - " └────┬────────────┬───┘ │ ┌─┴─┐┌───────────────────────┐┌─┴─┐┌───┐ │ │ │ └───┘ │ \n", - "q_3 -> 3 ─────┤ P(-2.5863) ├───────┼───┤ X ├┤ Rz(-2.91151808057099) ├┤ X ├┤ S ├──┼─────────────────────┼────────────────┼───────────┼──\n", - " └──┬─────┬───┘ │ └───┘└───────────────────────┘└───┘└───┘ │ │ ┌───┐ ┌─┴─┐┌─────┐┌─┴─┐\n", - "q_4 -> 4 ────────┤ Tdg ├───────────X─────────────────────────────────────────────■─────────────────────■───┤ T ├──────┤ X ├┤ Tdg ├┤ X ├\n", - " └─────┘ └───┘ └───┘└─────┘└───┘" + "global phase: 2.0774\n", + " ┌───────────┐ ┌────┐ ┌────────────┐ \n", + "q_0 -> 0 ───────────────────────■───────┤ P(2.2423) ├─────┤ √X ├────┤ P(-1.7549) ├───────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────\n", + " ┌──────────────┐ │ ├───────────┴┐┌───┴────┴───┐└────────────┘ ┌───┐┌─────────────┐ ┌────────────┐┌──────────────┐ \n", + "q_1 -> 1 ┤ Rz(-0.14167) ├───────┼───────┤ Ry(2.4735) ├┤ Rz(2.9079) ├──────────────────────────────┤ X ├┤ Rz(-2.4203) ├─┤ Ry(2.2266) ├┤ Rz(-0.95318) ├────────────────────────────────────────────────────────────────────────\n", + " └──────────────┘ │ └────────────┘└────────────┘ └─┬─┘└─────────────┘ └────────────┘└──────────────┘ ┌────────┐ \n", + "q_2 -> 2 ───────────────────────■───────────────────────────────────────────────────────────────────┼─────────■────────────────────────────────────────■───┤ P(π/4) ├─────────────■───────────────■──────────────────────────\n", + " ┌─────────────┐ ┌───┐ ┌────────────┐ ┌───┐ ┌──────────────┐ │ │ ┌──────────┐ ┌────────┐ │ └────────┘ │ │ \n", + "q_3 -> 3 ────────────────┤ P(0.069993) ├────┤ X ├─────┤ Ry(-3.065) ├────┤ X ├─────┤ P(-0.069993) ├──■─────────┼─────────┤ Ry(-π/2) ├────┤ Rz(-π) ├─────┼──────────────────────────┼───────────────┼──────────────────────────\n", + " └─┬─────────┬─┘ └─┬─┘ ├────────────┤ └─┬─┘ ├─────────────┬┘ ┌─┴─┐ ┌─┴──────────┴┐ └────────┘ ┌─┴─┐┌──────────┐┌────────┐┌─┴─┐┌─────────┐┌─┴─┐┌───────────┐┌─────────┐\n", + "q_4 -> 4 ──────────────────┤ Ry(π/2) ├────────■───────┤ Ry(-3.065) ├──────■───────┤ Ry(0.45197) ├───────────┤ X ├─────┤ Ry(-2.0228) ├────────────────┤ X ├┤ Ry(-π/2) ├┤ Rz(-π) ├┤ X ├┤ P(-π/4) ├┤ X ├┤ Rz(-3π/4) ├┤ Ry(π/2) ├\n", + " └─────────┘ └────────────┘ └─────────────┘ └───┘ └─────────────┘ └───┘└──────────┘└────────┘└───┘└─────────┘└───┘└───────────┘└─────────┘" ] }, - "execution_count": 24, + "execution_count": 4, "metadata": {}, "output_type": "execute_result" } @@ -166,6 +170,7 @@ ] }, { + "attachments": {}, "cell_type": "markdown", "id": "fa7d65c1", "metadata": {}, @@ -175,7 +180,7 @@ }, { "cell_type": "code", - "execution_count": 14, + "execution_count": 5, "id": "fc6aa158", "metadata": {}, "outputs": [], @@ -185,18 +190,18 @@ }, { "cell_type": "code", - "execution_count": 20, + "execution_count": 6, "id": "a4ea3a45", "metadata": {}, "outputs": [ { "data": { - "image/png": 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\n", 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", "text/plain": [ - "
" + "
" ] }, - "execution_count": 20, + "execution_count": 6, "metadata": {}, "output_type": "execute_result" } @@ -222,7 +227,7 @@ "name": "python", "nbconvert_exporter": "python", "pygments_lexer": "ipython3", - "version": "3.9.7" + "version": "3.8.10" } }, "nbformat": 4, diff --git a/docs/how_tos/2_how_to_retrieve_results_from_backend.ipynb b/docs/how_tos/2_how_to_retrieve_results_from_backend.ipynb index 1e9a933f..bdedcf48 100644 --- a/docs/how_tos/2_how_to_retrieve_results_from_backend.ipynb +++ b/docs/how_tos/2_how_to_retrieve_results_from_backend.ipynb @@ -1,6 +1,7 @@ { "cells": [ { + "attachments": {}, "cell_type": "markdown", "id": "c74932e2", "metadata": {}, @@ -22,6 +23,7 @@ ] }, { + "attachments": {}, "cell_type": "markdown", "id": "e306df72", "metadata": {}, @@ -31,40 +33,40 @@ }, { "cell_type": "code", - "execution_count": 4, + "execution_count": 2, "id": "ddc70eea", "metadata": {}, "outputs": [ { "data": { "text/html": [ - "
                                                   ┌───┐\n",
-       "q_0: ─────X────────────■───────────────────────────┤ X ├\n",
-       "          │            │      ┌─────┐┌────────────┐└─┬─┘\n",
-       "q_1: ─────X────────────┼──────┤ Sdg ├┤ Rx(3.9689) ├──┼──\n",
-       "     ┌──────────┐      │      └─────┘└────────────┘  │  \n",
-       "q_2: ┤ U1(6.13) ├──────┼─────────X───────────────────■──\n",
-       "     └──┬───┬───┘┌─────┴─────┐   │       ┌───┐       │  \n",
-       "q_3: ───┤ T ├────┤ Rz(5.823) ├───┼───────┤ S ├───────┼──\n",
-       "       ┌┴───┴┐   └───────────┘   │       └───┘       │  \n",
-       "q_4: ──┤ Tdg ├───────────────────X───────────────────■──\n",
-       "       └─────┘
" + "
                                 ┌───┐┌───────────────────┐           \n",
+       "q_0: ──────────────────────────■─┤ Y ├┤ U2(6.0991,5.6116) ├───────────\n",
+       "       ┌───────────────────┐   │ ├───┤└┬──────────────────┤           \n",
+       "q_1: ──┤ R(4.3817,0.59173) ├───┼─┤ H ├─┤ R(4.7632,2.2276) ├───────────\n",
+       "       └───────────────────┘   │ └─┬─┘ └──────────────────┘           \n",
+       "q_2: ──────────────────────────■───┼────────────■────────────■────────\n",
+       "     ┌───────────────────────┐     │            │            │   ┌───┐\n",
+       "q_3: ┤0                      ├─────■────────────┼────────────┼───┤ H ├\n",
+       "     │  {XX+YY}(6.13,4.7824) │            ┌─────┴──────┐   ┌─┴──┐└───┘\n",
+       "q_4: ┤1                      ├────────────┤ Ry(4.0455) ├───┤ Sx ├─────\n",
+       "     └───────────────────────┘            └────────────┘   └────┘
" ], "text/plain": [ - " ┌───┐\n", - "q_0: ─────X────────────■───────────────────────────┤ X ├\n", - " │ │ ┌─────┐┌────────────┐└─┬─┘\n", - "q_1: ─────X────────────┼──────┤ Sdg ├┤ Rx(3.9689) ├──┼──\n", - " ┌──────────┐ │ └─────┘└────────────┘ │ \n", - "q_2: ┤ U1(6.13) ├──────┼─────────X───────────────────■──\n", - " └──┬───┬───┘┌─────┴─────┐ │ ┌───┐ │ \n", - "q_3: ───┤ T ├────┤ Rz(5.823) ├───┼───────┤ S ├───────┼──\n", - " ┌┴───┴┐ └───────────┘ │ └───┘ │ \n", - "q_4: ──┤ Tdg ├───────────────────X───────────────────■──\n", - " └─────┘ " + " ┌───┐┌───────────────────┐ \n", + "q_0: ──────────────────────────■─┤ Y ├┤ U2(6.0991,5.6116) ├───────────\n", + " ┌───────────────────┐ │ ├───┤└┬──────────────────┤ \n", + "q_1: ──┤ R(4.3817,0.59173) ├───┼─┤ H ├─┤ R(4.7632,2.2276) ├───────────\n", + " └───────────────────┘ │ └─┬─┘ └──────────────────┘ \n", + "q_2: ──────────────────────────■───┼────────────■────────────■────────\n", + " ┌───────────────────────┐ │ │ │ ┌───┐\n", + "q_3: ┤0 ├─────■────────────┼────────────┼───┤ H ├\n", + " │ {XX+YY}(6.13,4.7824) │ ┌─────┴──────┐ ┌─┴──┐└───┘\n", + "q_4: ┤1 ├────────────┤ Ry(4.0455) ├───┤ Sx ├─────\n", + " └───────────────────────┘ └────────────┘ └────┘ " ] }, - "execution_count": 4, + "execution_count": 2, "metadata": {}, "output_type": "execute_result" } @@ -75,6 +77,7 @@ ] }, { + "attachments": {}, "cell_type": "markdown", "id": "d96fb4ef", "metadata": {}, @@ -84,7 +87,7 @@ }, { "cell_type": "code", - "execution_count": 5, + "execution_count": 3, "id": "50522a02", "metadata": {}, "outputs": [ @@ -94,7 +97,7 @@ "BraketBackend[SV1]" ] }, - "execution_count": 5, + "execution_count": 3, "metadata": {}, "output_type": "execute_result" } @@ -106,6 +109,7 @@ ] }, { + "attachments": {}, "cell_type": "markdown", "id": "a9963aac", "metadata": {}, @@ -115,7 +119,7 @@ }, { "cell_type": "code", - "execution_count": 6, + "execution_count": 4, "id": "efd93336", "metadata": { "scrolled": true @@ -124,35 +128,35 @@ { "data": { "text/html": [ - "
global phase: 4.8274\n",
-       "                                                                          ┌───┐┌───┐┌─────┐┌───┐┌───┐┌───┐┌─────┐┌───┐┌───┐ ┌───┐      \n",
-       "q_0 -> 0 ───────────X────────────────────■─────────────────────────────■──┤ H ├┤ X ├┤ Tdg ├┤ X ├┤ T ├┤ X ├┤ Tdg ├┤ X ├┤ T ├─┤ H ├──────\n",
-       "                    │           ┌─────┐  │        ┌────────────┐       │  └───┘└─┬─┘└─────┘└─┬─┘└───┘└─┬─┘└─────┘└─┬─┘└───┘ └───┘      \n",
-       "q_1 -> 1 ───────────X───────────┤ Sdg ├──┼────────┤ Rx(3.9689) ├───────┼─────────┼───────────┼─────────┼───────────┼───────────────────\n",
-       "         ┌─────────────────────┐└─────┘  │        └────────────┘       │         │           │         │           │        ┌───┐      \n",
-       "q_2 -> 2 ┤ P(6.13001602516006) ├───X─────┼─────────────────────────────┼─────────┼───────────■─────────┼───────────■────■───┤ T ├───■──\n",
-       "         └────┬────────────┬───┘   │   ┌─┴─┐┌───────────────────────┐┌─┴─┐┌───┐  │                     │                │   └───┘   │  \n",
-       "q_3 -> 3 ─────┤ P(-2.5863) ├───────┼───┤ X ├┤ Rz(-2.91151808057099) ├┤ X ├┤ S ├──┼─────────────────────┼────────────────┼───────────┼──\n",
-       "              └──┬─────┬───┘       │   └───┘└───────────────────────┘└───┘└───┘  │                     │   ┌───┐      ┌─┴─┐┌─────┐┌─┴─┐\n",
-       "q_4 -> 4 ────────┤ Tdg ├───────────X─────────────────────────────────────────────■─────────────────────■───┤ T ├──────┤ X ├┤ Tdg ├┤ X ├\n",
-       "                 └─────┘                                                                                   └───┘      └───┘└─────┘└───┘
" + "
global phase: 2.0774\n",
+       "                                        ┌───────────┐     ┌────┐    ┌────────────┐                                                                                                                                           \n",
+       "q_0 -> 0 ───────────────────────■───────┤ P(2.2423) ├─────┤ √X ├────┤ P(-1.7549) ├───────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────\n",
+       "         ┌──────────────┐       │       ├───────────┴┐┌───┴────┴───┐└────────────┘                ┌───┐┌─────────────┐ ┌────────────┐┌──────────────┐                                                                        \n",
+       "q_1 -> 1 ┤ Rz(-0.14167) ├───────┼───────┤ Ry(2.4735) ├┤ Rz(2.9079) ├──────────────────────────────┤ X ├┤ Rz(-2.4203) ├─┤ Ry(2.2266) ├┤ Rz(-0.95318) ├────────────────────────────────────────────────────────────────────────\n",
+       "         └──────────────┘       │       └────────────┘└────────────┘                              └─┬─┘└─────────────┘ └────────────┘└──────────────┘      ┌────────┐                                                        \n",
+       "q_2 -> 2 ───────────────────────■───────────────────────────────────────────────────────────────────┼─────────■────────────────────────────────────────■───┤ P(π/4) ├─────────────■───────────────■──────────────────────────\n",
+       "                         ┌─────────────┐    ┌───┐     ┌────────────┐    ┌───┐     ┌──────────────┐  │         │         ┌──────────┐    ┌────────┐     │   └────────┘             │               │                          \n",
+       "q_3 -> 3 ────────────────┤ P(0.069993) ├────┤ X ├─────┤ Ry(-3.065) ├────┤ X ├─────┤ P(-0.069993) ├──■─────────┼─────────┤ Ry(-π/2) ├────┤ Rz(-π) ├─────┼──────────────────────────┼───────────────┼──────────────────────────\n",
+       "                         └─┬─────────┬─┘    └─┬─┘     ├────────────┤    └─┬─┘     ├─────────────┬┘          ┌─┴─┐     ┌─┴──────────┴┐   └────────┘   ┌─┴─┐┌──────────┐┌────────┐┌─┴─┐┌─────────┐┌─┴─┐┌───────────┐┌─────────┐\n",
+       "q_4 -> 4 ──────────────────┤ Ry(π/2) ├────────■───────┤ Ry(-3.065) ├──────■───────┤ Ry(0.45197) ├───────────┤ X ├─────┤ Ry(-2.0228) ├────────────────┤ X ├┤ Ry(-π/2) ├┤ Rz(-π) ├┤ X ├┤ P(-π/4) ├┤ X ├┤ Rz(-3π/4) ├┤ Ry(π/2) ├\n",
+       "                           └─────────┘                └────────────┘              └─────────────┘           └───┘     └─────────────┘                └───┘└──────────┘└────────┘└───┘└─────────┘└───┘└───────────┘└─────────┘
" ], "text/plain": [ - "global phase: 4.8274\n", - " ┌───┐┌───┐┌─────┐┌───┐┌───┐┌───┐┌─────┐┌───┐┌───┐ ┌───┐ \n", - "q_0 -> 0 ───────────X────────────────────■─────────────────────────────■──┤ H ├┤ X ├┤ Tdg ├┤ X ├┤ T ├┤ X ├┤ Tdg ├┤ X ├┤ T ├─┤ H ├──────\n", - " │ ┌─────┐ │ ┌────────────┐ │ └───┘└─┬─┘└─────┘└─┬─┘└───┘└─┬─┘└─────┘└─┬─┘└───┘ └───┘ \n", - "q_1 -> 1 ───────────X───────────┤ Sdg ├──┼────────┤ Rx(3.9689) ├───────┼─────────┼───────────┼─────────┼───────────┼───────────────────\n", - " ┌─────────────────────┐└─────┘ │ └────────────┘ │ │ │ │ │ ┌───┐ \n", - "q_2 -> 2 ┤ P(6.13001602516006) ├───X─────┼─────────────────────────────┼─────────┼───────────■─────────┼───────────■────■───┤ T ├───■──\n", - " └────┬────────────┬───┘ │ ┌─┴─┐┌───────────────────────┐┌─┴─┐┌───┐ │ │ │ └───┘ │ \n", - "q_3 -> 3 ─────┤ P(-2.5863) ├───────┼───┤ X ├┤ Rz(-2.91151808057099) ├┤ X ├┤ S ├──┼─────────────────────┼────────────────┼───────────┼──\n", - " └──┬─────┬───┘ │ └───┘└───────────────────────┘└───┘└───┘ │ │ ┌───┐ ┌─┴─┐┌─────┐┌─┴─┐\n", - "q_4 -> 4 ────────┤ Tdg ├───────────X─────────────────────────────────────────────■─────────────────────■───┤ T ├──────┤ X ├┤ Tdg ├┤ X ├\n", - " └─────┘ └───┘ └───┘└─────┘└───┘" + "global phase: 2.0774\n", + " ┌───────────┐ ┌────┐ ┌────────────┐ \n", + "q_0 -> 0 ───────────────────────■───────┤ P(2.2423) ├─────┤ √X ├────┤ P(-1.7549) ├───────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────\n", + " ┌──────────────┐ │ ├───────────┴┐┌───┴────┴───┐└────────────┘ ┌───┐┌─────────────┐ ┌────────────┐┌──────────────┐ \n", + "q_1 -> 1 ┤ Rz(-0.14167) ├───────┼───────┤ Ry(2.4735) ├┤ Rz(2.9079) ├──────────────────────────────┤ X ├┤ Rz(-2.4203) ├─┤ Ry(2.2266) ├┤ Rz(-0.95318) ├────────────────────────────────────────────────────────────────────────\n", + " └──────────────┘ │ └────────────┘└────────────┘ └─┬─┘└─────────────┘ └────────────┘└──────────────┘ ┌────────┐ \n", + "q_2 -> 2 ───────────────────────■───────────────────────────────────────────────────────────────────┼─────────■────────────────────────────────────────■───┤ P(π/4) ├─────────────■───────────────■──────────────────────────\n", + " ┌─────────────┐ ┌───┐ ┌────────────┐ ┌───┐ ┌──────────────┐ │ │ ┌──────────┐ ┌────────┐ │ └────────┘ │ │ \n", + "q_3 -> 3 ────────────────┤ P(0.069993) ├────┤ X ├─────┤ Ry(-3.065) ├────┤ X ├─────┤ P(-0.069993) ├──■─────────┼─────────┤ Ry(-π/2) ├────┤ Rz(-π) ├─────┼──────────────────────────┼───────────────┼──────────────────────────\n", + " └─┬─────────┬─┘ └─┬─┘ ├────────────┤ └─┬─┘ ├─────────────┬┘ ┌─┴─┐ ┌─┴──────────┴┐ └────────┘ ┌─┴─┐┌──────────┐┌────────┐┌─┴─┐┌─────────┐┌─┴─┐┌───────────┐┌─────────┐\n", + "q_4 -> 4 ──────────────────┤ Ry(π/2) ├────────■───────┤ Ry(-3.065) ├──────■───────┤ Ry(0.45197) ├───────────┤ X ├─────┤ Ry(-2.0228) ├────────────────┤ X ├┤ Ry(-π/2) ├┤ Rz(-π) ├┤ X ├┤ P(-π/4) ├┤ X ├┤ Rz(-3π/4) ├┤ Ry(π/2) ├\n", + " └─────────┘ └────────────┘ └─────────────┘ └───┘ └─────────────┘ └───┘└──────────┘└────────┘└───┘└─────────┘└───┘└───────────┘└─────────┘" ] }, - "execution_count": 6, + "execution_count": 4, "metadata": {}, "output_type": "execute_result" } @@ -163,6 +167,7 @@ ] }, { + "attachments": {}, "cell_type": "markdown", "id": "fa7d65c1", "metadata": {}, @@ -172,7 +177,7 @@ }, { "cell_type": "code", - "execution_count": 7, + "execution_count": 5, "id": "fc6aa158", "metadata": {}, "outputs": [], @@ -182,17 +187,17 @@ }, { "cell_type": "code", - "execution_count": 8, + "execution_count": 6, "id": "a4ea3a45", "metadata": {}, "outputs": [ { "data": { "text/plain": [ - "'Task id 3e6b6feb-fdc9-42c3-a7ba-0c4cd94089e2'" + "'Task id b171d67b-e8c4-4ec6-b548-1b6e8f7c6c38'" ] }, - "execution_count": 8, + "execution_count": 6, "metadata": {}, "output_type": "execute_result" } @@ -202,6 +207,7 @@ ] }, { + "attachments": {}, "cell_type": "markdown", "id": "83222235", "metadata": {}, @@ -211,39 +217,39 @@ }, { "cell_type": "code", - "execution_count": 10, + "execution_count": 8, "id": "f65cd41c", "metadata": {}, "outputs": [ { "data": { "text/plain": [ - "" + "" ] }, - "execution_count": 10, + "execution_count": 8, "metadata": {}, "output_type": "execute_result" } ], "source": [ - "retrieved_job = backend.retrieve_job(job_id=job.job_id())\n", + "retrieved_job = backend.retrieve_job(task_id=job.job_id())\n", "retrieved_job" ] }, { "cell_type": "code", - "execution_count": 12, + "execution_count": 9, "id": "652bf407", "metadata": {}, "outputs": [ { "data": { "text/plain": [ - "{'00010': 7, '00000': 3}" + "{'00001': 4, '01011': 1, '01000': 1, '00011': 3, '01001': 1}" ] }, - "execution_count": 12, + "execution_count": 9, "metadata": {}, "output_type": "execute_result" } @@ -255,7 +261,7 @@ ], "metadata": { "kernelspec": { - "display_name": "Python 3 (ipykernel)", + "display_name": "Python 3", "language": "python", "name": "python3" }, @@ -269,7 +275,7 @@ "name": "python", "nbconvert_exporter": "python", "pygments_lexer": "ipython3", - "version": "3.9.7" + "version": "3.8.10" } }, "nbformat": 4, diff --git a/docs/how_tos/3_how_to_qiskit_hybrid_job.ipynb b/docs/how_tos/3_how_to_qiskit_hybrid_job.ipynb index 34b97ec0..edc8864a 100644 --- a/docs/how_tos/3_how_to_qiskit_hybrid_job.ipynb +++ b/docs/how_tos/3_how_to_qiskit_hybrid_job.ipynb @@ -1,6 +1,7 @@ { "cells": [ { + "attachments": {}, "cell_type": "markdown", "id": "508d0758", "metadata": {}, @@ -9,6 +10,7 @@ ] }, { + "attachments": {}, "cell_type": "markdown", "id": "d11f022a", "metadata": {}, @@ -17,6 +19,7 @@ ] }, { + "attachments": {}, "cell_type": "markdown", "id": "f108e253", "metadata": {}, @@ -26,7 +29,7 @@ }, { "cell_type": "code", - "execution_count": 2, + "execution_count": 1, "id": "5f01867f", "metadata": {}, "outputs": [ @@ -34,23 +37,23 @@ "name": "stdout", "output_type": "stream", "text": [ - "\"\"\"Example of usage of Qiskit-Braket provider.\"\"\"\r\n", - "from qiskit import QuantumCircuit\r\n", - "from qiskit_braket_provider import AWSBraketProvider\r\n", - "\r\n", - "from braket.jobs import save_job_result\r\n", - "\r\n", - "\r\n", - "provider = AWSBraketProvider()\r\n", - "backend = provider.get_backend(\"SV1\")\r\n", - "circuit = QuantumCircuit(2)\r\n", - "circuit.h(0)\r\n", - "circuit.cx(0, 1)\r\n", - "\r\n", - "results = backend.run(circuit, shots=1)\r\n", - "\r\n", - "print(results.result().get_counts())\r\n", - "save_job_result(results.result().get_counts())\r\n" + "\"\"\"Example of usage of Qiskit-Braket provider.\"\"\"\n", + "from qiskit import QuantumCircuit\n", + "from qiskit_braket_provider import AWSBraketProvider\n", + "\n", + "from braket.jobs import save_job_result\n", + "\n", + "\n", + "provider = AWSBraketProvider()\n", + "backend = provider.get_backend(\"SV1\")\n", + "circuit = QuantumCircuit(2)\n", + "circuit.h(0)\n", + "circuit.cx(0, 1)\n", + "\n", + "results = backend.run(circuit, shots=1)\n", + "\n", + "print(results.result().get_counts())\n", + "save_job_result(results.result().get_counts())\n" ] } ], @@ -59,6 +62,7 @@ ] }, { + "attachments": {}, "cell_type": "markdown", "id": "547c4880", "metadata": {}, @@ -68,7 +72,7 @@ }, { "cell_type": "code", - "execution_count": 4, + "execution_count": 2, "id": "6b352997", "metadata": {}, "outputs": [ @@ -76,11 +80,11 @@ "name": "stdout", "output_type": "stream", "text": [ - "FROM 292282985366.dkr.ecr.us-west-2.amazonaws.com/amazon-braket-base-jobs:1.0-cpu-py37-ubuntu18.04\r\n", - "\r\n", - "RUN python3 -m pip install --upgrade pip\r\n", - "\r\n", - "RUN python3 -m pip install --no-cache --upgrade git+https://github.com/qiskit-community/qiskit-braket-provider\r\n" + "FROM 292282985366.dkr.ecr.us-west-2.amazonaws.com/amazon-braket-base-jobs:1.0-cpu-py37-ubuntu18.04\n", + "\n", + "RUN python3 -m pip install --upgrade pip\n", + "\n", + "RUN python3 -m pip install --no-cache --upgrade git+https://github.com/qiskit-community/qiskit-braket-provider\n" ] } ], @@ -89,6 +93,7 @@ ] }, { + "attachments": {}, "cell_type": "markdown", "id": "ab26ae15", "metadata": {}, @@ -97,6 +102,7 @@ ] }, { + "attachments": {}, "cell_type": "markdown", "id": "825395d8", "metadata": {}, @@ -113,6 +119,7 @@ ] }, { + "attachments": {}, "cell_type": "markdown", "id": "f1b487b7", "metadata": {}, @@ -129,6 +136,7 @@ ] }, { + "attachments": {}, "cell_type": "markdown", "id": "cd52d73c", "metadata": {}, @@ -200,7 +208,7 @@ "name": "python", "nbconvert_exporter": "python", "pygments_lexer": "ipython3", - "version": "3.9.7" + "version": "3.8.10" } }, "nbformat": 4, diff --git a/docs/how_tos/4_how_to_verbatim_circuits.ipynb b/docs/how_tos/4_how_to_verbatim_circuits.ipynb index 8c70ae71..165a0b45 100644 --- a/docs/how_tos/4_how_to_verbatim_circuits.ipynb +++ b/docs/how_tos/4_how_to_verbatim_circuits.ipynb @@ -106,7 +106,7 @@ "\u001b[0;31mValidationException\u001b[0m Traceback (most recent call last)", "Input \u001b[0;32mIn [3]\u001b[0m, in \u001b[0;36m\u001b[0;34m()\u001b[0m\n\u001b[0;32m----> 1\u001b[0m \u001b[43maspen\u001b[49m\u001b[38;5;241;43m.\u001b[39;49m\u001b[43mrun\u001b[49m\u001b[43m(\u001b[49m\u001b[43mcircuit\u001b[49m\u001b[43m,\u001b[49m\u001b[43m \u001b[49m\u001b[43mverbatim\u001b[49m\u001b[38;5;241;43m=\u001b[39;49m\u001b[38;5;28;43;01mTrue\u001b[39;49;00m\u001b[43m,\u001b[49m\u001b[43m \u001b[49m\u001b[43mdisable_qubit_rewiring\u001b[49m\u001b[38;5;241;43m=\u001b[39;49m\u001b[38;5;28;43;01mTrue\u001b[39;49;00m\u001b[43m)\u001b[49m\n", "File \u001b[0;32m~/Projects/qiskit-braket-provider/qiskit_braket_provider/providers/braket_backend.py:251\u001b[0m, in \u001b[0;36mAWSBraketBackend.run\u001b[0;34m(self, run_input, **options)\u001b[0m\n\u001b[1;32m 248\u001b[0m \u001b[38;5;28;01mif\u001b[39;00m options\u001b[38;5;241m.\u001b[39mpop(\u001b[38;5;124m\"\u001b[39m\u001b[38;5;124mverbatim\u001b[39m\u001b[38;5;124m\"\u001b[39m, \u001b[38;5;28;01mFalse\u001b[39;00m):\n\u001b[1;32m 249\u001b[0m braket_circuits \u001b[38;5;241m=\u001b[39m wrap_circuits_in_verbatim_box(braket_circuits)\n\u001b[0;32m--> 251\u001b[0m batch_task: AwsQuantumTaskBatch \u001b[38;5;241m=\u001b[39m \u001b[38;5;28;43mself\u001b[39;49m\u001b[38;5;241;43m.\u001b[39;49m\u001b[43m_device\u001b[49m\u001b[38;5;241;43m.\u001b[39;49m\u001b[43mrun_batch\u001b[49m\u001b[43m(\u001b[49m\n\u001b[1;32m 252\u001b[0m \u001b[43m \u001b[49m\u001b[43mbraket_circuits\u001b[49m\u001b[43m,\u001b[49m\u001b[43m \u001b[49m\u001b[38;5;241;43m*\u001b[39;49m\u001b[38;5;241;43m*\u001b[39;49m\u001b[43moptions\u001b[49m\n\u001b[1;32m 253\u001b[0m \u001b[43m\u001b[49m\u001b[43m)\u001b[49m\n\u001b[1;32m 254\u001b[0m tasks: List[AwsQuantumTask] \u001b[38;5;241m=\u001b[39m batch_task\u001b[38;5;241m.\u001b[39mtasks\n\u001b[1;32m 255\u001b[0m job_id \u001b[38;5;241m=\u001b[39m TASK_ID_DIVIDER\u001b[38;5;241m.\u001b[39mjoin(task\u001b[38;5;241m.\u001b[39mid \u001b[38;5;28;01mfor\u001b[39;00m task \u001b[38;5;129;01min\u001b[39;00m tasks)\n", - "File \u001b[0;32m~/.virtualenvs/pyqbench/lib/python3.9/site-packages/braket/aws/aws_device.py:208\u001b[0m, in \u001b[0;36mAwsDevice.run_batch\u001b[0;34m(self, task_specifications, s3_destination_folder, shots, max_parallel, max_connections, poll_timeout_seconds, poll_interval_seconds, *aws_quantum_task_args, **aws_quantum_task_kwargs)\u001b[0m\n\u001b[1;32m 165\u001b[0m \u001b[38;5;28;01mdef\u001b[39;00m \u001b[38;5;21mrun_batch\u001b[39m(\n\u001b[1;32m 166\u001b[0m \u001b[38;5;28mself\u001b[39m,\n\u001b[1;32m 167\u001b[0m task_specifications: List[Union[Circuit, Problem, OpenQasmProgram, BlackbirdProgram]],\n\u001b[0;32m (...)\u001b[0m\n\u001b[1;32m 175\u001b[0m \u001b[38;5;241m*\u001b[39m\u001b[38;5;241m*\u001b[39maws_quantum_task_kwargs,\n\u001b[1;32m 176\u001b[0m ) \u001b[38;5;241m-\u001b[39m\u001b[38;5;241m>\u001b[39m AwsQuantumTaskBatch:\n\u001b[1;32m 177\u001b[0m \u001b[38;5;124;03m\"\"\"Executes a batch of tasks in parallel\u001b[39;00m\n\u001b[1;32m 178\u001b[0m \n\u001b[1;32m 179\u001b[0m \u001b[38;5;124;03m Args:\u001b[39;00m\n\u001b[0;32m (...)\u001b[0m\n\u001b[1;32m 206\u001b[0m \u001b[38;5;124;03m `braket.aws.aws_quantum_task_batch.AwsQuantumTaskBatch`\u001b[39;00m\n\u001b[1;32m 207\u001b[0m \u001b[38;5;124;03m \"\"\"\u001b[39;00m\n\u001b[0;32m--> 208\u001b[0m \u001b[38;5;28;01mreturn\u001b[39;00m \u001b[43mAwsQuantumTaskBatch\u001b[49m\u001b[43m(\u001b[49m\n\u001b[1;32m 209\u001b[0m \u001b[43m \u001b[49m\u001b[43mAwsSession\u001b[49m\u001b[38;5;241;43m.\u001b[39;49m\u001b[43mcopy_session\u001b[49m\u001b[43m(\u001b[49m\u001b[38;5;28;43mself\u001b[39;49m\u001b[38;5;241;43m.\u001b[39;49m\u001b[43m_aws_session\u001b[49m\u001b[43m,\u001b[49m\u001b[43m \u001b[49m\u001b[43mmax_connections\u001b[49m\u001b[38;5;241;43m=\u001b[39;49m\u001b[43mmax_connections\u001b[49m\u001b[43m)\u001b[49m\u001b[43m,\u001b[49m\n\u001b[1;32m 210\u001b[0m \u001b[43m 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\u001b[49m\u001b[38;5;241;43m*\u001b[39;49m\u001b[43maws_quantum_task_args\u001b[49m\u001b[43m,\u001b[49m\n\u001b[1;32m 225\u001b[0m \u001b[43m \u001b[49m\u001b[38;5;241;43m*\u001b[39;49m\u001b[38;5;241;43m*\u001b[39;49m\u001b[43maws_quantum_task_kwargs\u001b[49m\u001b[43m,\u001b[49m\n\u001b[1;32m 226\u001b[0m \u001b[43m \u001b[49m\u001b[43m)\u001b[49m\n", + "File \u001b[0;32m~/.virtualenvs/pyqbench/lib/python3.9/site-packages/braket/aws/aws_device.py:208\u001b[0m, in \u001b[0;36mAwsDevice.run_batch\u001b[0;34m(self, task_specifications, s3_destination_folder, shots, max_parallel, max_connections, poll_timeout_seconds, poll_interval_seconds, *aws_quantum_task_args, **aws_quantum_task_kwargs)\u001b[0m\n\u001b[1;32m 165\u001b[0m \u001b[38;5;28;01mdef\u001b[39;00m \u001b[38;5;21mrun_batch\u001b[39m(\n\u001b[1;32m 166\u001b[0m \u001b[38;5;28mself\u001b[39m,\n\u001b[1;32m 167\u001b[0m task_specifications: List[Union[Circuit, Problem, OpenQasmProgram, BlackbirdProgram]],\n\u001b[0;32m (...)\u001b[0m\n\u001b[1;32m 175\u001b[0m \u001b[38;5;241m*\u001b[39m\u001b[38;5;241m*\u001b[39maws_quantum_task_kwargs,\n\u001b[1;32m 176\u001b[0m ) \u001b[38;5;241m-\u001b[39m\u001b[38;5;241m>\u001b[39m AwsQuantumTaskBatch:\n\u001b[1;32m 177\u001b[0m \u001b[38;5;124;03m\"\"\"Executes a batch of tasks in parallel\u001b[39;00m\n\u001b[1;32m 178\u001b[0m \n\u001b[1;32m 179\u001b[0m \u001b[38;5;124;03m Args:\u001b[39;00m\n\u001b[0;32m (...)\u001b[0m\n\u001b[1;32m 206\u001b[0m \u001b[38;5;124;03m `braket.aws.aws_quantum_task_batch.AwsQuantumTaskBatch`\u001b[39;00m\n\u001b[1;32m 207\u001b[0m \u001b[38;5;124;03m \"\"\"\u001b[39;00m\n\u001b[0;32m--> 208\u001b[0m \u001b[38;5;28;01mreturn\u001b[39;00m \u001b[43mAwsQuantumTaskBatch\u001b[49m\u001b[43m(\u001b[49m\n\u001b[1;32m 209\u001b[0m \u001b[43m \u001b[49m\u001b[43mAwsSession\u001b[49m\u001b[38;5;241;43m.\u001b[39;49m\u001b[43mcopy_session\u001b[49m\u001b[43m(\u001b[49m\u001b[38;5;28;43mself\u001b[39;49m\u001b[38;5;241;43m.\u001b[39;49m\u001b[43m_aws_session\u001b[49m\u001b[43m,\u001b[49m\u001b[43m \u001b[49m\u001b[43mmax_connections\u001b[49m\u001b[38;5;241;43m=\u001b[39;49m\u001b[43mmax_connections\u001b[49m\u001b[43m)\u001b[49m\u001b[43m,\u001b[49m\n\u001b[1;32m 210\u001b[0m \u001b[43m \u001b[49m\u001b[38;5;28;43mself\u001b[39;49m\u001b[38;5;241;43m.\u001b[39;49m\u001b[43m_arn\u001b[49m\u001b[43m,\u001b[49m\n\u001b[1;32m 211\u001b[0m \u001b[43m \u001b[49m\u001b[43mtask_specifications\u001b[49m\u001b[43m,\u001b[49m\n\u001b[1;32m 212\u001b[0m \u001b[43m \u001b[49m\u001b[43ms3_destination_folder\u001b[49m\n\u001b[1;32m 213\u001b[0m \u001b[43m \u001b[49m\u001b[38;5;129;43;01mor\u001b[39;49;00m\u001b[43m \u001b[49m\u001b[43m(\u001b[49m\n\u001b[1;32m 214\u001b[0m \u001b[43m 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\u001b[0;32m~/.virtualenvs/pyqbench/lib/python3.9/site-packages/braket/aws/aws_quantum_task_batch.py:83\u001b[0m, in \u001b[0;36mAwsQuantumTaskBatch.__init__\u001b[0;34m(self, aws_session, device_arn, task_specifications, s3_destination_folder, shots, max_parallel, max_workers, poll_timeout_seconds, poll_interval_seconds, *aws_quantum_task_args, **aws_quantum_task_kwargs)\u001b[0m\n\u001b[1;32m 42\u001b[0m \u001b[38;5;28;01mdef\u001b[39;00m \u001b[38;5;21m__init__\u001b[39m(\n\u001b[1;32m 43\u001b[0m \u001b[38;5;28mself\u001b[39m,\n\u001b[1;32m 44\u001b[0m aws_session: AwsSession,\n\u001b[0;32m (...)\u001b[0m\n\u001b[1;32m 54\u001b[0m \u001b[38;5;241m*\u001b[39m\u001b[38;5;241m*\u001b[39maws_quantum_task_kwargs,\n\u001b[1;32m 55\u001b[0m ):\n\u001b[1;32m 56\u001b[0m \u001b[38;5;124;03m\"\"\"Creates a batch of quantum tasks.\u001b[39;00m\n\u001b[1;32m 57\u001b[0m \n\u001b[1;32m 58\u001b[0m \u001b[38;5;124;03m Args:\u001b[39;00m\n\u001b[0;32m (...)\u001b[0m\n\u001b[1;32m 81\u001b[0m \u001b[38;5;124;03m `braket.aws.aws_quantum_task.AwsQuantumTask.create()`.\u001b[39;00m\n\u001b[1;32m 82\u001b[0m \u001b[38;5;124;03m \"\"\"\u001b[39;00m\n\u001b[0;32m---> 83\u001b[0m \u001b[38;5;28mself\u001b[39m\u001b[38;5;241m.\u001b[39m_tasks \u001b[38;5;241m=\u001b[39m \u001b[43mAwsQuantumTaskBatch\u001b[49m\u001b[38;5;241;43m.\u001b[39;49m\u001b[43m_execute\u001b[49m\u001b[43m(\u001b[49m\n\u001b[1;32m 84\u001b[0m \u001b[43m \u001b[49m\u001b[43maws_session\u001b[49m\u001b[43m,\u001b[49m\n\u001b[1;32m 85\u001b[0m \u001b[43m \u001b[49m\u001b[43mdevice_arn\u001b[49m\u001b[43m,\u001b[49m\n\u001b[1;32m 86\u001b[0m \u001b[43m \u001b[49m\u001b[43mtask_specifications\u001b[49m\u001b[43m,\u001b[49m\n\u001b[1;32m 87\u001b[0m \u001b[43m \u001b[49m\u001b[43ms3_destination_folder\u001b[49m\u001b[43m,\u001b[49m\n\u001b[1;32m 88\u001b[0m \u001b[43m \u001b[49m\u001b[43mshots\u001b[49m\u001b[43m,\u001b[49m\n\u001b[1;32m 89\u001b[0m \u001b[43m 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]\n\u001b[0;32m--> 151\u001b[0m tasks \u001b[38;5;241m=\u001b[39m [future\u001b[38;5;241m.\u001b[39mresult() \u001b[38;5;28;01mfor\u001b[39;00m future \u001b[38;5;129;01min\u001b[39;00m task_futures]\n\u001b[1;32m 152\u001b[0m \u001b[38;5;28;01mreturn\u001b[39;00m tasks\n", "File \u001b[0;32m~/.virtualenvs/pyqbench/lib/python3.9/site-packages/braket/aws/aws_quantum_task_batch.py:151\u001b[0m, in \u001b[0;36m\u001b[0;34m(.0)\u001b[0m\n\u001b[1;32m 134\u001b[0m \u001b[38;5;28;01mwith\u001b[39;00m ThreadPoolExecutor(max_workers\u001b[38;5;241m=\u001b[39mmax_threads) \u001b[38;5;28;01mas\u001b[39;00m executor:\n\u001b[1;32m 135\u001b[0m task_futures \u001b[38;5;241m=\u001b[39m [\n\u001b[1;32m 136\u001b[0m executor\u001b[38;5;241m.\u001b[39msubmit(\n\u001b[1;32m 137\u001b[0m AwsQuantumTaskBatch\u001b[38;5;241m.\u001b[39m_create_task,\n\u001b[0;32m (...)\u001b[0m\n\u001b[1;32m 149\u001b[0m \u001b[38;5;28;01mfor\u001b[39;00m task \u001b[38;5;129;01min\u001b[39;00m task_specifications\n\u001b[1;32m 150\u001b[0m ]\n\u001b[0;32m--> 151\u001b[0m tasks \u001b[38;5;241m=\u001b[39m [\u001b[43mfuture\u001b[49m\u001b[38;5;241;43m.\u001b[39;49m\u001b[43mresult\u001b[49m\u001b[43m(\u001b[49m\u001b[43m)\u001b[49m \u001b[38;5;28;01mfor\u001b[39;00m future \u001b[38;5;129;01min\u001b[39;00m task_futures]\n\u001b[1;32m 152\u001b[0m \u001b[38;5;28;01mreturn\u001b[39;00m tasks\n", diff --git a/docs/how_tos/5_how_to_run_circuits_on_Braket_local_backend.ipynb b/docs/how_tos/5_how_to_run_circuits_on_Braket_local_backend.ipynb index 921d2884..bc722afe 100644 --- a/docs/how_tos/5_how_to_run_circuits_on_Braket_local_backend.ipynb +++ b/docs/how_tos/5_how_to_run_circuits_on_Braket_local_backend.ipynb @@ -14,16 +14,16 @@ }, { "cell_type": "code", - "execution_count": 24, + "execution_count": 1, "metadata": {}, "outputs": [ { "data": { "text/plain": [ - "" + "" ] }, - "execution_count": 24, + "execution_count": 1, "metadata": {}, "output_type": "execute_result" } @@ -52,17 +52,17 @@ }, { "cell_type": "code", - "execution_count": 6, + "execution_count": 2, "metadata": {}, "outputs": [ { "data": { - "image/png": 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", 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", 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" ] }, - "execution_count": 6, + "execution_count": 2, "metadata": {}, "output_type": "execute_result" } @@ -82,17 +82,17 @@ }, { "cell_type": "code", - "execution_count": 17, + "execution_count": 3, "metadata": {}, "outputs": [ { "data": { - "image/png": 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", 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", 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" ] }, - "execution_count": 17, + "execution_count": 3, "metadata": {}, "output_type": "execute_result" } @@ -119,7 +119,7 @@ "name": "python", "nbconvert_exporter": "python", "pygments_lexer": "ipython3", - "version": "3.11.3" + "version": "3.8.10" }, "orig_nbformat": 4 }, diff --git a/docs/tutorials/0_tutorial_qiskit-braket-provider_overview.ipynb b/docs/tutorials/0_tutorial_qiskit-braket-provider_overview.ipynb index 62159438..842372b2 100644 --- a/docs/tutorials/0_tutorial_qiskit-braket-provider_overview.ipynb +++ b/docs/tutorials/0_tutorial_qiskit-braket-provider_overview.ipynb @@ -1,6 +1,7 @@ { "cells": [ { + "attachments": {}, "cell_type": "markdown", "id": "dfb19657", "metadata": { @@ -13,6 +14,7 @@ ] }, { + "attachments": {}, "cell_type": "markdown", "id": "a95fc7c5", "metadata": { @@ -25,6 +27,7 @@ ] }, { + "attachments": {}, "cell_type": "markdown", "id": "447c275b", "metadata": { @@ -47,6 +50,7 @@ ] }, { + "attachments": {}, "cell_type": "markdown", "id": "04160f91", "metadata": {}, @@ -82,6 +86,7 @@ ] }, { + "attachments": {}, "cell_type": "markdown", "id": "6fea9c62", "metadata": { @@ -96,6 +101,7 @@ ] }, { + "attachments": {}, "cell_type": "markdown", "id": "a59c288b", "metadata": {}, @@ -143,6 +149,7 @@ ] }, { + "attachments": {}, "cell_type": "markdown", "id": "edbae0ee", "metadata": {}, @@ -179,6 +186,7 @@ ] }, { + "attachments": {}, "cell_type": "markdown", "id": "390c3a64", "metadata": {}, @@ -209,6 +217,7 @@ ] }, { + "attachments": {}, "cell_type": "markdown", "id": "e13d6409", "metadata": {}, @@ -241,6 +250,7 @@ ] }, { + "attachments": {}, "cell_type": "markdown", "id": "cf366038", "metadata": {}, @@ -273,6 +283,7 @@ ] }, { + "attachments": {}, "cell_type": "markdown", "id": "e91eeeee", "metadata": { @@ -286,6 +297,7 @@ ] }, { + "attachments": {}, "cell_type": "markdown", "id": "137ae345", "metadata": {}, @@ -329,6 +341,7 @@ ] }, { + "attachments": {}, "cell_type": "markdown", "id": "512cfd00", "metadata": {}, @@ -345,7 +358,7 @@ { "data": { "text/plain": [ - "" + "" ] }, "execution_count": 9, @@ -359,6 +372,7 @@ ] }, { + "attachments": {}, "cell_type": "markdown", "id": "851eab0e", "metadata": {}, @@ -374,9 +388,9 @@ "outputs": [ { "data": { - "image/png": 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", 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", 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" ] }, "execution_count": 10, @@ -389,6 +403,7 @@ ] }, { + "attachments": {}, "cell_type": "markdown", "id": "43128a91", "metadata": {}, @@ -405,7 +420,7 @@ { "data": { "text/plain": [ - "['00', '11', '11', '11', '00', '00', '11', '11', '11', '00']" + "['11', '11', '00', '11', '11', '00', '00', '11', '11', '00']" ] }, "execution_count": 11, @@ -418,6 +433,7 @@ ] }, { + "attachments": {}, "cell_type": "markdown", "id": "d48764e8", "metadata": {}, @@ -429,44 +445,44 @@ }, { "cell_type": "code", - "execution_count": 10, + "execution_count": 12, "id": "2d278880", "metadata": {}, "outputs": [ { "data": { "text/html": [ - "
        ┌───┐        ┌───┐                                          ┌──────────────────────────┐┌──────────────┐                                                                                                   ┌─────────────┐    ┌───┐                                                                                           ┌───────────────────┐┌────────────┐┌────────────┐                                                                     \n",
-       "q_0: ───┤ T ├────────┤ S ├───────────────────X───■───────────■──────┤ U3(4.2086,2.7467,5.2319) ├┤ Rx(0.046259) ├──────────────────────────────────■────────────────────────────────────────X───────────■───────────┤ Ry(0.95701) ├────┤ Y ├───────■─────────■─────────────────────────────────────────■───────────────────────■───────┤ U2(3.0304,4.9181) ├┤ Rz(1.6775) ├┤ U1(4.2238) ├────────────────────────────────────────────────────────■────────────\n",
-       "     ┌──┴───┴───┐    └───┘                   │ ┌─┴─┐         │      └──────────────────────────┘└──────────────┘┌─────┐┌────────────────────────┐ │           ┌──────────────────────────┐ │           │           └┬────────────┤    └───┘       │         │             ┌───┐                       │                       │       └───────────────────┘└─────┬──────┘└────────────┘┌─────┐                             ┌────────────┐      │            \n",
-       "q_1: ┤ U1(6.13) ├────────────────────X───────X─┤ X ├─────────┼───────────────────X─────────────────────X────────┤ Tdg ├┤ U3(2.96,3.5515,4.8066) ├─┼───────────┤ U3(0.36633,1.768,1.8447) ├─┼───────────■────────────┤ Rz(2.8033) ├─■──────────────┼────■────┼─────────────┤ T ├───────────────────■───┼───────────────────────■─────────────────■────────────────┼─────────────■───────┤ Sdg ├─────────────────────────────┤ Rz(5.2137) ├──────┼────────────\n",
-       "     └──────────┘┌────────────┐      │       │ └─┬─┘         │                   │                     │        ├─────┤└───────────┬────────────┘ │U1(3.4782) └──────────┬───┬───────────┘ │         ┌─┴─┐          └─────┬──────┘ │ZZ(0.74145)   │    │    │  ┌──────────┴───┴───────────┐┌───┐  │   │                       │                 │                │           ┌─┴─┐     └┬───┬┘                             └─────┬──────┘      │            \n",
-       "q_2: ─────X──────┤ Ry(4.0455) ├──────┼───■───┼───┼───■───────┼───────────────────X─────────────────────X────────┤ Sdg ├────────────┼──────────────■──────────────────────┤ Z ├─────────────┼─────────┤ X ├────────────────■────────■──────────────┼────■────┼──┤ U3(1.9224,3.6393,1.1107) ├┤ Y ├──┼───┼─────────────■─────────┼─────────────────■────────────────┼───────────┤ X ├──────┤ X ├────────────────────────────────────┼─────────────┼─────────■──\n",
-       "          │      └───┬───┬────┘      │   │   │   │   │       │                   │                   ┌───┐      ├─────┤            │                 ┌───┐               └───┘             │         ├───┤              ┌───┐                     │  ┌─┴─┐  │  └──────────────────────────┘└─┬─┘  │   │           ┌─┴─┐       │                                  │           └─┬─┘      └───┘ ┌───────────────────────────┐      │             │       ┌─┴─┐\n",
-       "q_3: ─────┼──────────┤ T ├───────■───┼───┼───■───┼───X───────┼───────────────────■───────────────────┤ X ├──────┤ Tdg ├────────────■─────────────────┤ Z ├─────────────────────────────────┼─────────┤ H ├──────────────┤ X ├───────────■─────────┼──┤ X ├──■────────────────────────────────■────┼───┼───────────┤ Y ├───────┼─────────────────■────────────────■─────────────┼──────────────┤ U3(4.8296,0.67696,5.7555) ├──────┼─────────────┼───────┤ Y ├\n",
-       "          │          └───┘       │   │ ┌─┴─┐     │   │     ┌─┴─┐               ┌───┐                 └───┘      ├─────┤                              └───┘                                 │         └─┬─┘              └─┬─┘           │       ┌─┴─┐└───┘┌─┴─┐                                 ┌─┴─┐ │           └───┘     ┌─┴─┐         ┌─────┴──────┐       ┌───┐           │        ┌───┐ └─────────────┬─────────────┘      │       ┌─────┴──────┐└───┘\n",
-       "q_4: ─────■──────────────────────┼───X─┤ X ├─────■───┼─────┤ Y ├───────────────┤ T ├──────────────■─────────────┤ Tdg ├────────────────────────────────────────────────────────────────────■───────────■──────────────────■─────────────■───────┤ X ├─────┤ X ├─────────────────────────────────┤ X ├─┼─────────────────────┤ X ├─────────┤ Rz(3.7128) ├───────┤ S ├───────────┼────────┤ S ├───────────────┼────────────────────┼───────┤ Rz(1.9926) ├─────\n",
-       "          │                    ┌─┴─┐   └─┬─┘         │ ┌───┴───┴───┐           ├───┤              │ZZ(4.2882)   └┬───┬┘                                                                    │ ┌────────────────────┐       │           ┌─┴─┐     └─┬─┘┌───┐└───┘                                 └───┘ │U1(2.6126) ┌───┐┌────┴───┴────┐    └────────────┘       └───┘           │        └───┘               │                    │       └────────────┘     \n",
-       "q_5: ─────X────────────────────┤ H ├─────■───────────X─┤ Ry(6.079) ├───────────┤ Z ├──────────────■──────────────┤ S ├─────────────────────────────────────────────────────────────────────X─┤ U2(0.1427,0.56579) ├───────■───────────┤ X ├───────■──┤ Z ├────────────────────────────────────────────■───────────┤ X ├┤ Rz(0.51981) ├─────────────────────────────────────────■────────────────────────────■────────────────────■──────────────────────────\n",
-       "                               └───┘                   └───────────┘           └───┘                             └───┘                                                                       └────────────────────┘                   └───┘          └───┘                                                        └───┘└─────────────┘
" + "
     ┌────────────────────────┐                                       ┌─────────────────────────┐┌────┐   ┌───────────────────┐                                                     ┌──────┐                                                                                               ┌────────────────────┐┌───────────┐┌─────────────────────────┐                                   ┌──────────────┐       ┌───┐        ┌────────────┐                                   ┌────────────────────┐  ┌───┐                                                           ┌──────────────────┐                   \n",
+       "q_0: ┤0                       ├────■──────────────────────────────────┤1                        ├┤ Sx ├───┤ U2(1.8116,4.2882) ├─────────────────────────────────────────────────────┤1     ├─────────────────────────────────────────X───────────────────────────────────────────────────X─┤ U2(0.56579,4.5387) ├┤ Rx(2.394) ├┤ U3(4.893,4.5044,2.8234) ├───────────────────────────────────┤0             ├───────┤ Y ├────────┤ Ry(3.7128) ├───────────────────────────■───────┤ U2(0.13579,5.1917) ├──┤ H ├──────────────────────────■────────────────────────■───────┤ R(4.1573,2.3478) ├───────────────────\n",
+       "     │                        │    │ ┌───┐┌────────────┐┌────────────┐│                         │└─┬──┘   └───────────────────┘                                     ┌──────────────┐│      │                                         │                                                   │ └────────────────────┘└───────────┘└──────┬────────────┬─────┘        ┌───┐            ┌─────┐   │              │       └─┬─┘        └────────────┘             ┌──────┐      │       └────────────────────┘  ├───┴┐ ┌──────────────┐┌────┐  │        ┌───┐           │       └──────────────────┘                   \n",
+       "q_1: ┤  {XX+YY}(4.7824,4.939) ├─■──┼─┤ X ├┤ Ry(6.0991) ├┤ Rx(1.1905) ├┤                         ├──┼────────────────────────────────────────────────────────────────┤0             ├┤      ├─────────────────■───────────■───────────┼──────────────────────────────────────────────■────┼───────────■───────────────────────────────┤ Rx(1.8945) ├──────────────┤ Y ├────────────┤ Sdg ├───┤              ├─────────■─────────────────────────────────────┤1     ├──────┼─────────────■─────────────────┤ Sx ├─┤0             ├┤ Sx ├──┼────────┤ T ├───────────┼────────────────■─────────────────────────────\n",
+       "     │                        │ │  │ └─┬─┘└──┬─────┬───┘└──┬─────┬───┘│                         │  │   ┌─────────────────────────┐                                  │              ││      │┌──────────────┐ │           │           │ ┌────────────────────────────────┐ ┌───┐     │    │     ┌─────┴──────┐                        └─────┬──────┘      ┌───────┴───┴────────┐   └─────┘   │  Rzx(5.3823) │                                               │      │      │             │P(5.8925)        └─┬──┘ │  Rxx(4.5678) │└─┬──┘  │    ┌───┴───┴────┐      │                │          ┌─────────────────┐\n",
+       "q_2: ┤1                       ├─┼──┼───┼─────┤ Sdg ├───────┤ Tdg ├────┤  {XX-YY}(5.6116,4.8907) ├──┼───┤1                        ├────────────────■─────────────────┤              ├┤  Ecr ├┤0             ├─┼───────────┼───────────┼─┤ U(3.5136,1.9098,0.19363,2.744) ├─┤ X ├─────┼────┼─────┤ Ry(1.0491) ├──────────■───────────────────┼─────────────┤ U2(1.7105,0.60564) ├─■───────────┤              ├────■──────────────────────────────■───────────┤      ├──────┼─────────────■───────────────────■────┤1             ├──┼─────┼────┤ U1(1.9926) ├──────X────────────────┼──────────┤ R(1.985,4.8507) ├\n",
+       "     └─────────┬────┬─────────┘ │  │   │     └──┬──┘       └─────┘    │                         │  │   │  {XX-YY}(2.3277,2.9503) │┌───────────────┴────────────────┐│  Rxx(2.4346) ││      ││  Rxx(2.8835) │ │           │           │ └───────────────┬────────────────┘┌┴───┴─┐   │    │     └──┬──────┬──┘          │                   │             └───────┬───┬────────┘ │           │              │    │U1(0.26147)    ┌────────────┐ │           │  Ecr │      │              ┌──────┐       ┌───────┐├──────────────┤  │     │   ┌┴────────────┤      │              ┌─┴─┐        └─────────────────┘\n",
+       "q_3: ──────────┤ √X ├───────────┼──┼───■────────┼─────────────■───────┤                         ├──┼───┤0                        ├┤ U(4.3999,1.9627,5.2292,5.0565) ├┤              ├┤      ├┤1             ├─┼───────────┼───────────X─────────────────┼─────────────────┤ √Xdg ├───┼────┼────────┤1     ├─────────────■───────────────────┼─────────────────────┤ H ├──────────┼───────────┤1             ├────■───────────────┤ Ry(3.6509) ├─┼───────────┤      ├──────┼──────────────┤0     ├───────┤1      ├┤1             ├──■─────┼───┤ Ry(0.28218) ├──────┼──────────────┤ X ├───────────────────────────\n",
+       "               └────┘           │  │            │             │       │                         │  │   └──────┬────────────┬─────┘└────────────────────────────────┘│              ││      │└──────────────┘ │           │P(3.4782)                    │                 └──────┘┌──┴──┐ │        │  Ecr │             │                   │                     ├───┤          │           └┬────────────┬┘┌──────────────────┐└────────────┘ │           │      │      │              │  Ecr │       │       ││  Rxx(4.8296) │      ┌─┴──┐└──────┬──────┘      │              └─┬─┘                           \n",
+       "q_4: ───────────────────────────■──┼────────────■─────────────┼───────┤0                        ├──┼──────────┤ Rx(2.0472) ├────────────────────────────────────────┤1             ├┤0     ├─────────────────┼───────────■─────────────────────────────┼─────────────────────────┤ Sdg ├─┼────────┤0     ├─────────────■───────────────────┼─────────────────────┤ S ├──────────┼────────────┤ U1(4.7659) ├─┤ R(3.1038,2.0726) ├───────────────┼───────────┤0     ├──────┼──────────────┤1     ├───────┤0 Rccx ├┤0             ├──────┤ Sx ├───────┼─────────────X────────────────■─────────────────────────────\n",
+       "        ┌─────────────────┐        │                        ┌─┴─┐     └─────────────────────────┘  │          └──┬──────┬──┘                                        └──────────────┘└──────┘                 │P(3.5735)                                │                         └─────┘ │     ┌──┴──────┴──┐                              │              ┌──────┴───┴───────┐  │ZZ(1.1107)  ├────────────┤ └──────────────────┘               │U1(2.1794) └──────┘┌─────┴──────┐       └──────┘       │       │└────┬───┬─────┘┌───┐ └────┘       │       ┌────────────┐                                       \n",
+       "q_5: ───┤ R(0.59173,6.13) ├────────■────────────────────────┤ Y ├──────────────────────────────────■─────────────┤ √Xdg ├────────────────────────────────────────────────────────────────────────────────────■─────────────────────────────────────────■─────────────────────────────────X─────┤ Ry(0.1427) ├──────────────────────────────■──────────────┤ R(1.6705,6.0895) ├──■────────────┤ Rx(2.6126) ├────────────────────────────────────■───────────────────┤ Rx(3.0832) ├──────────────────────┤2      ├─────┤ H ├──────┤ Y ├──────────────■───────┤ Rx(3.2601) ├───────────────────────────────────────\n",
+       "        └─────────────────┘                                 └───┘                                                └──────┘                                                                                                                                                                      └────────────┘                                             └──────────────────┘               └────────────┘                                                        └────────────┘                      └───────┘     └───┘      └───┘                      └────────────┘
" ], "text/plain": [ - " ┌───┐ ┌───┐ ┌──────────────────────────┐┌──────────────┐ ┌─────────────┐ ┌───┐ ┌───────────────────┐┌────────────┐┌────────────┐ \n", - "q_0: ───┤ T ├────────┤ S ├───────────────────X───■───────────■──────┤ U3(4.2086,2.7467,5.2319) ├┤ Rx(0.046259) ├──────────────────────────────────■────────────────────────────────────────X───────────■───────────┤ Ry(0.95701) ├────┤ Y ├───────■─────────■─────────────────────────────────────────■───────────────────────■───────┤ U2(3.0304,4.9181) ├┤ Rz(1.6775) ├┤ U1(4.2238) ├────────────────────────────────────────────────────────■────────────\n", - " ┌──┴───┴───┐ └───┘ │ ┌─┴─┐ │ └──────────────────────────┘└──────────────┘┌─────┐┌────────────────────────┐ │ ┌──────────────────────────┐ │ │ └┬────────────┤ └───┘ │ │ ┌───┐ │ │ └───────────────────┘└─────┬──────┘└────────────┘┌─────┐ ┌────────────┐ │ \n", - "q_1: ┤ U1(6.13) ├────────────────────X───────X─┤ X ├─────────┼───────────────────X─────────────────────X────────┤ Tdg ├┤ U3(2.96,3.5515,4.8066) ├─┼───────────┤ U3(0.36633,1.768,1.8447) ├─┼───────────■────────────┤ Rz(2.8033) ├─■──────────────┼────■────┼─────────────┤ T ├───────────────────■───┼───────────────────────■─────────────────■────────────────┼─────────────■───────┤ Sdg ├─────────────────────────────┤ Rz(5.2137) ├──────┼────────────\n", - " └──────────┘┌────────────┐ │ │ └─┬─┘ │ │ │ ├─────┤└───────────┬────────────┘ │U1(3.4782) └──────────┬───┬───────────┘ │ ┌─┴─┐ └─────┬──────┘ │ZZ(0.74145) │ │ │ ┌──────────┴───┴───────────┐┌───┐ │ │ │ │ │ ┌─┴─┐ └┬───┬┘ └─────┬──────┘ │ \n", - "q_2: ─────X──────┤ Ry(4.0455) ├──────┼───■───┼───┼───■───────┼───────────────────X─────────────────────X────────┤ Sdg ├────────────┼──────────────■──────────────────────┤ Z ├─────────────┼─────────┤ X ├────────────────■────────■──────────────┼────■────┼──┤ U3(1.9224,3.6393,1.1107) ├┤ Y ├──┼───┼─────────────■─────────┼─────────────────■────────────────┼───────────┤ X ├──────┤ X ├────────────────────────────────────┼─────────────┼─────────■──\n", - " │ └───┬───┬────┘ │ │ │ │ │ │ │ ┌───┐ ├─────┤ │ ┌───┐ └───┘ │ ├───┤ ┌───┐ │ ┌─┴─┐ │ └──────────────────────────┘└─┬─┘ │ │ ┌─┴─┐ │ │ └─┬─┘ └───┘ ┌───────────────────────────┐ │ │ ┌─┴─┐\n", - "q_3: ─────┼──────────┤ T ├───────■───┼───┼───■───┼───X───────┼───────────────────■───────────────────┤ X ├──────┤ Tdg ├────────────■─────────────────┤ Z ├─────────────────────────────────┼─────────┤ H ├──────────────┤ X ├───────────■─────────┼──┤ X ├──■────────────────────────────────■────┼───┼───────────┤ Y ├───────┼─────────────────■────────────────■─────────────┼──────────────┤ U3(4.8296,0.67696,5.7555) ├──────┼─────────────┼───────┤ Y ├\n", - " │ └───┘ │ │ ┌─┴─┐ │ │ ┌─┴─┐ ┌───┐ └───┘ ├─────┤ └───┘ │ └─┬─┘ └─┬─┘ │ ┌─┴─┐└───┘┌─┴─┐ ┌─┴─┐ │ └───┘ ┌─┴─┐ ┌─────┴──────┐ ┌───┐ │ ┌───┐ └─────────────┬─────────────┘ │ ┌─────┴──────┐└───┘\n", - "q_4: ─────■──────────────────────┼───X─┤ X ├─────■───┼─────┤ Y ├───────────────┤ T ├──────────────■─────────────┤ Tdg ├────────────────────────────────────────────────────────────────────■───────────■──────────────────■─────────────■───────┤ X ├─────┤ X ├─────────────────────────────────┤ X ├─┼─────────────────────┤ X ├─────────┤ Rz(3.7128) ├───────┤ S ├───────────┼────────┤ S ├───────────────┼────────────────────┼───────┤ Rz(1.9926) ├─────\n", - " │ ┌─┴─┐ └─┬─┘ │ ┌───┴───┴───┐ ├───┤ │ZZ(4.2882) └┬───┬┘ │ ┌────────────────────┐ │ ┌─┴─┐ └─┬─┘┌───┐└───┘ └───┘ │U1(2.6126) ┌───┐┌────┴───┴────┐ └────────────┘ └───┘ │ └───┘ │ │ └────────────┘ \n", - "q_5: ─────X────────────────────┤ H ├─────■───────────X─┤ Ry(6.079) ├───────────┤ Z ├──────────────■──────────────┤ S ├─────────────────────────────────────────────────────────────────────X─┤ U2(0.1427,0.56579) ├───────■───────────┤ X ├───────■──┤ Z ├────────────────────────────────────────────■───────────┤ X ├┤ Rz(0.51981) ├─────────────────────────────────────────■────────────────────────────■────────────────────■──────────────────────────\n", - " └───┘ └───────────┘ └───┘ └───┘ └────────────────────┘ └───┘ └───┘ └───┘└─────────────┘ " + " ┌────────────────────────┐ ┌─────────────────────────┐┌────┐ ┌───────────────────┐ ┌──────┐ ┌────────────────────┐┌───────────┐┌─────────────────────────┐ ┌──────────────┐ ┌───┐ ┌────────────┐ ┌────────────────────┐ ┌───┐ ┌──────────────────┐ \n", + "q_0: ┤0 ├────■──────────────────────────────────┤1 ├┤ Sx ├───┤ U2(1.8116,4.2882) ├─────────────────────────────────────────────────────┤1 ├─────────────────────────────────────────X───────────────────────────────────────────────────X─┤ U2(0.56579,4.5387) ├┤ Rx(2.394) ├┤ U3(4.893,4.5044,2.8234) ├───────────────────────────────────┤0 ├───────┤ Y ├────────┤ Ry(3.7128) ├───────────────────────────■───────┤ U2(0.13579,5.1917) ├──┤ H ├──────────────────────────■────────────────────────■───────┤ R(4.1573,2.3478) ├───────────────────\n", + " │ │ │ ┌───┐┌────────────┐┌────────────┐│ │└─┬──┘ └───────────────────┘ ┌──────────────┐│ │ │ │ └────────────────────┘└───────────┘└──────┬────────────┬─────┘ ┌───┐ ┌─────┐ │ │ └─┬─┘ └────────────┘ ┌──────┐ │ └────────────────────┘ ├───┴┐ ┌──────────────┐┌────┐ │ ┌───┐ │ └──────────────────┘ \n", + "q_1: ┤ {XX+YY}(4.7824,4.939) ├─■──┼─┤ X ├┤ Ry(6.0991) ├┤ Rx(1.1905) ├┤ ├──┼────────────────────────────────────────────────────────────────┤0 ├┤ ├─────────────────■───────────■───────────┼──────────────────────────────────────────────■────┼───────────■───────────────────────────────┤ Rx(1.8945) ├──────────────┤ Y ├────────────┤ Sdg ├───┤ ├─────────■─────────────────────────────────────┤1 ├──────┼─────────────■─────────────────┤ Sx ├─┤0 ├┤ Sx ├──┼────────┤ T ├───────────┼────────────────■─────────────────────────────\n", + " │ │ │ │ └─┬─┘└──┬─────┬───┘└──┬─────┬───┘│ │ │ ┌─────────────────────────┐ │ ││ │┌──────────────┐ │ │ │ ┌────────────────────────────────┐ ┌───┐ │ │ ┌─────┴──────┐ └─────┬──────┘ ┌───────┴───┴────────┐ └─────┘ │ Rzx(5.3823) │ │ │ │ │P(5.8925) └─┬──┘ │ Rxx(4.5678) │└─┬──┘ │ ┌───┴───┴────┐ │ │ ┌─────────────────┐\n", + "q_2: ┤1 ├─┼──┼───┼─────┤ Sdg ├───────┤ Tdg ├────┤ {XX-YY}(5.6116,4.8907) ├──┼───┤1 ├────────────────■─────────────────┤ ├┤ Ecr ├┤0 ├─┼───────────┼───────────┼─┤ U(3.5136,1.9098,0.19363,2.744) ├─┤ X ├─────┼────┼─────┤ Ry(1.0491) ├──────────■───────────────────┼─────────────┤ U2(1.7105,0.60564) ├─■───────────┤ ├────■──────────────────────────────■───────────┤ ├──────┼─────────────■───────────────────■────┤1 ├──┼─────┼────┤ U1(1.9926) ├──────X────────────────┼──────────┤ R(1.985,4.8507) ├\n", + " └─────────┬────┬─────────┘ │ │ │ └──┬──┘ └─────┘ │ │ │ │ {XX-YY}(2.3277,2.9503) │┌───────────────┴────────────────┐│ Rxx(2.4346) ││ ││ Rxx(2.8835) │ │ │ │ └───────────────┬────────────────┘┌┴───┴─┐ │ │ └──┬──────┬──┘ │ │ └───────┬───┬────────┘ │ │ │ │U1(0.26147) ┌────────────┐ │ │ Ecr │ │ ┌──────┐ ┌───────┐├──────────────┤ │ │ ┌┴────────────┤ │ ┌─┴─┐ └─────────────────┘\n", + "q_3: ──────────┤ √X ├───────────┼──┼───■────────┼─────────────■───────┤ ├──┼───┤0 ├┤ U(4.3999,1.9627,5.2292,5.0565) ├┤ ├┤ ├┤1 ├─┼───────────┼───────────X─────────────────┼─────────────────┤ √Xdg ├───┼────┼────────┤1 ├─────────────■───────────────────┼─────────────────────┤ H ├──────────┼───────────┤1 ├────■───────────────┤ Ry(3.6509) ├─┼───────────┤ ├──────┼──────────────┤0 ├───────┤1 ├┤1 ├──■─────┼───┤ Ry(0.28218) ├──────┼──────────────┤ X ├───────────────────────────\n", + " └────┘ │ │ │ │ │ │ │ └──────┬────────────┬─────┘└────────────────────────────────┘│ ││ │└──────────────┘ │ │P(3.4782) │ └──────┘┌──┴──┐ │ │ Ecr │ │ │ ├───┤ │ └┬────────────┬┘┌──────────────────┐└────────────┘ │ │ │ │ │ Ecr │ │ ││ Rxx(4.8296) │ ┌─┴──┐└──────┬──────┘ │ └─┬─┘ \n", + "q_4: ───────────────────────────■──┼────────────■─────────────┼───────┤0 ├──┼──────────┤ Rx(2.0472) ├────────────────────────────────────────┤1 ├┤0 ├─────────────────┼───────────■─────────────────────────────┼─────────────────────────┤ Sdg ├─┼────────┤0 ├─────────────■───────────────────┼─────────────────────┤ S ├──────────┼────────────┤ U1(4.7659) ├─┤ R(3.1038,2.0726) ├───────────────┼───────────┤0 ├──────┼──────────────┤1 ├───────┤0 Rccx ├┤0 ├──────┤ Sx ├───────┼─────────────X────────────────■─────────────────────────────\n", + " ┌─────────────────┐ │ ┌─┴─┐ └─────────────────────────┘ │ └──┬──────┬──┘ └──────────────┘└──────┘ │P(3.5735) │ └─────┘ │ ┌──┴──────┴──┐ │ ┌──────┴───┴───────┐ │ZZ(1.1107) ├────────────┤ └──────────────────┘ │U1(2.1794) └──────┘┌─────┴──────┐ └──────┘ │ │└────┬───┬─────┘┌───┐ └────┘ │ ┌────────────┐ \n", + "q_5: ───┤ R(0.59173,6.13) ├────────■────────────────────────┤ Y ├──────────────────────────────────■─────────────┤ √Xdg ├────────────────────────────────────────────────────────────────────────────────────■─────────────────────────────────────────■─────────────────────────────────X─────┤ Ry(0.1427) ├──────────────────────────────■──────────────┤ R(1.6705,6.0895) ├──■────────────┤ Rx(2.6126) ├────────────────────────────────────■───────────────────┤ Rx(3.0832) ├──────────────────────┤2 ├─────┤ H ├──────┤ Y ├──────────────■───────┤ Rx(3.2601) ├───────────────────────────────────────\n", + " └─────────────────┘ └───┘ └──────┘ └────────────┘ └──────────────────┘ └────────────┘ └────────────┘ └───────┘ └───┘ └───┘ └────────────┘ " ] }, - "execution_count": 10, + "execution_count": 12, "metadata": {}, "output_type": "execute_result" } @@ -477,6 +493,7 @@ ] }, { + "attachments": {}, "cell_type": "markdown", "id": "d9d69137", "metadata": {}, @@ -492,7 +509,7 @@ }, { "cell_type": "code", - "execution_count": 11, + "execution_count": 13, "id": "51e60f77", "metadata": { "slideshow": { @@ -503,39 +520,39 @@ { "data": { "text/html": [ - "
global phase: 3.2614\n",
-       "           ┌──────────┐                                                                                                       ┌───┐   ┌───┐     ┌─────┐  ┌───┐ ┌───┐ ┌───┐┌─────┐┌───┐ ┌───┐  ┌───┐                                                        ┌───┐            ┌───┐ ┌─────┐┌───┐                 ┌────────────┐┌────────────┐┌────────────┐                                                                                                                                                                                     ┌───┐                                                                   ┌───┐      ┌───┐┌─────┐┌───┐     ┌───┐                                                                                 ┌───┐          ┌─────────────┐                                                                                                                                                                                            ┌───┐                                                                     ┌───┐      ┌───┐┌─────┐┌───┐┌──────────────────────┐                                                                                                        ┌───┐                         ┌─────────────┐       ┌─────────┐       ┌─────────────┐               ┌───┐┌────────────────────────┐┌───┐┌──────────────────────┐                                                                                                                                                                                                                                \n",
-       "q_0: ──────┤ Rz(3π/4) ├───────────────────────────────────────────────────────────────────────────────────────────────■───────┤ H ├───┤ X ├─────┤ Tdg ├──┤ X ├─┤ T ├─┤ X ├┤ Tdg ├┤ X ├─┤ T ├──┤ H ├────────■─────────■────────────────────────────────■────┤ T ├────────────┤ X ├─┤ Tdg ├┤ X ├──────────────■──┤ Rz(2.1395) ├┤ Ry(2.0919) ├┤ Rz(1.3684) ├─────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────■─────────────────────────────────■─────────────────────┤ X ├───────────────────────────────■───────────────────────────────■───┤ T ├──────┤ X ├┤ Tdg ├┤ X ├─────┤ X ├────────────■──────────────────────────────────────────────────────────■─────■───┤ T ├───■──────┤ Ry(-2.1846) ├─────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────■──────────────────────────■───────────────■───┤ T ├────────■──────────────────■─────────────────────────────────────■───┤ T ├──────┤ X ├┤ Tdg ├┤ X ├┤ Rz(1.30629747996744) ├───────────────────■──────────────────────────────────■─────────■──────────────────────────────■────■───┤ T ├────────────■────────────┤ Rz(-1.3651) ├───────┤ Ry(π/2) ├───────┤ Rz(-2.4141) ├───────────────┤ X ├┤ Rz(-0.838728781856755) ├┤ X ├┤ Rz(4.22380907548478) ├──────────────────────────■─────────────────────────────────────■───────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────\n",
-       "     ┌─────┴──────────┴─────┐                                                                                       ┌─┴─┐     └───┘   └─┬─┘     └─────┘  └─┬─┘ └───┘ └─┬─┘└┬───┬┘└─┬─┘ ├───┤ ┌┴───┴┐┌───┐┌─┴─┐┌───┐┌─┴─┐┌─────┐          ┌───┐┌───┐ ┌─┴─┐ ┌┴───┴┐┌───┐┌───┐ └─┬─┘ └┬───┬┘└─┬─┘              │  └────────────┘└────────────┘└───┬───┬────┘                                                 ┌───┐           ┌───┐┌─────┐┌───┐     ┌───┐               ┌──────────────┐  │  ┌───┐     ┌────────────┐       │  ┌───────────┐ ┌───┐└─┬─┘┌──────────────┐┌───────────┐  │  ┌─────────────┐              │   └───┘      └─┬─┘└─────┘└─┬─┘     └─┬─┘            │                                                 ┌───┐    │   ┌─┴─┐┌┴───┴┐┌─┴─┐┌───┴─────────────┴────┐┌───┐┌───────────────────────┐ ┌───┐                                                                                                    │                          │               │   ├───┤        │      ┌───┐       │                                     │   └───┘      └─┬─┘└─────┘└─┬─┘└──────────────────────┘                   │                                  │         │                      ┌───┐   │  ┌─┴─┐┌┴───┴┐         ┌─┴─┐          └────┬───┬────┘       └──┬───┬──┘       └────┬───┬────┘               └─┬─┘└────────────────────────┘└─┬─┘└──────────────────────┘                          │                             ┌───┐   │                  ┌───┐  ┌─────┐  ┌───┐     ┌────────────┐                                                        ┌───┐┌───────────────────────┐     ┌───┐     \n",
-       "q_1: ┤ Rz(6.13001602516006) ├────────────────────────────────────────────────────────────────────────────X──────────┤ X ├───────────────■──────────────────┼───────────■───┤ T ├───┼───┤ X ├─┤ Tdg ├┤ X ├┤ X ├┤ H ├┤ X ├┤ Tdg ├──────────┤ X ├┤ T ├─┤ X ├─┤ Tdg ├┤ X ├┤ T ├───┼────┤ H ├───┼────────────────┼──────────────────────────────────┤ X ├────────────────────■─────────────────────────────■───┤ T ├───────────┤ X ├┤ Tdg ├┤ X ├─────┤ X ├──────────X────┤ Rz(-0.15782) ├──┼──┤ X ├─────┤ Rz(2.1041) ├───────┼──┤ Ry(-1.48) ├─┤ X ├──┼──┤ Rz(-0.28426) ├┤ Ry(1.712) ├──┼──┤ Rz(0.87374) ├──■───────────┼────────────────┼───────────┼─────────┼──────────────┼───────────────────────────────────■─────────────┤ T ├────┼───┤ X ├┤ Tdg ├┤ X ├┤ Rz(1.40164127769636) ├┤ X ├┤ Rz(-1.40164127769636) ├─┤ X ├──■────────────────────────────────────────────────────────────────────────────────────────────■────┼─────────────────────■────┼───────■───────┼───┤ T ├───■────┼──────┤ T ├───────┼─────────────────────────────────────┼────────────────┼───────────┼─────────────■──────────────────────────■────┼──────────────────────────────────┼─────────┼──────────────────■───┤ T ├───┼──┤ X ├┤ Tdg ├─────────┤ X ├───────────────┤ H ├───────────────┤ X ├───────────────┤ H ├────────────■─────────┼──────────────────────────────┼────────────────────────────────────────────────────┼──────────────■──────────────┤ T ├───┼──────────────────┤ X ├──┤ Tdg ├──┤ X ├─────┤ Rz(1.0361) ├────────────────────────────────────────────────────────┤ X ├┤ Rz(-2.60686136104895) ├─────┤ X ├─────\n",
-       "     └──────────────────────┘     ┌───┐┌───┐┌─────┐┌───┐┌───┐┌───┐┌─────┐┌───┐┌───┐ ┌───┐                │      ┌───┴───┴────┐                             │               └───┘   │   └─┬─┘ └─────┘└─┬─┘└───┘└───┘└───┘└┬───┬┘          └─┬─┘└───┘ └───┘ └─────┘└─┬─┘└───┘   │    └───┘   │                │      ┌───┐                       └─┬─┘         ┌───┐    ┌─┴─┐   ┌─────┐    ┌───┐ ┌───┐┌─┴─┐┌┴───┴┐┌───┐┌───┐└─┬─┘└┬───┬┘└─┬─┘     └─┬─┘          │    └───┬─────┬────┘┌─┴─┐└─┬─┘┌────┴────────────┴────┐┌─┴─┐├───────────┴┐└─┬─┘  │  └─┬─────────┬──┘└───────────┘  │  └─────────────┘┌─┴─┐┌─────┐  │                │           │         │            ┌─┴─┐             ┌───┐             ┌─┴─┐          ┌┴───┴┐ ┌─┴─┐ ├───┤└┬───┬┘└───┘└──────────────────────┘└─┬─┘└───────────────────────┘ └─┬─┘  │ZZ(0.74145)                                                                                 │    │             ┌───┐   │    │     ┌─┴─┐     │  ┌┴───┴┐┌─┴─┐  │  ┌───┴───┴────┐  │  ┌────────────┐┌────────────┐       │                │           │             │            ┌───┐ ┌───┐   │    │                                  │         │                  │   └───┘   │  └───┘└─────┘         └───┘               └───┘               └─┬─┘               ├───┤          ┌─┴─┐       │           ┌─────┐            │           ┌───┐                   ┌───┐            │            ┌─┴─┐           ┌┴───┴┐  │  ┌───┐┌─────────┐└─┬─┘┌─┴─────┴─┐└─┬─┘     └────────────┘                                                        └─┬─┘└───────────────────────┘     └─┬─┘     \n",
-       "q_2: ──────────────────────────■──┤ H ├┤ X ├┤ Tdg ├┤ X ├┤ T ├┤ X ├┤ Tdg ├┤ X ├┤ T ├─┤ H ├────────■───────┼──────┤ Ry(4.0455) ├─────────────────────────────┼───────────■───────────┼─────┼────────────┼────■─────────■───┤ T ├───■─────────┼─────────────────■─────┼──────────┼────────────┼────■─────■─────┼──────┤ T ├───────────■─────────────■───────────┤ H ├────┤ X ├───┤ Tdg ├────┤ X ├─┤ T ├┤ X ├┤ Tdg ├┤ X ├┤ T ├──┼───┤ H ├───┼─────────■────────────X────────┤ Sdg ├─────┤ X ├──┼──┤ Rz(-1.7391209782858) ├┤ X ├┤ Rz(1.7391) ├──┼────┼────┤ Ry(π/2) ├──────────────────┼─────────────────┤ X ├┤ Tdg ├──┼────────────────┼───────────┼─────────┼────────────┤ X ├─────────────┤ T ├─────────────┤ X ├──────────┤ Tdg ├─┤ X ├─┤ T ├─┤ H ├────────────────────────────────■──────────────────────────────■────■────────────────────────────────────────────────────────────────────────────────■───────────┼────┼─────────■───┤ T ├───┼────┼─────┤ X ├─────┼──┤ Tdg ├┤ X ├──┼──┤ Rz(1.1107) ├──┼──┤ Ry(1.9224) ├┤ Rz(2.0685) ├───────┼────────────────┼───────────┼─────────────┼────────────┤ X ├─┤ S ├───┼────┼──────────────■───────────────────┼─────────┼──────────────────┼───────────┼─────────────────────────────────────────────────────────────────■─────────────────┤ H ├──────────┤ X ├───────┼───────────┤ Tdg ├────────────┼───────────┤ X ├───────────────────┤ T ├────────────┼────────────┤ X ├───────────┤ Tdg ├──┼──┤ X ├┤ Rz(π/4) ├──┼──┤ Ry(π/2) ├──┼───────────────────────────────────────────────────────────────────────────────┼─────────────────────────────■────┼───────\n",
-       "              ┌───┐            │  └───┘└─┬─┘└─────┘└─┬─┘└───┘└─┬─┘└─────┘└─┬─┘└───┘ └───┘        │       │      └────────────┘                             │           │           │     │    ┌───┐   │    │         │   └───┘   │  ┌───┐  │                 │     │          │    ┌───┐   │    │   ┌─┴─┐   │     ┌┴───┴┐        ┌─┴─┐         ┌───┐         └───┘    └───┘   └─────┘    └─┬─┘ └───┘└───┘└─────┘└─┬─┘└───┘  │   ├───┤   │  ┌──────────────┐┌───────┐    └─────┘     └───┘  │  └──────────────────────┘└───┘└────────────┘  │    │    ├─────────┤    ┌──────────┐  │                 └───┘└─────┘  │                │           │  ┌───┐  │         ┌──┴───┴───┐      ┌──┴───┴───┐         └───┘          └┬───┬┘┌┴───┴┐├───┤ ├───┤ ┌───┐        ┌─────┐         ┌───┐          ┌───┐           ┌───┐                                                                 ┌───┐      ┌───┐┌─┴─┐┌─────┐┌─┴─┐  │  ┌───┐┌─┴─┐┌┴───┴┐┌─┴─┐  │     ├───┤     │  └┬───┬┘└───┘  │  └────────────┘  │  └────────────┘└────────────┘       │                │   ┌───┐   │             │            └─┬─┘┌┴───┴┐  │    │            ┌─┴─┐          ┌───┐  │         │                  │           │                                                                                   └───┘          └───┘       │           └─────┘            │           └─┬─┘          ┌────────┴───┴─────────┐  │            └───┘           └─────┘  │  └─┬─┘└─────────┘  │  └─────────┘  │                         ┌───┐┌───────────┐┌─────────────┐┌───┐┌────────────┐  │       ┌──────────────┐    ┌─┴─┐  │  ┌───┐\n",
-       "q_3: ─────────┤ T ├────────────┼─────────┼───────────┼─────────┼───────────┼─────────────────────┼───────┼──────────────────────■──────────────────────────■───────────┼───────────■─────■────┤ T ├───■────┼─────────┼───────────┼──┤ X ├──┼────■────────────┼─────┼────■─────┼────┤ T ├───┼────┼───┤ X ├───┼─────┤ Tdg ├────────┤ X ├─────────┤ X ├───────────────────────────────────────■──────────────────────■─────────■───┤ T ├───■──┤ Rz(-0.25207) ├┤ Ry(π) ├───────────────────────■───────────────────────────────────────────────■────┼────┤ Rx(π/2) ├────┤ Rz(3π/4) ├──┼───────────────────────────────┼────────────────┼───────────┼──┤ X ├──┼─────────┤ Rz(-π/4) ├──────┤ Rx(-π/2) ├─────────────────────────┤ X ├─┤ Tdg ├┤ X ├─┤ T ├─┤ X ├────────┤ Tdg ├─────────┤ X ├──────────┤ T ├───────────┤ H ├──────────────────────────────────■─────────────────────■────■───┤ T ├───■──┤ H ├┤ X ├┤ Tdg ├┤ X ├──┼──┤ T ├┤ X ├┤ Tdg ├┤ X ├──┼─────┤ T ├─────┼───┤ H ├────────┼──────────────────┼──────────────────────■──────────────┼───────────■────■───┤ T ├───■─────────────┼──────────────■──┤ Sdg ├──┼────┼────────────┤ X ├──────────┤ S ├──┼─────────┼──────────────────┼───────────┼─────────────────────────────────────────────■───────────────────────────────────────■────────────────────────■──────────────────────────────■─────────────┼────────────┤ Rz(2.53925791897968) ├──┼─────────────────────────────────────┼────┼───────────────┼───────────────┼─────────────────────────┤ X ├┤ Rz(3.067) ├┤ Ry(-2.4148) ├┤ X ├┤ Ry(2.4148) ├──┼───────┤ Rz(-0.89384) ├────┤ X ├──┼──┤ S ├\n",
-       "              └───┘            │         │           │         │           │        ┌───┐        │       │          ┌───┐       │                        ┌───┐┌─────┐┌─┴─┐ ┌───┐ ┌───┐┌─────┐ └───┘      ┌─┴─┐┌───┐  │   ┌───┐   │  └─┬─┘  │    │            │     │    │     │    ├───┤   │    │  ┌┴───┴┐┌─┴─┐ ┌─┴─────┴──┐     └───┘         └─┬─┘                                    ┌─────┐                                 └───┘      └──────────────┘└───────┘                                                                            │    └─────────┘    └──────────┘  │                               │                │   ┌───┐   │  └─┬─┘  │         └──────────┘      └──────────┘                         └─┬─┘ └─────┘└─┬─┘ └───┘ └─┬─┘        └─────┘         └─┬─┘          └───┘           ├───┤                                  │             ┌───┐   │  ┌─┴─┐┌┴───┴┐┌─┴─┐├───┤├───┤├─────┤└───┘┌─┴─┐├───┤├───┤├─────┤└───┘┌─┴─┐┌──┴───┴──┐  │   └───┘        │                ┌─┴─┐   ┌─────┐        ┌─┴─┐     ┌───┐┌─┴─┐┌─────┐┌─┴─┐┌───┐ ├───┤               ┌─┴─┐          ┌───┐└─────┘┌─┴─┐  │           ┌┴───┴┐         └───┘  │       ┌─┴─┐       ┌───┐  ┌─┴─┐┌─────┐┌─┴─┐┌───┐ ┌───┐ ┌──────────────────────┐     ┌─┴─┐     ┌───────────────────────┐     ┌─┴─┐     ┌─────────────┐                                               │            └──────────────────────┘┌─┴─┐┌────────────────────────┐       ┌─┴─┐  │               │               │                         └─┬─┘└───────────┘└─────────────┘└─┬─┘└────────────┘  │       └──────────────┘    └───┘  │  └───┘\n",
-       "q_4: ──────────────────────────┼─────────┼───────────■─────────┼───────────■────■───┤ T ├───■────┼───────X──────────┤ H ├───────┼────────────────────────┤ X ├┤ Tdg ├┤ X ├─┤ T ├─┤ X ├┤ Tdg ├────────────┤ X ├┤ T ├──┼───┤ H ├───┼────┼────■────┼────────────┼─────■────┼─────■────┤ T ├───■────┼──┤ Sdg ├┤ X ├─┤ Rz(3π/4) ├─────────────────────┼──────────────────────────■───────────┤ Tdg ├─────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────┼─────────────────────────────────┼───────────────────■───────────┼───────────■────■───┤ T ├───■────■────┼──────────────────────────────────────────────────────────────────┼────────────■───────────┼────────────────────────────■──────────────■─────────────┤ T ├───────■──────────────■───────────┼─────────■───┤ T ├───┼──┤ X ├┤ Tdg ├┤ X ├┤ H ├┤ X ├┤ Tdg ├─────┤ X ├┤ T ├┤ X ├┤ Tdg ├─────┤ X ├┤ Rz(π/4) ├──┼────────────────┼────────────────┤ X ├───┤ Tdg ├────────┤ X ├─────┤ T ├┤ X ├┤ Tdg ├┤ X ├┤ T ├─┤ H ├───────────────┤ X ├──────────┤ H ├───────┤ X ├──┼───────────┤ Tdg ├────────────────┼───────┤ X ├───────┤ T ├──┤ X ├┤ Tdg ├┤ X ├┤ T ├─┤ H ├─┤ Rz(1.85641576693042) ├─────┤ X ├─────┤ Rz(-1.85641576693042) ├─────┤ X ├─────┤ Rz(-2.1453) ├───────────────────────────────────────────────┼────────────────────────────────────┤ X ├┤ Rz(-0.996321215859445) ├───────┤ X ├──┼───────────────┼───────────────┼───────────────────────────┼────────────────────────────────┼──────────────────┼──────────────────────────────────┼───────\n",
-       "                             ┌─┴─┐       │                     │   ┌───┐      ┌─┴─┐┌┴───┴┐┌─┴─┐┌─┴─┐┌──────────┐ ┌──┴───┴───┐ ┌─┴─┐┌─────────┐┌─────────┐└─┬─┘└─────┘└───┘ └───┘ └─┬─┘└┬───┬┘            └───┘└───┘┌─┴─┐┌┴───┴┐┌─┴─┐  │  ┌───┐┌─┴─┐┌─────┐ ┌─┴─┐ ┌───┐┌─┴─┐┌─────┐ └───┘      ┌─┴─┐└┬───┬┘├───┤ └──────────┘                     │       ┌───────────┐┌───┐ │ZZ(4.2882) └┬───┬┘                                                                                                                                                 │       ┌───┐                   ┌─┴─┐    ┌─────┐    ┌─┴─┐ ┌───┐ ┌─┴─┐┌─────┐┌─┴─┐┌───┐ ├───┤             │  ┌───────────────────────┐   ┌────┐   ┌──────────────────────┐   │                        │           ┌───┐                         ┌─┴─┐          ┌┴───┴┐    ┌─┴─┐     ┌───┐┌─┴─┐┌─────┐┌─┴─┐┌───┐┌─┴─┐┌┴───┴┐┌─┴─┐├───┤└┬───┬┘└───┘└───┘└─┬─┘└─────┘     └───┘└───┘└─┬─┘└┬───┬┘     └───┘└─────────┘┌─┴─┐┌─────┐     ┌─┴─┐    ┌───┐     └───┘   └─────┘        └───┘     └───┘└───┘└─────┘└───┘└───┘ └───┘               └───┘          └───┘       └───┘┌─┴─┐┌────────┴─────┴────────┐     ┌─┴─┐┌────┴───┴────┐┌─┴───┴─┐└───┘└─────┘└───┘└───┘ └───┘ └──────────────────────┘     └───┘     └───────────────────────┘     └───┘     └─────────────┘                                               │                                    └───┘└────────────────────────┘       └───┘  │               │     ┌───┐     │  ┌─────────────────────┐  │                                │                  │                                  │       \n",
-       "q_5: ────────────────────────┤ X ├───────■─────────────────────■───┤ T ├──────┤ X ├┤ Tdg ├┤ X ├┤ X ├┤ Rx(-π/2) ├─┤ Rz(-π/4) ├─┤ X ├┤ Rz(π/4) ├┤ Rx(π/2) ├──■───────────────────────■───┤ T ├───────────────────────┤ X ├┤ Tdg ├┤ X ├──■──┤ H ├┤ X ├┤ Tdg ├─┤ X ├─┤ T ├┤ X ├┤ Tdg ├────────────┤ X ├─┤ T ├─┤ H ├──────────────────────────────────■───────┤ Ry(6.079) ├┤ Z ├─■────────────┤ S ├──────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────■───────┤ H ├───────────────────┤ X ├────┤ Tdg ├────┤ X ├─┤ T ├─┤ X ├┤ Tdg ├┤ X ├┤ T ├─┤ H ├─────────────■──┤ Rz(-1.00500893102643) ├───┤ √X ├───┤ Rz(1.71350049100516) ├───■────────────────────────■───────────┤ T ├─────────────────────────┤ X ├──────────┤ Tdg ├────┤ X ├─────┤ H ├┤ X ├┤ Tdg ├┤ X ├┤ T ├┤ X ├┤ Tdg ├┤ X ├┤ T ├─┤ H ├─────────────■──────────────────────────■───┤ T ├──────────────────────┤ X ├┤ Tdg ├─────┤ X ├────┤ Z ├──────────────────────────────────────────────────────────────────────────────────────────────────────────────────────┤ X ├┤ Rz(-1.30629747996744) ├─────┤ X ├┤ Rz(-2.3551) ├┤ Ry(π) ├──────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────■─────────────────────────────────────────────────────────────────────────────────■───────────────■─────┤ T ├─────■──┤ Rz(3.2162142475914) ├──■────────────────────────────────■──────────────────■──────────────────────────────────■───────\n",
-       "                             └───┘                                 └───┘      └───┘└─────┘└───┘└───┘└──────────┘ └──────────┘ └───┘└─────────┘└─────────┘                              └───┘                       └───┘└─────┘└───┘     └───┘└───┘└─────┘ └───┘ └───┘└───┘└─────┘            └───┘ └───┘ └───┘                                          └───────────┘└───┘              └───┘                                                                                                                                                          └───┘                   └───┘    └─────┘    └───┘ └───┘ └───┘└─────┘└───┘└───┘ └───┘                └───────────────────────┘   └────┘   └──────────────────────┘                                        └───┘                         └───┘          └─────┘    └───┘     └───┘└───┘└─────┘└───┘└───┘└───┘└─────┘└───┘└───┘ └───┘                                            └───┘                      └───┘└─────┘     └───┘    └───┘                                                                                                                      └───┘└───────────────────────┘     └───┘└─────────────┘└───────┘                                                                                                                                                                                                                                                                                  └───┘        └─────────────────────┘
" + "
global phase: 1.0121\n",
+       "          ┌────────────┐                  ┌───┐     ┌─────────────┐     ┌───┐┌─────────────┐                           ┌────────────┐                                                                ┌───┐┌─────────────┐               ┌───┐┌─────────────┐  ┌─────────┐                                           ┌───┐ ┌──────────┐                ┌───┐┌─────────────┐┌────────────┐┌──────────────┐                     ┌───┐                                                                                                                          ┌──────────────┐┌────────────┐┌─────────────┐                                                                                                                                                                                                                                                                        ┌──────────┐     ┌───┐     ┌──────────┐┌────────────┐                                                                                                     ┌───────────────┐ ┌────────────┐┌────────────┐ ┌────────────┐                                                                                                                                                                                                                                                                                              ┌─────────┐      ┌────────────┐┌────────────┐┌─────────────┐                                                                        \n",
+       "q_0 -> 0 ─┤ Rz(0.2266) ├──────────────────┤ X ├─────┤ Ry(-2.3912) ├─────┤ X ├┤ Rz(-0.2266) ├───────────────────────■───┤ Rz(2.9633) ├────────────────────────────────────────────────────────────────┤ X ├┤ Ry(-2.8058) ├───────────────┤ X ├┤ Rz(0.17834) ├──┤ Ry(π/2) ├───────────────────────────────────────────┤ X ├─┤ Rz(-π/4) ├────────────────┤ X ├┤ Rz(-2.2555) ├┤ Ry(1.3517) ├┤ Rz(-0.43523) ├─────────────────────┤ X ├────────────────────X───────────────────────────────────────────────────────────────────────────────────────────────────X─┤ Rz(-0.27086) ├┤ Ry(2.2172) ├┤ Rz(0.43785) ├────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────■───────────────────────────────────────────■───────┤ Rz(-π/2) ├─────┤ X ├─────┤ Rz(-π/2) ├┤ Ry(-2.142) ├─────────────────────────────────────────────────────────────────────────────────────────────────────┤0              ├─┤ Rz(3.0787) ├┤ Ry(1.4504) ├─┤ Rz(2.8393) ├───────────────────────────────────────────────────────────────────────────────────────────────■─────────────────────■────────────────────────────────────────────────────────────────────────────────────────────────────────■──────────────────────────────────────────■─────────────────■──┤ Rz(π/4) ├───■──┤ Rz(2.3646) ├┤ Ry(2.1258) ├┤ Rz(-2.3646) ├────────────────────────────────────────────────────────────────────────\n",
+       "          └┬──────────┬┘  ┌────────┐      └─┬─┘     └─────────────┘┌───┐└─┬─┘└─┬──────────┬┘┌────────┐   ┌───┐     │  ┌┴────────────┴┐┌────────────┐                                                 └─┬─┘└─────────────┘               └─┬─┘└─────────────┘  └─────────┘                ┌──────────────┐           └─┬─┘ └──────────┘                └─┬─┘└─────────────┘└────────────┘└──────────────┘┌───┐┌─────────────┐ └─┬─┘                    │    ┌───┐ ┌────────────┐┌───┐┌─────────────┐               ┌───┐ ┌────────────┐                    │ └──────────────┘└┬─────────┬─┘└─────────────┘                                                           ┌─────────────┐            ┌────────────────┐  ┌─────────┐    ┌───────┐                                                                                  │                                           │       └──────────┘     └─┬─┘     ├─────────┬┘└───┬───┬────┘                                                                                                ┌───┐│               │┌┴────────────┤└───┬───┬────┘┌┴────────────┴┐┌─────────┐ ┌───┐┌──────────┐┌───┐ ┌───────────┐  ┌─────────┐ ┌──────────────┐ ┌──────────┐   │   ┌────────┐ ┌───┐  │   ┌──────────┐   ┌───┐    ┌───────────┐ ┌─────────┐┌─────────┐                                         │                                          │                 │  └─────────┘   │  └────────────┘└────────────┘└─────────────┘                    ┌─────────┐                   ┌───┐┌──────────┐┌───┐\n",
+       "q_1 -> 1 ──┤ Ry(-π/2) ├───┤ Rz(-π) ├────────┼──────────────────────┤ X ├──┼────┤ Ry(-π/2) ├─┤ Rz(-π) ├───┤ X ├─────┼──┤ Ry(-0.18411) ├┤ Rx(1.1905) ├───────────────────────────────────────────────────┼──────────────────────────────────┼──────────────────────────────────────────────┤0             ├─────────────┼─────────────────────────────────┼───────────────────────────────────────────────┤ X ├┤ Rz(-1.7868) ├───┼──────────────────────┼────┤ X ├─┤ Rz(1.7868) ├┤ X ├┤ Rz(-1.7391) ├───────────────┤ X ├─┤ Rz(1.7391) ├────────────────────┼────────■─────────┤ Rz(π/4) ├───────────────────■────────────────■───────■──────────────────────────■────┤ Rx(0.94723) ├────────────┤1               ├──┤ Rz(π/2) ├────┤ Ry(π) ├──────────────────────────────────────────────────────────────────────────────────┼───────────────────────────────────────────┼──────────────────────────■───────┤ Rx(π/2) ├─────┤ X ├─────────────────────────────────────────────────────────────────────────────────────────────────────┤ X ├┤               ├┤ Rz(-2.9463) ├────┤ X ├─────┤ Rz(-0.19532) ├┤ Ry(π/2) ├─┤ X ├┤ Rz(-π/4) ├┤ X ├─┤ Rz(-3π/4) ├──┤ Ry(π/2) ├─┤0             ├─┤ Ry(-π/2) ├───┼───┤ Rz(-π) ├─┤ X ├──┼───┤ Rz(-π/4) ├───┤ X ├────┤ Rz(-3π/4) ├─┤ Ry(π/2) ├┤ Rz(π/4) ├─────────────────────────────────────────┼────────────────────■─────────────────────┼─────────────────┼────────────────┼──────────────────────────────────────────────────────────────■──┤ Rz(π/4) ├───────────────────┤ X ├┤ Rz(-π/4) ├┤ X ├\n",
+       "           ├─────────┬┘   └────────┘        │       ┌─────────────┐└─┬─┘  │    └┬───────┬─┘ └─┬───┬──┘   └─┬─┘     │  └─┬──────────┬─┘└─┬────────┬─┘┌───┐┌──────────┐            ┌───┐┌─────────────┐  │       ┌───┐     ┌─────────────┐  │       ┌───┐     ┌─────────────┐              │              │             │                                 │                                               └─┬─┘├─────────────┴┐  │  ┌──────────────┐    │    └─┬─┘ └────────────┘└─┬─┘└────┬───┬────┘┌─────────────┐└─┬─┘┌┴────────────┤┌───┐┌────────────┐ │        │        ┌┴─────────┴─┐┌─────────────┐  │                │     ┌─┴─┐    ┌──────────────┐  ┌─┴─┐  └────┬───┬────┘┌──────────┐│                │  └──┬───┬──┘   ┌┴───────┴┐       ┌───┐      ┌──────────┐┌───┐┌───────────┐┌─────────┐ ┌────────────┐       │                                           │                                  └──┬───┬──┘     └─┬─┘     ┌──────────────┐┌───┐┌─────────────┐           ┌───┐┌─────────────┐         ┌───┐┌─────────────┐└─┬─┘│               │└─────────────┘    └─┬─┘     └─┬─────────┬──┘└─────────┘ └─┬─┘└──────────┘└─┬─┘ └───────────┘  └─────────┘ │  Rxx(4.5678) │┌┴──────────┴┐  │   └────────┘ └─┬─┘  │   └──────────┘   └─┬─┘    └───────────┘ └─────────┘├─────────┴┐   ┌────────┐   ┌───┐┌──────────┐     ┌─┴─┐     ┌─────────┐  │  ┌───┐┌──────────┐┌─┴─┐┌───────────┐  │  ┌─────────┐   │                ┌────────────┐ ┌───────────┐ ┌─────────────┐  │  └─────────┘                   └─┬─┘└──────────┘└─┬─┘\n",
+       "q_2 -> 2 ──┤ Ry(π/2) ├──────────────────────■───────┤ Ry(-2.3912) ├──┼────■─────┤ Rx(π) ├─────┤ X ├────────┼───────┼────┤ Ry(-π/2) ├────┤ Rz(-π) ├──┤ X ├┤ Rz(-π/4) ├────────────┤ X ├┤ Rz(-1.3795) ├──┼───────┤ X ├─────┤ Ry(-1.1638) ├──┼───────┤ X ├─────┤ Rz(-2.5344) ├──────────────┤              ├─────■───────┼─────────────────────────────────┼─────────■───────────────────────────────────────┼──┤0             ├──┼──┤ Rz(-0.85807) ├────┼──────┼───────────────────┼───────┤ X ├─────┤ Rz(-1.0517) ├──┼──┤ Ry(-1.7568) ├┤ X ├┤ Rz(2.6189) ├─┼────────┼────────┤ Ry(1.2411) ├┤ Rz(-1.7732) ├──┼────────────────┼─────┤ X ├────┤ Ry(-0.52456) ├──┤ X ├───────┤ X ├─────┤ Rz(-π/4) ├┤                ├─────┤ X ├──────┤ Rz(π/4) ├───────┤ X ├──────┤ Rz(-π/4) ├┤ X ├┤ Rz(1.391) ├┤ Ry(π/2) ├─┤ Rz(1.7105) ├───────┼─────────■─────────────────────────────────┼─────────────────────────────────────┤ X ├──────────┼───────┤ Rz(-0.13073) ├┤ X ├┤ Rz(0.13073) ├───────────┤ X ├┤ Rz(-1.0897) ├─────────┤ X ├┤ Rz(-2.2472) ├──■──┤               ├─────────────────────■─────────┤ Rz(π/4) ├─────────────────■────────────────■──────────────────────────────┤1             ├┤ Rz(1.9926) ├──┼────────────────┼────┼────────────────────┼─────────────────────────■─────┤ Ry(-π/2) ├───┤ Rz(-π) ├───┤ X ├┤ Rz(-π/4) ├─────┤ X ├─────┤ Rz(π/4) ├──┼──┤ X ├┤ Rz(-π/4) ├┤ X ├┤ Rz(-3π/4) ├──┼──┤ Ry(π/2) ├───┼────────■───────┤ Rz(3.0033) ├─┤ Ry(1.985) ├─┤ Rz(-3.0033) ├──┼──────────────────────────────────┼────────────────┼──\n",
+       "           ├─────────┤                              └─────────────┘  │          └───────┘     └─┬─┘        │       │    └──────────┘    └────────┘  └─┬─┘└──────────┘┌─────────┐ └─┬─┘└─────────────┘  │       └─┬─┘     └┬────────────┤  │       └─┬─┘     └─┬──────────┬┘┌────────────┐│  Rxx(2.4346) │   ┌─┴─┐     │  ┌────────────┐┌─────────────┐  │       ┌─┴─┐     ┌────────────┐ ┌────────────┐   │  │  Rxx(2.8835) │  │  └──────────────┘    │      │                   │       └─┬─┘     └─────────────┘  │  └─────────────┘└─┬─┘└────────────┘ │        │        └────────────┘└─────────────┘  │                │     └───┘    └────┬───┬─────┘  └───┘       └─┬─┘     └──────────┘│                │     └─┬─┘      └─────────┘       └─┬─┘      ├─────────┬┘└─┬─┘└───┬───┬───┘├─────────┴┐└───┬───┬────┘     ┌─┴─┐       │           ┌──────────────┐    ┌─┴─┐     ┌──────────┐┌─────────────┐   └─┬─┘          │       └──────────────┘└─┬─┘├─────────────┤┌─────────┐└─┬─┘└─────────────┘┌───────┐└─┬─┘└─────────────┘     │  Rxx(-1.5416) │                               └─────────┘                                     ┌──────────────┐┌─────────┐ └──────────────┘└────────────┘  │                │    │                    │     ┌─────────────┐     │     └──┬───┬───┘┌──┴────────┴──┐└─┬─┘└──┬───┬───┘  ┌──┴───┴───┐ └┬────────┤┌─┴─┐└─┬─┘├──────────┤└───┘└───────────┘  │  └─────────┘   │        │       └───┬───┬────┘ └┬─────────┬┘ └─────────────┘┌─┴─┐┌──────────┐┌───┐┌───────────┐  │  ┌─────────┐   │  \n",
+       "q_3 -> 3 ──┤ Rx(π/2) ├───────────────────────────────────────────────┼──────────────────────────┼──────────■───────┼──────────────────────────────────┼───────■──────┤ Ry(π/2) ├───┼───────────────────┼─────────■────────┤ Ry(1.1638) ├──┼─────────■─────────┤ Ry(-π/2) ├─┤ Rz(1.6333) ├┤              ├───┤ X ├─────┼──┤ Rz(2.6872) ├┤ Ry(-2.1999) ├──┼───────┤ X ├─────┤ Ry(2.1999) ├─┤ Rz(1.9627) ├───┼──┤1             ├──┼──────────────────────X──────┼───────────────────┼─────────┼────────────────────────┼───────────────────┼─────────────────┼────────┼───────────────────────────────────────┼────────────────┼───────────────────┤ X ├──────────────────────■───────────────────┤  Rxx(-0.94723) ├───────┼────────────────────────────■────────┤ Rz(π/4) ├───┼──────┤ X ├────┤ Rz(-π/4) ├────┤ X ├──────────┤ X ├───────┼───────────┤ Rz(-0.90092) ├────┤ X ├─────┤ Ry(-π/2) ├┤ Rz(-3.0109) ├─────■────────────┼─────────────────────────■──┤ Ry(-2.6323) ├┤ Rz(π/2) ├──┼─────────■───────┤ Rx(π) ├──┼──────────────────────┤               ├────────────────────────────────────■───────────────────────────────────────■──┤1             ├┤ Rz(π/4) ├─────────────────────────────────┼────────────────■────┼────────────────────■─────┤ Ry(0.14109) ├─────┼────────┤ X ├────┤ Ry(-0.14109) ├──┼─────┤ X ├──────┤ Ry(-π/2) ├──┤ Rz(-π) ├┤ X ├──┼──┤ Rz(-π/4) ├────────────────────┼────────────────┼────────┼───────────┤ X ├───────┤ Rz(π/4) ├─────────────────┤ X ├┤ Rz(-π/4) ├┤ X ├┤ Rz(-3π/4) ├──┼──┤ Ry(π/2) ├───┼──\n",
+       "           └─────────┘                                               │                          │     ┌─────────┐  │                                  │       │      └─────────┘   │    ┌─────────┐    │   ┌────────────┐ └────────────┘  │  ┌─────────────┐  ├──────────┤ └────────────┘│              │┌──┴───┴──┐  │  └────────────┘└─────────────┘  │       └───┘     └────────────┘ └────────────┘   │  └──────────────┘  │   ┌────────────┐ ┌───────┐  │                   │         │                        │    ┌──────────┐   │    ┌────────┐   │      ┌─┴─┐       ┌──────────┐    ┌────────┐  ┌─┴─┐┌──────────┐┌─┴─┐┌──────────┐     └─┬─┘      ┌───────┐                           │                │       │                                     └─────────┘   │      └─┬─┘    ├─────────┬┘    └─┬─┘     ┌────┴───┴─────┐ │           └┬────────────┬┘┌───┴───┴────┐└──────────┘└─────────────┘                  │         ┌──────────┐       └─────────────┘└─────────┘  │       ┌─┴─┐     └───────┘  │                      │               │                                    │                                       │  │  Rxx(4.8296) │├─────────┴┐   ┌────────┐                 ┌─┴─┐┌──────────┐     ┌─┴─┐┌───────────┐┌─────────┐└─────────────┘   ┌─┴─┐      └─┬─┘    └──────────────┘  │     └─┬─┘      └──────────┘  └────────┘└───┘  │  ├─────────┬┘                  ┌─┴─┐┌──────────┐┌─┴─┐    ┌─┴─┐         └─┬─┘       └─────────┘                 └───┘└──────────┘└─┬─┘└───────────┘  │  ├─────────┤   │  \n",
+       "q_4 -> 4 ────────────────────────────────────────────────────────────■──────────────────────────■─────┤ Rz(π/4) ├──┼──────────────────────────────────■───────┼────────────────────■────┤ Ry(π/2) ├────■───┤ Ry(2.8058) ├─────────────────■──┤ Rz(-2.0472) ├──┤ Ry(-π/2) ├───────────────┤1             ├┤ Rz(π/2) ├──┼─────────────────────────────────┼─────────────────────────────────────────────────┼────────────────────■───┤ Rz(1.4025) ├─┤ Ry(π) ├──┼───────────────────■─────────┼────────────────────────■────┤ Ry(-π/2) ├───┼────┤ Rz(-π) ├───┼──────┤ X ├───────┤ Ry(-π/2) ├────┤ Rz(-π) ├──┤ X ├┤ Rz(-π/4) ├┤ X ├┤ Rz(3π/4) ├───────■────────┤ Rx(π) ├───────────────────────────┤                ├───────■───────────────────────────────────────────────────■────────■──────┤ Rz(π/4) ├───────■───────┤ Rz(-0.44825) ├─┼────────────┤ Ry(3.1038) ├─┤ Rz(2.0726) ├─────────────────────────────────────────────■─────────┤ Rx(-π/2) ├───────────────────────────────────┼───────┤ X ├────────────────┼──────────────────────┤               ├────────────────────────────────────┼──────────────────────■────────────────┼──┤0             ├┤ Ry(-π/2) ├───┤ Rz(-π) ├─────────────────┤ X ├┤ Rz(-π/4) ├─────┤ X ├┤ Rz(-3π/4) ├┤ Ry(π/2) ├──────────────────┤ X ├────────┼────────────────────────■───────┼───────────────────────────────────────■──┤ Rz(π/4) ├───────────────────┤ X ├┤ Rz(-π/4) ├┤ X ├────┤ X ├───────────■────────────────────────────────────────────────────────■─────────────────■──┤ Rz(π/4) ├───■──\n",
+       "         ┌─────────────┐┌───────────┐┌─────────────┐                                                  └─────────┘┌─┴─┐  ┌──────────┐   ┌─────────┐          ┌─┴─┐    ┌──────────┐       └─────────┘        └────────────┘                    └─────────────┘  └──────────┘               └──────────────┘└─────────┘  │                                 │    ┌──────────┐ ┌────────────┐                  │                        └────────────┘ └───────┘  │  ┌─────────────┐            │                             └──────────┘   │    └────────┘   │ ┌────┴───┴────┐  └┬────────┬┘    └────────┘  └───┘└──────────┘└───┘└──────────┘                └───────┘                           │                │┌─────────────┐┌────────────┐┌──────────────┐                              └─────────┘               └──────────────┘ │ZZ(1.1107)  ├────────────┤ ├────────────┤                                                       └──────────┘                                   │       └───┘                │   ┌────────────┐     │               │  ┌──────────┐ ┌───────────┐      ┌─┴─┐      ┌──────────┐┌─┴─┐┌─────────┐ ┌─┴─┐└─┬──────────┬─┘└┬───────┬─┘   └────────┘                 └───┘└──────────┘     └───┘└───────────┘└─────────┘                  └───┘        │                                │      ┌─────────────┐                     └─────────┘                   └───┘└──────────┘└───┘    └───┘                                                                                         └─────────┘      \n",
+       "q_5 -> 5 ┤ Rz(-3.1159) ├┤ Ry(1.656) ├┤ Rz(0.58629) ├─────────────────────────────────────────────────────────────┤ X ├──┤ Ry(-π/2) ├───┤ Rz(π/2) ├──────────┤ X ├────┤ Rz(3π/4) ├─────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────■─────────────────────────────────■────┤ Rx(-π/2) ├─┤ Rz(1.7868) ├──────────────────■──────────────────────────────────────────────────■──┤ Rz(-2.4875) ├────────────■────────────────────────────────────────────■─────────────────X─┤ Ry(-1.4281) ├───┤ Rz(-π) ├───────────────────────────────────────────────────────────────────────────────────────────────────────┤0               ├┤ Rz(-1.4692) ├┤ Ry(1.3781) ├┤ Rz(-0.21319) ├─────────────────────────────────────────────────────────────────────────■────────────┤ Rx(2.6126) ├─┤ Rz(1.0897) ├──────────────────────────────────────────────────────────────────────────────────────────────────────■────────────────────────────■───┤ Rx(1.5416) ├─────┤1              ├──┤ Ry(-π/2) ├─┤ Rz(-3π/4) ├──────┤ X ├──────┤ Rz(-π/4) ├┤ X ├┤ Rz(π/4) ├─┤ X ├──┤ Rz(-π/4) ├───┤ Ry(π) ├──────────────────────────────────────────────────────────────────────────────────────────────────────────────────■────────────────────────────────■──────┤ Rx(-3.0231) ├────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────\n",
+       "         └─────────────┘└───────────┘└─────────────┘                                                             └───┘  └──────────┘   └─────────┘          └───┘    └──────────┘                                                                                                                                                                            └──────────┘ └────────────┘                                                                        └─────────────┘                                                                             └─────────────┘   └────────┘                                                                                                       └────────────────┘└─────────────┘└────────────┘└──────────────┘                                                                                      └────────────┘ └────────────┘                                                                                                                                       └────────────┘     └───────────────┘  └──────────┘ └───────────┘      └───┘      └──────────┘└───┘└─────────┘ └───┘  └──────────┘   └───────┘                                                                                                                                                          └─────────────┘
" ], "text/plain": [ - "global phase: 3.2614\n", - " ┌──────────┐ ┌───┐ ┌───┐ ┌─────┐ ┌───┐ ┌───┐ ┌───┐┌─────┐┌───┐ ┌───┐ ┌───┐ ┌───┐ ┌───┐ ┌─────┐┌───┐ ┌────────────┐┌────────────┐┌────────────┐ ┌───┐ ┌───┐ ┌───┐┌─────┐┌───┐ ┌───┐ ┌───┐ ┌─────────────┐ ┌───┐ ┌───┐ ┌───┐┌─────┐┌───┐┌──────────────────────┐ ┌───┐ ┌─────────────┐ ┌─────────┐ ┌─────────────┐ ┌───┐┌────────────────────────┐┌───┐┌──────────────────────┐ \n", - "q_0: ──────┤ Rz(3π/4) ├───────────────────────────────────────────────────────────────────────────────────────────────■───────┤ H ├───┤ X ├─────┤ Tdg ├──┤ X ├─┤ T ├─┤ X ├┤ Tdg ├┤ X ├─┤ T ├──┤ H ├────────■─────────■────────────────────────────────■────┤ T ├────────────┤ X ├─┤ Tdg ├┤ X ├──────────────■──┤ Rz(2.1395) ├┤ Ry(2.0919) ├┤ Rz(1.3684) ├─────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────■─────────────────────────────────■─────────────────────┤ X ├───────────────────────────────■───────────────────────────────■───┤ T ├──────┤ X ├┤ Tdg ├┤ X ├─────┤ X ├────────────■──────────────────────────────────────────────────────────■─────■───┤ T ├───■──────┤ Ry(-2.1846) ├─────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────■──────────────────────────■───────────────■───┤ T ├────────■──────────────────■─────────────────────────────────────■───┤ T ├──────┤ X ├┤ Tdg ├┤ X ├┤ Rz(1.30629747996744) ├───────────────────■──────────────────────────────────■─────────■──────────────────────────────■────■───┤ T ├────────────■────────────┤ Rz(-1.3651) ├───────┤ Ry(π/2) ├───────┤ Rz(-2.4141) ├───────────────┤ X ├┤ Rz(-0.838728781856755) ├┤ X ├┤ Rz(4.22380907548478) ├──────────────────────────■─────────────────────────────────────■───────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────\n", - " ┌─────┴──────────┴─────┐ ┌─┴─┐ └───┘ └─┬─┘ └─────┘ └─┬─┘ └───┘ └─┬─┘└┬───┬┘└─┬─┘ ├───┤ ┌┴───┴┐┌───┐┌─┴─┐┌───┐┌─┴─┐┌─────┐ ┌───┐┌───┐ ┌─┴─┐ ┌┴───┴┐┌───┐┌───┐ └─┬─┘ └┬───┬┘└─┬─┘ │ └────────────┘└────────────┘└───┬───┬────┘ ┌───┐ ┌───┐┌─────┐┌───┐ ┌───┐ ┌──────────────┐ │ ┌───┐ ┌────────────┐ │ ┌───────────┐ ┌───┐└─┬─┘┌──────────────┐┌───────────┐ │ ┌─────────────┐ │ └───┘ └─┬─┘└─────┘└─┬─┘ └─┬─┘ │ ┌───┐ │ ┌─┴─┐┌┴───┴┐┌─┴─┐┌───┴─────────────┴────┐┌───┐┌───────────────────────┐ ┌───┐ │ │ │ ├───┤ │ ┌───┐ │ │ └───┘ └─┬─┘└─────┘└─┬─┘└──────────────────────┘ │ │ │ ┌───┐ │ ┌─┴─┐┌┴───┴┐ ┌─┴─┐ └────┬───┬────┘ └──┬───┬──┘ └────┬───┬────┘ └─┬─┘└────────────────────────┘└─┬─┘└──────────────────────┘ │ ┌───┐ │ ┌───┐ ┌─────┐ ┌───┐ ┌────────────┐ ┌───┐┌───────────────────────┐ ┌───┐ \n", - "q_1: ┤ Rz(6.13001602516006) ├────────────────────────────────────────────────────────────────────────────X──────────┤ X ├───────────────■──────────────────┼───────────■───┤ T ├───┼───┤ X ├─┤ Tdg ├┤ X ├┤ X ├┤ H ├┤ X ├┤ Tdg ├──────────┤ X ├┤ T ├─┤ X ├─┤ Tdg ├┤ X ├┤ T ├───┼────┤ H ├───┼────────────────┼──────────────────────────────────┤ X ├────────────────────■─────────────────────────────■───┤ T ├───────────┤ X ├┤ Tdg ├┤ X ├─────┤ X ├──────────X────┤ Rz(-0.15782) ├──┼──┤ X ├─────┤ Rz(2.1041) ├───────┼──┤ Ry(-1.48) ├─┤ X ├──┼──┤ Rz(-0.28426) ├┤ Ry(1.712) ├──┼──┤ Rz(0.87374) ├──■───────────┼────────────────┼───────────┼─────────┼──────────────┼───────────────────────────────────■─────────────┤ T ├────┼───┤ X ├┤ Tdg ├┤ X ├┤ Rz(1.40164127769636) ├┤ X ├┤ Rz(-1.40164127769636) ├─┤ X ├──■────────────────────────────────────────────────────────────────────────────────────────────■────┼─────────────────────■────┼───────■───────┼───┤ T ├───■────┼──────┤ T ├───────┼─────────────────────────────────────┼────────────────┼───────────┼─────────────■──────────────────────────■────┼──────────────────────────────────┼─────────┼──────────────────■───┤ T ├───┼──┤ X ├┤ Tdg ├─────────┤ X ├───────────────┤ H ├───────────────┤ X ├───────────────┤ H ├────────────■─────────┼──────────────────────────────┼────────────────────────────────────────────────────┼──────────────■──────────────┤ T ├───┼──────────────────┤ X ├──┤ Tdg ├──┤ X ├─────┤ Rz(1.0361) ├────────────────────────────────────────────────────────┤ X ├┤ Rz(-2.60686136104895) ├─────┤ X ├─────\n", - " └──────────────────────┘ ┌───┐┌───┐┌─────┐┌───┐┌───┐┌───┐┌─────┐┌───┐┌───┐ ┌───┐ │ ┌───┴───┴────┐ │ └───┘ │ └─┬─┘ └─────┘└─┬─┘└───┘└───┘└───┘└┬───┬┘ └─┬─┘└───┘ └───┘ └─────┘└─┬─┘└───┘ │ └───┘ │ │ ┌───┐ └─┬─┘ ┌───┐ ┌─┴─┐ ┌─────┐ ┌───┐ ┌───┐┌─┴─┐┌┴───┴┐┌───┐┌───┐└─┬─┘└┬───┬┘└─┬─┘ └─┬─┘ │ └───┬─────┬────┘┌─┴─┐└─┬─┘┌────┴────────────┴────┐┌─┴─┐├───────────┴┐└─┬─┘ │ └─┬─────────┬──┘└───────────┘ │ └─────────────┘┌─┴─┐┌─────┐ │ │ │ │ ┌─┴─┐ ┌───┐ ┌─┴─┐ ┌┴───┴┐ ┌─┴─┐ ├───┤└┬───┬┘└───┘└──────────────────────┘└─┬─┘└───────────────────────┘ └─┬─┘ │ZZ(0.74145) │ │ ┌───┐ │ │ ┌─┴─┐ │ ┌┴───┴┐┌─┴─┐ │ ┌───┴───┴────┐ │ ┌────────────┐┌────────────┐ │ │ │ │ ┌───┐ ┌───┐ │ │ │ │ │ └───┘ │ └───┘└─────┘ └───┘ └───┘ └─┬─┘ ├───┤ ┌─┴─┐ │ ┌─────┐ │ ┌───┐ ┌───┐ │ ┌─┴─┐ ┌┴───┴┐ │ ┌───┐┌─────────┐└─┬─┘┌─┴─────┴─┐└─┬─┘ └────────────┘ └─┬─┘└───────────────────────┘ └─┬─┘ \n", - "q_2: ──────────────────────────■──┤ H ├┤ X ├┤ Tdg ├┤ X ├┤ T ├┤ X ├┤ Tdg ├┤ X ├┤ T ├─┤ H ├────────■───────┼──────┤ Ry(4.0455) ├─────────────────────────────┼───────────■───────────┼─────┼────────────┼────■─────────■───┤ T ├───■─────────┼─────────────────■─────┼──────────┼────────────┼────■─────■─────┼──────┤ T ├───────────■─────────────■───────────┤ H ├────┤ X ├───┤ Tdg ├────┤ X ├─┤ T ├┤ X ├┤ Tdg ├┤ X ├┤ T ├──┼───┤ H ├───┼─────────■────────────X────────┤ Sdg ├─────┤ X ├──┼──┤ Rz(-1.7391209782858) ├┤ X ├┤ Rz(1.7391) ├──┼────┼────┤ Ry(π/2) ├──────────────────┼─────────────────┤ X ├┤ Tdg ├──┼────────────────┼───────────┼─────────┼────────────┤ X ├─────────────┤ T ├─────────────┤ X ├──────────┤ Tdg ├─┤ X ├─┤ T ├─┤ H ├────────────────────────────────■──────────────────────────────■────■────────────────────────────────────────────────────────────────────────────────■───────────┼────┼─────────■───┤ T ├───┼────┼─────┤ X ├─────┼──┤ Tdg ├┤ X ├──┼──┤ Rz(1.1107) ├──┼──┤ Ry(1.9224) ├┤ Rz(2.0685) ├───────┼────────────────┼───────────┼─────────────┼────────────┤ X ├─┤ S ├───┼────┼──────────────■───────────────────┼─────────┼──────────────────┼───────────┼─────────────────────────────────────────────────────────────────■─────────────────┤ H ├──────────┤ X ├───────┼───────────┤ Tdg ├────────────┼───────────┤ X ├───────────────────┤ T ├────────────┼────────────┤ X ├───────────┤ Tdg ├──┼──┤ X ├┤ Rz(π/4) ├──┼──┤ Ry(π/2) ├──┼───────────────────────────────────────────────────────────────────────────────┼─────────────────────────────■────┼───────\n", - " ┌───┐ │ └───┘└─┬─┘└─────┘└─┬─┘└───┘└─┬─┘└─────┘└─┬─┘└───┘ └───┘ │ │ └────────────┘ │ │ │ │ ┌───┐ │ │ │ └───┘ │ ┌───┐ │ │ │ │ ┌───┐ │ │ ┌─┴─┐ │ ┌┴───┴┐ ┌─┴─┐ ┌───┐ └───┘ └───┘ └─────┘ └─┬─┘ └───┘└───┘└─────┘└─┬─┘└───┘ │ ├───┤ │ ┌──────────────┐┌───────┐ └─────┘ └───┘ │ └──────────────────────┘└───┘└────────────┘ │ │ ├─────────┤ ┌──────────┐ │ └───┘└─────┘ │ │ │ ┌───┐ │ ┌──┴───┴───┐ ┌──┴───┴───┐ └───┘ └┬───┬┘┌┴───┴┐├───┤ ├───┤ ┌───┐ ┌─────┐ ┌───┐ ┌───┐ ┌───┐ ┌───┐ ┌───┐┌─┴─┐┌─────┐┌─┴─┐ │ ┌───┐┌─┴─┐┌┴───┴┐┌─┴─┐ │ ├───┤ │ └┬───┬┘└───┘ │ └────────────┘ │ └────────────┘└────────────┘ │ │ ┌───┐ │ │ └─┬─┘┌┴───┴┐ │ │ ┌─┴─┐ ┌───┐ │ │ │ │ └───┘ └───┘ │ └─────┘ │ └─┬─┘ ┌────────┴───┴─────────┐ │ └───┘ └─────┘ │ └─┬─┘└─────────┘ │ └─────────┘ │ ┌───┐┌───────────┐┌─────────────┐┌───┐┌────────────┐ │ ┌──────────────┐ ┌─┴─┐ │ ┌───┐\n", - "q_3: ─────────┤ T ├────────────┼─────────┼───────────┼─────────┼───────────┼─────────────────────┼───────┼──────────────────────■──────────────────────────■───────────┼───────────■─────■────┤ T ├───■────┼─────────┼───────────┼──┤ X ├──┼────■────────────┼─────┼────■─────┼────┤ T ├───┼────┼───┤ X ├───┼─────┤ Tdg ├────────┤ X ├─────────┤ X ├───────────────────────────────────────■──────────────────────■─────────■───┤ T ├───■──┤ Rz(-0.25207) ├┤ Ry(π) ├───────────────────────■───────────────────────────────────────────────■────┼────┤ Rx(π/2) ├────┤ Rz(3π/4) ├──┼───────────────────────────────┼────────────────┼───────────┼──┤ X ├──┼─────────┤ Rz(-π/4) ├──────┤ Rx(-π/2) ├─────────────────────────┤ X ├─┤ Tdg ├┤ X ├─┤ T ├─┤ X ├────────┤ Tdg ├─────────┤ X ├──────────┤ T ├───────────┤ H ├──────────────────────────────────■─────────────────────■────■───┤ T ├───■──┤ H ├┤ X ├┤ Tdg ├┤ X ├──┼──┤ T ├┤ X ├┤ Tdg ├┤ X ├──┼─────┤ T ├─────┼───┤ H ├────────┼──────────────────┼──────────────────────■──────────────┼───────────■────■───┤ T ├───■─────────────┼──────────────■──┤ Sdg ├──┼────┼────────────┤ X ├──────────┤ S ├──┼─────────┼──────────────────┼───────────┼─────────────────────────────────────────────■───────────────────────────────────────■────────────────────────■──────────────────────────────■─────────────┼────────────┤ Rz(2.53925791897968) ├──┼─────────────────────────────────────┼────┼───────────────┼───────────────┼─────────────────────────┤ X ├┤ Rz(3.067) ├┤ Ry(-2.4148) ├┤ X ├┤ Ry(2.4148) ├──┼───────┤ Rz(-0.89384) ├────┤ X ├──┼──┤ S ├\n", - " └───┘ │ │ │ │ │ ┌───┐ │ │ ┌───┐ │ ┌───┐┌─────┐┌─┴─┐ ┌───┐ ┌───┐┌─────┐ └───┘ ┌─┴─┐┌───┐ │ ┌───┐ │ └─┬─┘ │ │ │ │ │ │ ├───┤ │ │ ┌┴───┴┐┌─┴─┐ ┌─┴─────┴──┐ └───┘ └─┬─┘ ┌─────┐ └───┘ └──────────────┘└───────┘ │ └─────────┘ └──────────┘ │ │ │ ┌───┐ │ └─┬─┘ │ └──────────┘ └──────────┘ └─┬─┘ └─────┘└─┬─┘ └───┘ └─┬─┘ └─────┘ └─┬─┘ └───┘ ├───┤ │ ┌───┐ │ ┌─┴─┐┌┴───┴┐┌─┴─┐├───┤├───┤├─────┤└───┘┌─┴─┐├───┤├───┤├─────┤└───┘┌─┴─┐┌──┴───┴──┐ │ └───┘ │ ┌─┴─┐ ┌─────┐ ┌─┴─┐ ┌───┐┌─┴─┐┌─────┐┌─┴─┐┌───┐ ├───┤ ┌─┴─┐ ┌───┐└─────┘┌─┴─┐ │ ┌┴───┴┐ └───┘ │ ┌─┴─┐ ┌───┐ ┌─┴─┐┌─────┐┌─┴─┐┌───┐ ┌───┐ ┌──────────────────────┐ ┌─┴─┐ ┌───────────────────────┐ ┌─┴─┐ ┌─────────────┐ │ └──────────────────────┘┌─┴─┐┌────────────────────────┐ ┌─┴─┐ │ │ │ └─┬─┘└───────────┘└─────────────┘└─┬─┘└────────────┘ │ └──────────────┘ └───┘ │ └───┘\n", - "q_4: ──────────────────────────┼─────────┼───────────■─────────┼───────────■────■───┤ T ├───■────┼───────X──────────┤ H ├───────┼────────────────────────┤ X ├┤ Tdg ├┤ X ├─┤ T ├─┤ X ├┤ Tdg ├────────────┤ X ├┤ T ├──┼───┤ H ├───┼────┼────■────┼────────────┼─────■────┼─────■────┤ T ├───■────┼──┤ Sdg ├┤ X ├─┤ Rz(3π/4) ├─────────────────────┼──────────────────────────■───────────┤ Tdg ├─────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────┼─────────────────────────────────┼───────────────────■───────────┼───────────■────■───┤ T ├───■────■────┼──────────────────────────────────────────────────────────────────┼────────────■───────────┼────────────────────────────■──────────────■─────────────┤ T ├───────■──────────────■───────────┼─────────■───┤ T ├───┼──┤ X ├┤ Tdg ├┤ X ├┤ H ├┤ X ├┤ Tdg ├─────┤ X ├┤ T ├┤ X ├┤ Tdg ├─────┤ X ├┤ Rz(π/4) ├──┼────────────────┼────────────────┤ X ├───┤ Tdg ├────────┤ X ├─────┤ T ├┤ X ├┤ Tdg ├┤ X ├┤ T ├─┤ H ├───────────────┤ X ├──────────┤ H ├───────┤ X ├──┼───────────┤ Tdg ├────────────────┼───────┤ X ├───────┤ T ├──┤ X ├┤ Tdg ├┤ X ├┤ T ├─┤ H ├─┤ Rz(1.85641576693042) ├─────┤ X ├─────┤ Rz(-1.85641576693042) ├─────┤ X ├─────┤ Rz(-2.1453) ├───────────────────────────────────────────────┼────────────────────────────────────┤ X ├┤ Rz(-0.996321215859445) ├───────┤ X ├──┼───────────────┼───────────────┼───────────────────────────┼────────────────────────────────┼──────────────────┼──────────────────────────────────┼───────\n", - " ┌─┴─┐ │ │ ┌───┐ ┌─┴─┐┌┴───┴┐┌─┴─┐┌─┴─┐┌──────────┐ ┌──┴───┴───┐ ┌─┴─┐┌─────────┐┌─────────┐└─┬─┘└─────┘└───┘ └───┘ └─┬─┘└┬───┬┘ └───┘└───┘┌─┴─┐┌┴───┴┐┌─┴─┐ │ ┌───┐┌─┴─┐┌─────┐ ┌─┴─┐ ┌───┐┌─┴─┐┌─────┐ └───┘ ┌─┴─┐└┬───┬┘├───┤ └──────────┘ │ ┌───────────┐┌───┐ │ZZ(4.2882) └┬───┬┘ │ ┌───┐ ┌─┴─┐ ┌─────┐ ┌─┴─┐ ┌───┐ ┌─┴─┐┌─────┐┌─┴─┐┌───┐ ├───┤ │ ┌───────────────────────┐ ┌────┐ ┌──────────────────────┐ │ │ ┌───┐ ┌─┴─┐ ┌┴───┴┐ ┌─┴─┐ ┌───┐┌─┴─┐┌─────┐┌─┴─┐┌───┐┌─┴─┐┌┴───┴┐┌─┴─┐├───┤└┬───┬┘└───┘└───┘└─┬─┘└─────┘ └───┘└───┘└─┬─┘└┬───┬┘ └───┘└─────────┘┌─┴─┐┌─────┐ ┌─┴─┐ ┌───┐ └───┘ └─────┘ └───┘ └───┘└───┘└─────┘└───┘└───┘ └───┘ └───┘ └───┘ └───┘┌─┴─┐┌────────┴─────┴────────┐ ┌─┴─┐┌────┴───┴────┐┌─┴───┴─┐└───┘└─────┘└───┘└───┘ └───┘ └──────────────────────┘ └───┘ └───────────────────────┘ └───┘ └─────────────┘ │ └───┘└────────────────────────┘ └───┘ │ │ ┌───┐ │ ┌─────────────────────┐ │ │ │ │ \n", - "q_5: ────────────────────────┤ X ├───────■─────────────────────■───┤ T ├──────┤ X ├┤ Tdg ├┤ X ├┤ X ├┤ Rx(-π/2) ├─┤ Rz(-π/4) ├─┤ X ├┤ Rz(π/4) ├┤ Rx(π/2) ├──■───────────────────────■───┤ T ├───────────────────────┤ X ├┤ Tdg ├┤ X ├──■──┤ H ├┤ X ├┤ Tdg ├─┤ X ├─┤ T ├┤ X ├┤ Tdg ├────────────┤ X ├─┤ T ├─┤ H ├──────────────────────────────────■───────┤ Ry(6.079) ├┤ Z ├─■────────────┤ S ├──────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────■───────┤ H ├───────────────────┤ X ├────┤ Tdg ├────┤ X ├─┤ T ├─┤ X ├┤ Tdg ├┤ X ├┤ T ├─┤ H ├─────────────■──┤ Rz(-1.00500893102643) ├───┤ √X ├───┤ Rz(1.71350049100516) ├───■────────────────────────■───────────┤ T ├─────────────────────────┤ X ├──────────┤ Tdg ├────┤ X ├─────┤ H ├┤ X ├┤ Tdg ├┤ X ├┤ T ├┤ X ├┤ Tdg ├┤ X ├┤ T ├─┤ H ├─────────────■──────────────────────────■───┤ T ├──────────────────────┤ X ├┤ Tdg ├─────┤ X ├────┤ Z ├──────────────────────────────────────────────────────────────────────────────────────────────────────────────────────┤ X ├┤ Rz(-1.30629747996744) ├─────┤ X ├┤ Rz(-2.3551) ├┤ Ry(π) ├──────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────■─────────────────────────────────────────────────────────────────────────────────■───────────────■─────┤ T ├─────■──┤ Rz(3.2162142475914) ├──■────────────────────────────────■──────────────────■──────────────────────────────────■───────\n", - " └───┘ └───┘ └───┘└─────┘└───┘└───┘└──────────┘ └──────────┘ └───┘└─────────┘└─────────┘ └───┘ └───┘└─────┘└───┘ └───┘└───┘└─────┘ └───┘ └───┘└───┘└─────┘ └───┘ └───┘ └───┘ └───────────┘└───┘ └───┘ └───┘ └───┘ └─────┘ └───┘ └───┘ └───┘└─────┘└───┘└───┘ └───┘ └───────────────────────┘ └────┘ └──────────────────────┘ └───┘ └───┘ └─────┘ └───┘ └───┘└───┘└─────┘└───┘└───┘└───┘└─────┘└───┘└───┘ └───┘ └───┘ └───┘└─────┘ └───┘ └───┘ └───┘└───────────────────────┘ └───┘└─────────────┘└───────┘ └───┘ └─────────────────────┘ " + "global phase: 1.0121\n", + " ┌────────────┐ ┌───┐ ┌─────────────┐ ┌───┐┌─────────────┐ ┌────────────┐ ┌───┐┌─────────────┐ ┌───┐┌─────────────┐ ┌─────────┐ ┌───┐ ┌──────────┐ ┌───┐┌─────────────┐┌────────────┐┌──────────────┐ ┌───┐ ┌──────────────┐┌────────────┐┌─────────────┐ ┌──────────┐ ┌───┐ ┌──────────┐┌────────────┐ ┌───────────────┐ ┌────────────┐┌────────────┐ ┌────────────┐ ┌─────────┐ ┌────────────┐┌────────────┐┌─────────────┐ \n", + "q_0 -> 0 ─┤ Rz(0.2266) ├──────────────────┤ X ├─────┤ Ry(-2.3912) ├─────┤ X ├┤ Rz(-0.2266) ├───────────────────────■───┤ Rz(2.9633) ├────────────────────────────────────────────────────────────────┤ X ├┤ Ry(-2.8058) ├───────────────┤ X ├┤ Rz(0.17834) ├──┤ Ry(π/2) ├───────────────────────────────────────────┤ X ├─┤ Rz(-π/4) ├────────────────┤ X ├┤ Rz(-2.2555) ├┤ Ry(1.3517) ├┤ Rz(-0.43523) ├─────────────────────┤ X ├────────────────────X───────────────────────────────────────────────────────────────────────────────────────────────────X─┤ Rz(-0.27086) ├┤ Ry(2.2172) ├┤ Rz(0.43785) ├────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────■───────────────────────────────────────────■───────┤ Rz(-π/2) ├─────┤ X ├─────┤ Rz(-π/2) ├┤ Ry(-2.142) ├─────────────────────────────────────────────────────────────────────────────────────────────────────┤0 ├─┤ Rz(3.0787) ├┤ Ry(1.4504) ├─┤ Rz(2.8393) ├───────────────────────────────────────────────────────────────────────────────────────────────■─────────────────────■────────────────────────────────────────────────────────────────────────────────────────────────────────■──────────────────────────────────────────■─────────────────■──┤ Rz(π/4) ├───■──┤ Rz(2.3646) ├┤ Ry(2.1258) ├┤ Rz(-2.3646) ├────────────────────────────────────────────────────────────────────────\n", + " └┬──────────┬┘ ┌────────┐ └─┬─┘ └─────────────┘┌───┐└─┬─┘└─┬──────────┬┘┌────────┐ ┌───┐ │ ┌┴────────────┴┐┌────────────┐ └─┬─┘└─────────────┘ └─┬─┘└─────────────┘ └─────────┘ ┌──────────────┐ └─┬─┘ └──────────┘ └─┬─┘└─────────────┘└────────────┘└──────────────┘┌───┐┌─────────────┐ └─┬─┘ │ ┌───┐ ┌────────────┐┌───┐┌─────────────┐ ┌───┐ ┌────────────┐ │ └──────────────┘└┬─────────┬─┘└─────────────┘ ┌─────────────┐ ┌────────────────┐ ┌─────────┐ ┌───────┐ │ │ └──────────┘ └─┬─┘ ├─────────┬┘└───┬───┬────┘ ┌───┐│ │┌┴────────────┤└───┬───┬────┘┌┴────────────┴┐┌─────────┐ ┌───┐┌──────────┐┌───┐ ┌───────────┐ ┌─────────┐ ┌──────────────┐ ┌──────────┐ │ ┌────────┐ ┌───┐ │ ┌──────────┐ ┌───┐ ┌───────────┐ ┌─────────┐┌─────────┐ │ │ │ └─────────┘ │ └────────────┘└────────────┘└─────────────┘ ┌─────────┐ ┌───┐┌──────────┐┌───┐\n", + "q_1 -> 1 ──┤ Ry(-π/2) ├───┤ Rz(-π) ├────────┼──────────────────────┤ X ├──┼────┤ Ry(-π/2) ├─┤ Rz(-π) ├───┤ X ├─────┼──┤ Ry(-0.18411) ├┤ Rx(1.1905) ├───────────────────────────────────────────────────┼──────────────────────────────────┼──────────────────────────────────────────────┤0 ├─────────────┼─────────────────────────────────┼───────────────────────────────────────────────┤ X ├┤ Rz(-1.7868) ├───┼──────────────────────┼────┤ X ├─┤ Rz(1.7868) ├┤ X ├┤ Rz(-1.7391) ├───────────────┤ X ├─┤ Rz(1.7391) ├────────────────────┼────────■─────────┤ Rz(π/4) ├───────────────────■────────────────■───────■──────────────────────────■────┤ Rx(0.94723) ├────────────┤1 ├──┤ Rz(π/2) ├────┤ Ry(π) ├──────────────────────────────────────────────────────────────────────────────────┼───────────────────────────────────────────┼──────────────────────────■───────┤ Rx(π/2) ├─────┤ X ├─────────────────────────────────────────────────────────────────────────────────────────────────────┤ X ├┤ ├┤ Rz(-2.9463) ├────┤ X ├─────┤ Rz(-0.19532) ├┤ Ry(π/2) ├─┤ X ├┤ Rz(-π/4) ├┤ X ├─┤ Rz(-3π/4) ├──┤ Ry(π/2) ├─┤0 ├─┤ Ry(-π/2) ├───┼───┤ Rz(-π) ├─┤ X ├──┼───┤ Rz(-π/4) ├───┤ X ├────┤ Rz(-3π/4) ├─┤ Ry(π/2) ├┤ Rz(π/4) ├─────────────────────────────────────────┼────────────────────■─────────────────────┼─────────────────┼────────────────┼──────────────────────────────────────────────────────────────■──┤ Rz(π/4) ├───────────────────┤ X ├┤ Rz(-π/4) ├┤ X ├\n", + " ├─────────┬┘ └────────┘ │ ┌─────────────┐└─┬─┘ │ └┬───────┬─┘ └─┬───┬──┘ └─┬─┘ │ └─┬──────────┬─┘└─┬────────┬─┘┌───┐┌──────────┐ ┌───┐┌─────────────┐ │ ┌───┐ ┌─────────────┐ │ ┌───┐ ┌─────────────┐ │ │ │ │ └─┬─┘├─────────────┴┐ │ ┌──────────────┐ │ └─┬─┘ └────────────┘└─┬─┘└────┬───┬────┘┌─────────────┐└─┬─┘┌┴────────────┤┌───┐┌────────────┐ │ │ ┌┴─────────┴─┐┌─────────────┐ │ │ ┌─┴─┐ ┌──────────────┐ ┌─┴─┐ └────┬───┬────┘┌──────────┐│ │ └──┬───┬──┘ ┌┴───────┴┐ ┌───┐ ┌──────────┐┌───┐┌───────────┐┌─────────┐ ┌────────────┐ │ │ └──┬───┬──┘ └─┬─┘ ┌──────────────┐┌───┐┌─────────────┐ ┌───┐┌─────────────┐ ┌───┐┌─────────────┐└─┬─┘│ │└─────────────┘ └─┬─┘ └─┬─────────┬──┘└─────────┘ └─┬─┘└──────────┘└─┬─┘ └───────────┘ └─────────┘ │ Rxx(4.5678) │┌┴──────────┴┐ │ └────────┘ └─┬─┘ │ └──────────┘ └─┬─┘ └───────────┘ └─────────┘├─────────┴┐ ┌────────┐ ┌───┐┌──────────┐ ┌─┴─┐ ┌─────────┐ │ ┌───┐┌──────────┐┌─┴─┐┌───────────┐ │ ┌─────────┐ │ ┌────────────┐ ┌───────────┐ ┌─────────────┐ │ └─────────┘ └─┬─┘└──────────┘└─┬─┘\n", + "q_2 -> 2 ──┤ Ry(π/2) ├──────────────────────■───────┤ Ry(-2.3912) ├──┼────■─────┤ Rx(π) ├─────┤ X ├────────┼───────┼────┤ Ry(-π/2) ├────┤ Rz(-π) ├──┤ X ├┤ Rz(-π/4) ├────────────┤ X ├┤ Rz(-1.3795) ├──┼───────┤ X ├─────┤ Ry(-1.1638) ├──┼───────┤ X ├─────┤ Rz(-2.5344) ├──────────────┤ ├─────■───────┼─────────────────────────────────┼─────────■───────────────────────────────────────┼──┤0 ├──┼──┤ Rz(-0.85807) ├────┼──────┼───────────────────┼───────┤ X ├─────┤ Rz(-1.0517) ├──┼──┤ Ry(-1.7568) ├┤ X ├┤ Rz(2.6189) ├─┼────────┼────────┤ Ry(1.2411) ├┤ Rz(-1.7732) ├──┼────────────────┼─────┤ X ├────┤ Ry(-0.52456) ├──┤ X ├───────┤ X ├─────┤ Rz(-π/4) ├┤ ├─────┤ X ├──────┤ Rz(π/4) ├───────┤ X ├──────┤ Rz(-π/4) ├┤ X ├┤ Rz(1.391) ├┤ Ry(π/2) ├─┤ Rz(1.7105) ├───────┼─────────■─────────────────────────────────┼─────────────────────────────────────┤ X ├──────────┼───────┤ Rz(-0.13073) ├┤ X ├┤ Rz(0.13073) ├───────────┤ X ├┤ Rz(-1.0897) ├─────────┤ X ├┤ Rz(-2.2472) ├──■──┤ ├─────────────────────■─────────┤ Rz(π/4) ├─────────────────■────────────────■──────────────────────────────┤1 ├┤ Rz(1.9926) ├──┼────────────────┼────┼────────────────────┼─────────────────────────■─────┤ Ry(-π/2) ├───┤ Rz(-π) ├───┤ X ├┤ Rz(-π/4) ├─────┤ X ├─────┤ Rz(π/4) ├──┼──┤ X ├┤ Rz(-π/4) ├┤ X ├┤ Rz(-3π/4) ├──┼──┤ Ry(π/2) ├───┼────────■───────┤ Rz(3.0033) ├─┤ Ry(1.985) ├─┤ Rz(-3.0033) ├──┼──────────────────────────────────┼────────────────┼──\n", + " ├─────────┤ └─────────────┘ │ └───────┘ └─┬─┘ │ │ └──────────┘ └────────┘ └─┬─┘└──────────┘┌─────────┐ └─┬─┘└─────────────┘ │ └─┬─┘ └┬────────────┤ │ └─┬─┘ └─┬──────────┬┘┌────────────┐│ Rxx(2.4346) │ ┌─┴─┐ │ ┌────────────┐┌─────────────┐ │ ┌─┴─┐ ┌────────────┐ ┌────────────┐ │ │ Rxx(2.8835) │ │ └──────────────┘ │ │ │ └─┬─┘ └─────────────┘ │ └─────────────┘└─┬─┘└────────────┘ │ │ └────────────┘└─────────────┘ │ │ └───┘ └────┬───┬─────┘ └───┘ └─┬─┘ └──────────┘│ │ └─┬─┘ └─────────┘ └─┬─┘ ├─────────┬┘└─┬─┘└───┬───┬───┘├─────────┴┐└───┬───┬────┘ ┌─┴─┐ │ ┌──────────────┐ ┌─┴─┐ ┌──────────┐┌─────────────┐ └─┬─┘ │ └──────────────┘└─┬─┘├─────────────┤┌─────────┐└─┬─┘└─────────────┘┌───────┐└─┬─┘└─────────────┘ │ Rxx(-1.5416) │ └─────────┘ ┌──────────────┐┌─────────┐ └──────────────┘└────────────┘ │ │ │ │ ┌─────────────┐ │ └──┬───┬───┘┌──┴────────┴──┐└─┬─┘└──┬───┬───┘ ┌──┴───┴───┐ └┬────────┤┌─┴─┐└─┬─┘├──────────┤└───┘└───────────┘ │ └─────────┘ │ │ └───┬───┬────┘ └┬─────────┬┘ └─────────────┘┌─┴─┐┌──────────┐┌───┐┌───────────┐ │ ┌─────────┐ │ \n", + "q_3 -> 3 ──┤ Rx(π/2) ├───────────────────────────────────────────────┼──────────────────────────┼──────────■───────┼──────────────────────────────────┼───────■──────┤ Ry(π/2) ├───┼───────────────────┼─────────■────────┤ Ry(1.1638) ├──┼─────────■─────────┤ Ry(-π/2) ├─┤ Rz(1.6333) ├┤ ├───┤ X ├─────┼──┤ Rz(2.6872) ├┤ Ry(-2.1999) ├──┼───────┤ X ├─────┤ Ry(2.1999) ├─┤ Rz(1.9627) ├───┼──┤1 ├──┼──────────────────────X──────┼───────────────────┼─────────┼────────────────────────┼───────────────────┼─────────────────┼────────┼───────────────────────────────────────┼────────────────┼───────────────────┤ X ├──────────────────────■───────────────────┤ Rxx(-0.94723) ├───────┼────────────────────────────■────────┤ Rz(π/4) ├───┼──────┤ X ├────┤ Rz(-π/4) ├────┤ X ├──────────┤ X ├───────┼───────────┤ Rz(-0.90092) ├────┤ X ├─────┤ Ry(-π/2) ├┤ Rz(-3.0109) ├─────■────────────┼─────────────────────────■──┤ Ry(-2.6323) ├┤ Rz(π/2) ├──┼─────────■───────┤ Rx(π) ├──┼──────────────────────┤ ├────────────────────────────────────■───────────────────────────────────────■──┤1 ├┤ Rz(π/4) ├─────────────────────────────────┼────────────────■────┼────────────────────■─────┤ Ry(0.14109) ├─────┼────────┤ X ├────┤ Ry(-0.14109) ├──┼─────┤ X ├──────┤ Ry(-π/2) ├──┤ Rz(-π) ├┤ X ├──┼──┤ Rz(-π/4) ├────────────────────┼────────────────┼────────┼───────────┤ X ├───────┤ Rz(π/4) ├─────────────────┤ X ├┤ Rz(-π/4) ├┤ X ├┤ Rz(-3π/4) ├──┼──┤ Ry(π/2) ├───┼──\n", + " └─────────┘ │ │ ┌─────────┐ │ │ │ └─────────┘ │ ┌─────────┐ │ ┌────────────┐ └────────────┘ │ ┌─────────────┐ ├──────────┤ └────────────┘│ │┌──┴───┴──┐ │ └────────────┘└─────────────┘ │ └───┘ └────────────┘ └────────────┘ │ └──────────────┘ │ ┌────────────┐ ┌───────┐ │ │ │ │ ┌──────────┐ │ ┌────────┐ │ ┌─┴─┐ ┌──────────┐ ┌────────┐ ┌─┴─┐┌──────────┐┌─┴─┐┌──────────┐ └─┬─┘ ┌───────┐ │ │ │ └─────────┘ │ └─┬─┘ ├─────────┬┘ └─┬─┘ ┌────┴───┴─────┐ │ └┬────────────┬┘┌───┴───┴────┐└──────────┘└─────────────┘ │ ┌──────────┐ └─────────────┘└─────────┘ │ ┌─┴─┐ └───────┘ │ │ │ │ │ │ Rxx(4.8296) │├─────────┴┐ ┌────────┐ ┌─┴─┐┌──────────┐ ┌─┴─┐┌───────────┐┌─────────┐└─────────────┘ ┌─┴─┐ └─┬─┘ └──────────────┘ │ └─┬─┘ └──────────┘ └────────┘└───┘ │ ├─────────┬┘ ┌─┴─┐┌──────────┐┌─┴─┐ ┌─┴─┐ └─┬─┘ └─────────┘ └───┘└──────────┘└─┬─┘└───────────┘ │ ├─────────┤ │ \n", + "q_4 -> 4 ────────────────────────────────────────────────────────────■──────────────────────────■─────┤ Rz(π/4) ├──┼──────────────────────────────────■───────┼────────────────────■────┤ Ry(π/2) ├────■───┤ Ry(2.8058) ├─────────────────■──┤ Rz(-2.0472) ├──┤ Ry(-π/2) ├───────────────┤1 ├┤ Rz(π/2) ├──┼─────────────────────────────────┼─────────────────────────────────────────────────┼────────────────────■───┤ Rz(1.4025) ├─┤ Ry(π) ├──┼───────────────────■─────────┼────────────────────────■────┤ Ry(-π/2) ├───┼────┤ Rz(-π) ├───┼──────┤ X ├───────┤ Ry(-π/2) ├────┤ Rz(-π) ├──┤ X ├┤ Rz(-π/4) ├┤ X ├┤ Rz(3π/4) ├───────■────────┤ Rx(π) ├───────────────────────────┤ ├───────■───────────────────────────────────────────────────■────────■──────┤ Rz(π/4) ├───────■───────┤ Rz(-0.44825) ├─┼────────────┤ Ry(3.1038) ├─┤ Rz(2.0726) ├─────────────────────────────────────────────■─────────┤ Rx(-π/2) ├───────────────────────────────────┼───────┤ X ├────────────────┼──────────────────────┤ ├────────────────────────────────────┼──────────────────────■────────────────┼──┤0 ├┤ Ry(-π/2) ├───┤ Rz(-π) ├─────────────────┤ X ├┤ Rz(-π/4) ├─────┤ X ├┤ Rz(-3π/4) ├┤ Ry(π/2) ├──────────────────┤ X ├────────┼────────────────────────■───────┼───────────────────────────────────────■──┤ Rz(π/4) ├───────────────────┤ X ├┤ Rz(-π/4) ├┤ X ├────┤ X ├───────────■────────────────────────────────────────────────────────■─────────────────■──┤ Rz(π/4) ├───■──\n", + " ┌─────────────┐┌───────────┐┌─────────────┐ └─────────┘┌─┴─┐ ┌──────────┐ ┌─────────┐ ┌─┴─┐ ┌──────────┐ └─────────┘ └────────────┘ └─────────────┘ └──────────┘ └──────────────┘└─────────┘ │ │ ┌──────────┐ ┌────────────┐ │ └────────────┘ └───────┘ │ ┌─────────────┐ │ └──────────┘ │ └────────┘ │ ┌────┴───┴────┐ └┬────────┬┘ └────────┘ └───┘└──────────┘└───┘└──────────┘ └───────┘ │ │┌─────────────┐┌────────────┐┌──────────────┐ └─────────┘ └──────────────┘ │ZZ(1.1107) ├────────────┤ ├────────────┤ └──────────┘ │ └───┘ │ ┌────────────┐ │ │ ┌──────────┐ ┌───────────┐ ┌─┴─┐ ┌──────────┐┌─┴─┐┌─────────┐ ┌─┴─┐└─┬──────────┬─┘└┬───────┬─┘ └────────┘ └───┘└──────────┘ └───┘└───────────┘└─────────┘ └───┘ │ │ ┌─────────────┐ └─────────┘ └───┘└──────────┘└───┘ └───┘ └─────────┘ \n", + "q_5 -> 5 ┤ Rz(-3.1159) ├┤ Ry(1.656) ├┤ Rz(0.58629) ├─────────────────────────────────────────────────────────────┤ X ├──┤ Ry(-π/2) ├───┤ Rz(π/2) ├──────────┤ X ├────┤ Rz(3π/4) ├─────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────■─────────────────────────────────■────┤ Rx(-π/2) ├─┤ Rz(1.7868) ├──────────────────■──────────────────────────────────────────────────■──┤ Rz(-2.4875) ├────────────■────────────────────────────────────────────■─────────────────X─┤ Ry(-1.4281) ├───┤ Rz(-π) ├───────────────────────────────────────────────────────────────────────────────────────────────────────┤0 ├┤ Rz(-1.4692) ├┤ Ry(1.3781) ├┤ Rz(-0.21319) ├─────────────────────────────────────────────────────────────────────────■────────────┤ Rx(2.6126) ├─┤ Rz(1.0897) ├──────────────────────────────────────────────────────────────────────────────────────────────────────■────────────────────────────■───┤ Rx(1.5416) ├─────┤1 ├──┤ Ry(-π/2) ├─┤ Rz(-3π/4) ├──────┤ X ├──────┤ Rz(-π/4) ├┤ X ├┤ Rz(π/4) ├─┤ X ├──┤ Rz(-π/4) ├───┤ Ry(π) ├──────────────────────────────────────────────────────────────────────────────────────────────────────────────────■────────────────────────────────■──────┤ Rx(-3.0231) ├────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────\n", + " └─────────────┘└───────────┘└─────────────┘ └───┘ └──────────┘ └─────────┘ └───┘ └──────────┘ └──────────┘ └────────────┘ └─────────────┘ └─────────────┘ └────────┘ └────────────────┘└─────────────┘└────────────┘└──────────────┘ └────────────┘ └────────────┘ └────────────┘ └───────────────┘ └──────────┘ └───────────┘ └───┘ └──────────┘└───┘└─────────┘ └───┘ └──────────┘ └───────┘ └─────────────┘ " ] }, - "execution_count": 11, + "execution_count": 13, "metadata": {}, "output_type": "execute_result" } @@ -546,6 +563,7 @@ ] }, { + "attachments": {}, "cell_type": "markdown", "id": "c698ffb1", "metadata": {}, @@ -569,6 +587,7 @@ ] }, { + "attachments": {}, "cell_type": "markdown", "id": "1c129b43", "metadata": {}, @@ -578,27 +597,28 @@ }, { "cell_type": "code", - "execution_count": 28, + "execution_count": 17, "id": "34787aad", "metadata": {}, "outputs": [ { "data": { "text/plain": [ - "" + "" ] }, - "execution_count": 28, + "execution_count": 17, "metadata": {}, "output_type": "execute_result" } ], "source": [ - "retrieved_job = ionq_device.retrieve_job(job_id=\"\")\n", + "retrieved_job = ionq_device.retrieve_job(task_id=\"\")\n", "retrieved_job" ] }, { + "attachments": {}, "cell_type": "markdown", "id": "d28a2001", "metadata": {}, @@ -608,7 +628,7 @@ }, { "cell_type": "code", - "execution_count": 29, + "execution_count": 18, "id": "764d4828", "metadata": {}, "outputs": [ @@ -618,7 +638,7 @@ "" ] }, - "execution_count": 29, + "execution_count": 18, "metadata": {}, "output_type": "execute_result" } @@ -628,6 +648,7 @@ ] }, { + "attachments": {}, "cell_type": "markdown", "id": "6ce860f0", "metadata": {}, @@ -637,18 +658,18 @@ }, { "cell_type": "code", - "execution_count": 30, + "execution_count": 19, "id": "4a8a8760", "metadata": {}, "outputs": [ { "data": { - 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", 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MzCxyCZw/fz6ef/55DBo0CDExMYW+n9FoRIcOHbB582b8/PPPeOyxx/Jd19YewPDwcKSkpMDf3x9Aye8BHPJJoaPclTnDHbMHcOhnjnmFPGe4Y/YADpvtmFeUpjyAfTM5Ks/cEY7ZA+ioPF+PdMwewJc+d8xr+i9edsweQGds3+yZyVnbN3tlcub2zR6ZHJGnoG1BSWTKyspCQEAA0tPTzb0jP6rbA2ja85dfwcvIyEBgYGCRv29h3v61RafTYciQIdi8eTO2bt1aYAH08vKCl5eX1XIPDw94eFj+YLm5udncm+jubvspyW+5o+SdP7/ZS1Omwj4fpSXT7XmA0p1Jp9PZfDuDmdSRyfRY9s7kKHl/f1wh0+3bg9Keydb2rTRnym/2kspU6DmKfU87MR37Z+s4v+TkZGRmZto8PrAg//zzD7Zv34569eqhTZs2RZ4pODgYAJCVlVXk+xIRERGpjeoKYLt27QDcOm7udrGxsRbrFNbdnvpl586dAG6dI5CIiIiotFNdAezYsSNq1KiBJUuWWBwMmZ6ejmnTpsHT0xMDBw40L79w4QKOHj2a71vGubm5WLRoETw8PCzud7uDBw9afNLIZNu2bZg+fTo8PDzQp0+f4gcjIiIiUgnVHQPo7u6OefPmITo6Gm3btrW4FNyZM2cwY8YMiz1xY8eOxcKFC7FgwQKbl3Bbvnw5Ll++jMcee6zAT83OnDkTf/zxB9q0aYPw8HB4eHjg8OHDWLt2LRRFwezZs1GzZk07JCYiIiJyLNUVQABo3749tmzZgsmTJ2Pp0qXIzc1FgwYNMH36dPTr169I36uwH/7o2bMn0tLSsH//fqxbtw45OTmoVKkS+vfvj5EjRyIqKqrYeYiIiIjURJUFEACioqKwevXqO64XExNT4Gld8p4/qCC9evVCr169CjseERERUamlumMAiYiIiMi+WACJiIiINIYFkIiIiEhjWACJiIiINIYFkIiIiEhjWACJiIiINIYFkIiIiEhjWACJiIiINIYFkIiIiEhjWACJiIiINIYFkIiIiEhjWACJiIiINIYFkIiIiEhjWACJiIiINIYFkIiIiEhjWACJiIiINIYFkIiIiEhjWACJiIiINIYFkIiIiEhjWACJiIiINIYFkIiIiEhjWACJiIiINIYFkIiIiEhjWACJiIiINIYFkIiIiEhjWACJiIiINIYFkIiIiEhjWACJiIiINIYFkIiIiEhjWACJiIiINIYFkIiIiEhjWACJiIiINIYFkIiIiEhjWACJiIiINIYFkIiIiEhjil0A4+Pjcfbs2QLXSUxMRHx8fHEfgoiIiIjsoNgFsH379oiJiSlwnW+//Rbt27cv7kMQERERkR0UuwCKyB3XMRqNUBSluA9BRERERHZg12MAExISEBAQYM+HICIiIqIici/Kys8++6zF17/99htOnz5ttZ7BYDAf//fQQw/d1YBEREREVLKKVADzHvOnKAr27duHffv22VxXURQ0a9YMH3/88d3MR0REREQlrEgF8NSpUwBuHf9Xo0YNjBw5Eq+++qrVem5ubggMDISvr2/JTElEREREJaZIBTAiIsL8/xcsWIDGjRtbLCMiIiIi9StSAcxr0KBBJTkHERERETlIsQugya5du7B7926kpaXBYDBY3a4oCiZOnHi3D0NEREREJaTYBTA1NRWPPvootm7dWuA5AVkAiYiIiNSl2AVw1KhR2LJlCx588EEMGjQIVapUgbv7Xe9QJCIiIiI7K3ZjW7lyJaKiorBhwwZe7YOIiIioFCn2lUBu3LiBtm3bsvwRERERlTLFLoCNGjWyeRUQIiIiIlK3YhfAyZMnY/ny5dixY0dJzkNEREREdlbsYwCTk5Px8MMPo127dnjqqafQpEkT+Pv721x34MCBxR6QiIiIiEpWsQvg4MGDoSgKRAQxMTGIiYmxOh5QRKAoCgsgERERkYoUuwAuWLCgJOcgIiIiIgfhpeCIiIiINKbYHwIhIiIiotKp2HsAz549W+h1q1atWtyHISIiIqISVuwCWK1atUKdBFpRFOj1+uI+DBERERGVsGIXwIEDB9osgOnp6di/fz9OnTqFdu3aoVq1anczHxERERGVsGIXwJiYmHxvExHMnDkTH3zwAebPn1/chyAiIiIiO7DLh0AURcHrr7+O+vXr44033rDHQxARERFRMdn1U8BNmzZFXFycPR+CiIiIiIrIrgXwxIkT/AAIERERkcoU+xjA/BiNRiQlJSEmJga///47OnbsWNIPQURERER3odgFUKfTFXgaGBFBYGAgZs6cWdyHICIiIiI7KHYBbNu2rc0CqNPpEBgYiGbNmuGZZ55BhQoV7mpAIiIiIipZxS6AmzZtKsExiIiIiMhReC1gIiIiIo0pkQ+BbN26Ffv27UNGRgb8/f3RqFEjtG7duiS+NRERERGVsLsqgNu2bcMzzzyDf//9F8CtD36YjgusXbs2FixYgJYtW979lERERERUYopdAA8fPowuXbrg+vXr6Ny5M9q3b4/KlSsjOTkZGzduxNq1axEdHY0dO3bg3nvvLcmZiYiIiOguFLsAvv3228jJycGqVavQtWtXi9vefPNNrFmzBo888gjefvtt/PDDD3c9KBERERGVjGJ/CGTTpk3o3bu3Vfkz6dq1K3r37o2NGzcWezgiIiIiKnnFLoDp6emoXr16getUr14d6enpxfr+u3fvRrdu3VCuXDn4+vqiRYsWWLZsWaHvHxMTA0VR8v2X32ls7vZxiYiIiNSu2G8Bh4aGYseOHQWus3PnToSGhhb5e2/cuBHR0dHw9vZG//794efnh59//hn9+vVDYmIiRo8eXejv1bNnTzRq1MhqebVq1ez6uERERERqVewC+Mgjj2DWrFmYOHEixo8fD29vb/NtN2/exPvvv4+NGzdixIgRRfq+er0eQ4YMgU6nQ3x8vLm8TZo0CVFRURg3bhx69+6NiIiIQn2/Rx99FIMHD3b44xIRERGpVbHfAp44cSKqV6+OadOmoWrVqujevTuee+45dO/eHREREXjnnXdQvXp1TJw4sUjfNy4uDidOnMCTTz5psecuICAA48aNQ05ODhYuXFjcsVX3uERERESOVuw9gOXLl8eOHTswZswY/PDDD1i1apX5Nm9vbzzzzDOYPn06goKCivR9TcfmdenSxeq26OhoAMDmzZsL/f327t2LK1euQK/Xo1q1aujUqRPKly9vl8fNzs5Gdna2+euMjAwAQG5uLnJzcwHculaym5sbDAYDjEajeV3Tcr1eDxExL3dzc4NOp8t3uaPk5uZCURS4u7vnO3tJZHLUxWlMz4e9MwEeds8C/JcHsHcmx+QxGo0wGAzmr+2XyTF5AMdkKqFz+9+RXq+Hu7u73TM5St7tmz0zOWv7Zq9Mzty+2SeTc7dvJZGpKO5qaxEcHIxvvvkGc+fOxdGjR81XAqlXrx48PIr3HzIhIQHArRNJ365SpUooW7aseZ3C+Oyzzyy+LlOmDCZPnow333yzxB/3/fffx9SpU62Wr127Fj4+PgCAqlWronHjxjhw4ADOnj1rXqdu3bqoV68edu3ahcuXL5uXN2rUCBEREYiPj8e1a9fMy1u2bIkKFSoUOE9JWrVqFUJCQtCqVSskJCTg2LFj5ttKMhPgmEymFyz2zgT0tHsWABYvwOybyTF5EhMTsW/fPvPX9svkmDyAYzIBHRwRBfHx8ejQoYPdMznKqlWr4OfnZ/dMgGMymbYH9s7kjO2bfTM5Jk9KSgq2b99u/rokMxXlcxeKWNb5O3rvvfeQlZWFqVOn5lvycnJyMHXqVPj5+eGtt94qyrdHly5dsG7dOiQkJKBWrVpWt4eFhSEzM/OOny7evHkzDh48iOjoaFSpUgWpqamIi4vD2LFjkZSUhM8++wyvvPJKiT6urT2A4eHhSElJgb+/P4CS3wM45JMC/zOUmDnDHbMHcOhnjnmFPGe4Y/YADpvtmFeUpjyAfTM5Ks/cEY7ZA+ioPF+PdMwewJc+d8wewC9edsweQGds3+yZyVnbN3tlcub2zR6ZHJGnoG1BSWTKyspCQEAA0tPTzb0jP0XaWqxfvx6TJk3CBx98UOAePk9PT5QvXx5vvPEGmjdvjvbt2xflYUpEu3bt0K5dO/PXYWFhGDBgAJo0aYKmTZtiypQpeOmll+DuXnIbTC8vL3h5eVkt9/DwsPrv5ebm9v9vCVjKb56SnLM48s6f3+ylKVNhn4/SksnW72NpzqTT6Wy+ncFM6shkeix7Z3KUvL8/rpDp9u1Bac9ka/tWmjPlN3tJZSr0HEVZ+dtvv0VgYCBefvnlO647fPhwBAUFYcGCBUUaKCAgAADy3dOWkZFhXqc46tevjzZt2iA1NRVHjhxx2OMSERERqUWRCuC2bdvQqVMnm3u5bufl5YVOnTph69atRRrIdAyerePtkpOTkZmZafM4vaIIDg4GAGRlZTn0cYmIiIjUoEgF8Pz586hRo0ah169evTouXLhQpIFMb9uuXbvW6rbY2FiLdYrDYDBgz549AGBxkLG9H5eIiIhILYpUAHU6ncXHse8kNze3yB9L7tixI2rUqIElS5ZYfBomPT0d06ZNg6enJwYOHGhefuHCBRw9etTqrdu//vrL6nsbDAa89dZb+Pfff9G+fXtUrly52I9LREREVFoV6ejH0NBQHDp0qNDrHzp0CGFhYUUbyN0d8+bNQ3R0NNq2bWtxSbYzZ85gxowZFpdxGzt2LBYuXIgFCxZYXPGjadOmaNiwIRo2bIiwsDCkpqZi8+bNOH78OKpUqYJ58+bd1eMSERERlVZF2j33wAMPIC4uDqdPn77juqdPn0ZcXBzatm1b5KHat2+PLVu2oHXr1li6dCm++OILVKxYET/88EOhr8c7evRo+Pn5Yd26dfjoo4+wZMkSlClTBhMmTMCBAwdsvpVdEo9LREREpHZF2gM4fPhwLFiwAL1798aaNWvMH6a43ZUrV9CnT59b56V66aViDRYVFYXVq1ffcb2YmBjExMRYLZ8xY4ZdH5eIiIiotCpSAWzSpAlGjhyJTz75BPfeey9efPFFtG/fHlWqVAEAJCUlYcOGDfjqq69w+fJljBo1Ck2aNLHL4ERERERUPEU+A+LMmTPh7e2NDz/8EO+99x7ee+89i9tFBG5ubhg7dizefffdEhuUiIiIiEpGkQugoiiYNm0annvuOSxYsADbtm1DcnIygFvXzG3dujUGDx6MmjVrlviwRERERHT3in0NlJo1a3IPHxEREVEp5JgrUxMRERGRarAAEhEREWkMCyARERGRxrAAEhEREWkMCyARERGRxrAAEhEREWkMCyARERGRxrAAEhEREWkMCyARERGRxrAAEhEREWkMCyARERGRxrAAEhEREWkMCyARERGRxrAAEhEREWkMCyARERGRxrAAEhEREWkMCyARERGRxrAAEhEREWkMCyARERGRxrAAEhEREWkMCyARERGRxrAAEhEREWkMCyARERGRxrAAEhEREWkMCyARERGRxrAAEhEREWkMCyARERGRxrAAEhEREWkMCyARERGRxrAAEhEREWkMCyARERGRxrAAEhEREWkMCyARERGRxrAAEhEREWkMCyARERGRxrAAEhEREWkMCyARERGRxrAAEhEREWkMCyARERGRxrAAEhEREWkMCyARERGRxrAAEhEREWkMCyARERGRxrAAEhEREWkMCyARERGRxrAAEhEREWkMCyARERGRxrAAEhEREWkMCyARERGRxrAAEhEREWkMCyARERGRxrAAEhEREWkMCyARERGRxrAAEhEREWkMCyARERGRxrAAEhEREWkMCyARERGRxrAAEhEREWkMCyARERGRxrAAEhEREWkMCyARERGRxrAAEhEREWkMCyARERGRxrAAEhEREWkMCyARERGRxrAAEhEREWkMCyARERGRxrAAEhEREWmMagvg7t270a1bN5QrVw6+vr5o0aIFli1bVqj7ighWr16Nl156CQ0bNkRAQAB8fHwQGRmJadOm4ebNmzbvpyhKvv8GDx5cgumIiIiInMfd2QPYsnHjRkRHR8Pb2xv9+/eHn58ffv75Z/Tr1w+JiYkYPXp0gffPzs5Gt27d4OXlhQcffBDR0dG4efMmYmNjMX78ePz222/YtGkTfHx8rO4bERFhs+w1atSohNIREREROZfqCqBer8eQIUOg0+kQHx9vLl6TJk1CVFQUxo0bh969eyMiIiLf7+Hm5oZ3330Xw4YNQ2BgoHl5bm4uHn/8caxYsQKzZ8/GG2+8YXXfatWqYcqUKSUdi4iIiEg1VPcWcFxcHE6cOIEnn3zSYq9bQEAAxo0bh5ycHCxcuLDA7+Hh4YHx48dblD/T8rFjxwIANm/eXOKzExEREZUGqtsDuGnTJgBAly5drG6Ljo4GcHflzcPDAwDg7m47elpaGr766iukpKQgKCgIrVu3RoMGDYr9eERERERqo7oCmJCQAACoXbu21W2VKlVC2bJlzesUxzfffAPAdsEEgP3792Po0KEWy7p27YqFCxeiQoUKBX7v7OxsZGdnm7/OyMgAcOut59zcXACATqeDm5sbDAYDjEajeV3Tcr1eDxExL3dzc4NOp8t3uaPk5uZCURS4u7vnO3tJZHLUTmnT82HvTICH3bMA/+UB7J3JMXmMRiMMBoP5a/tlckwewDGZHLVJ1+v1cHd3t3smR8m7fbNnJmdt3+yVyZnbN/tkcu72rSQyFYXqCmB6ejqAW2/52uLv729ep6hWr16NuXPn4p577sFzzz1ndfvo0aPx+OOPo06dOvD09MShQ4fwzjvvYPXq1ejevTu2b9/+/7/Etr3//vuYOnWq1fK1a9eaP3BStWpVNG7cGAcOHMDZs2fN69StWxf16tXDrl27cPnyZfPyRo0aISIiAvHx8bh27Zp5ecuWLe9YSEvSqlWrEBISglatWiEhIQHHjh0z31aSmQDHZFq1ahUA2D0T0NPuWYD/8gD2zuSYPImJidi3b5/5a/tlckwewDGZgA6OiIL4+Hh06NDB7pkcZdWqVfDz87N7JsAxmUzbA3tncsb2zb6ZHJMnJSUF27dvN39dkplCQ0MLPYcilnXe6bp06YJ169YhISEBtWrVsro9LCwMmZmZRS6Bu3fvRseOHeHu7o4///wT9evXL9T9jEYjOnTogM2bN+Pnn3/GY489lu+6tvYAhoeHIyUlBf7+/gBKfg/gkE8K+1/g7swZ7pg9gEM/c8wr5DnDHbMHcNhsx7yiNOUB7JvJUXnmjnDMHkBH5fl6pGP2AL70uWNe03/xsmP2ADpj+2bPTM7avtkrkzO3b/bI5Ig8BW0LSiJTVlYWAgICkJ6ebu4d+VHdHkDTnr/8Cl5GRobVhzvuZM+ePejSpQt0Oh1iY2MLXf6AW/9BhwwZgs2bN2Pr1q0FFkAvLy94eXlZLffw8DAfe2ji5uZmc29ifscm5rfcUfLOn9/spSlTYZ+P0pLp9jxA6c6k0+lsvp3BTOrIZHose2dylLy/P66Q6fbtQWnPZGv7Vpoz5Td7SWUq9BzFvqedmI79s3WcX3JyMjIzM20eH5ifPXv2oHPnzjAajYiNjUWzZs2KPFNwcDAAICsrq8j3JSIiIlIb1RXAdu3aAbh13NztYmNjLda5E1P5MxgMWLNmDZo3b16smXbu3Ang1jkCiYiIiEo71RXAjh07okaNGliyZInFwZDp6emYNm0aPD09MXDgQPPyCxcu4OjRo1ZvGf/111/o3Lkz9Ho9Vq9e/f8fMMjfwYMHLT5pZLJt2zZMnz4dHh4e6NOnz92FIyIiIlIB1R0D6O7ujnnz5iE6Ohpt27a1uBTcmTNnMGPGDIs9cWPHjsXChQuxYMEC8yXcUlNT0blzZ6SlpaFr165Yt24d1q1bZ/E45cqVw8iRI81fz5w5E3/88QfatGmD8PBweHh44PDhw1i7di0URcHs2bNRs2ZNB/wXICIiIrIv1RVAAGjfvj22bNmCyZMnY+nSpcjNzUWDBg0wffp09OvX7473z8jIwNWrVwEAa9aswZo1a6zWiYiIsCiAPXv2RFpaGvbv349169YhJycHlSpVQv/+/TFy5EhERUWVWD4iIiIiZ1JlAQSAqKgorF69+o7rxcTEICYmxmJZtWrVUNSz2/Tq1Qu9evUq0n2IiIiISiPVHQNIRERERPbFAkhERESkMSyARERERBrDAkhERESkMSyARERERBrDAkhERESkMSyARERERBrDAkhERESkMSyARERERBrDAkhERESkMSyARERERBrDAkhERESkMSyARERERBrDAkhERESkMSyARERERBrDAkhERESkMSyARERERBrDAkhERESkMSyARERERBrDAkhERESkMSyARERERBrDAkhERESkMSyARERERBrDAkhERESkMSyARERERBrDAkhERESkMSyARERERBrDAkhERESkMSyARERERBrDAkhERESkMSyARERERBrDAkhERESkMSyARERERBrDAkhERESkMSyARERERBrDAkhERESkMSyARERERBrDAkhERESkMSyARERERBrDAkhERESkMSyARERERBrDAkhERESkMSyARERERBrDAkhERESkMSyARERERBrDAkhERESkMSyARERERBrDAkhERESkMSyARERERBrDAkhERESkMSyARERERBrDAkhERESkMSyARERERBrDAkhERESkMSyARERERBrDAkhERESkMSyARERERBrDAkhERESkMSyARERERBrDAkhERESkMSyARERERBrDAkhERESkMSyARERERBrDAkhERESkMSyARERERBrDAkhERESkMSyARERERBrDAkhERESkMSyARERERBrDAkhERESkMSyARERERBrDAkhERESkMSyARERERBqj2gK4e/dudOvWDeXKlYOvry9atGiBZcuWFel7ZGdn4+2330bt2rXh7e2N0NBQvPDCC7h06VK+9/nuu+8QFRUFX19fBAYGonv37vj777/vNg4RERGRaqiyAG7cuBGtW7fGli1b0LdvX7z44otITk5Gv379MHPmzEJ9D6PRiJ49e2Ly5MkIDg7GyJEj0bJlS8ybNw8tW7bE5cuXre7z3nvv4emnn8alS5fw4osvok+fPoiPj0erVq2wdevWko5JRERE5BTuzh7gdnq9HkOGDIFOp0N8fDwaNWoEAJg0aRKioqIwbtw49O7dGxEREQV+n4ULFyI2NhZPPPEEvvvuOyiKAgD48ssv8dJLL2HChAmYO3euef2EhARMmTIFderUwa5duxAQEAAAGDZsGFq0aIEhQ4bg0KFD0OlU2ZmJiIiICk11bSYuLg4nTpzAk08+aS5/ABAQEIBx48YhJycHCxcuvOP3+frrrwEA77//vrn8AcDQoUNRo0YNfPfdd7hx44Z5+YIFC6DX6zF+/Hhz+QOARo0a4YknnsCRI0ewZcuWEkhIRERE5Fyq2wO4adMmAECXLl2sbouOjgYAbN68ucDvcfPmTezcuRN169a12lOoKAo6d+6MuXPnYs+ePXjggQcK9bgxMTHYvHkz2rZtm+/jZmdnIzs72/x1eno6ACA1NRW5ubkAAJ1OBzc3NxgMBhiNRvO6puV6vR4iYl7u5uYGnU6X7/KcmwX+pygxV67kQlEUuLu75zt7SWTKuemY1yRXrtx6PuydKeemhwPS/JcHsG8mR+VJSzPCYDCYv7ZXJkflyci4dViKvTPl3HTMJj01VQ93d3e7Z3LG9s2emZy1fbNXJmdu3+yRyRF5CtoWlESmrKwsALB4nvIlKtO7d28BIHv27LF5e9myZSU8PLzA73Ho0CEBIN27d7d5+4wZMwSAzJ8/37wsODhYypYta3P9PXv2CAAZMGBAgY87efJkAcB//Md//Md//Md//Oe0f4mJiQX2FRER1e0BNO01y/s2bF7+/v7mde7me+Rdz/T/K1SoUOj1bRk7dixGjRpl/tpoNCI1NRXly5e3eBvamTIyMhAeHo7ExERzrtKMedSNedSNedSNedRNjXlEBNeuXUNoaOgd11VdASzNvLy84OXlZbGsXLlyzhnmDvz9/VXzA1sSmEfdmEfdmEfdmEfd1JYnv51ft1Pdh0BMg+e3ty0jI+OO4QrzPfKuZ/r/RVmfiIiIqLRSXQGsXbs2gFunZbldcnIyMjMzzevkp0aNGtDpdDa/R97vnff71K5dG5mZmUhOTi7U+kRERESlleoKYLt27QAAa9eutbotNjbWYp38lClTBlFRUTh27BjOnDljcZuIYN26dfD19UXTpk1L9HFLAy8vL0yePNnqrerSinnUjXnUjXnUjXnUrbTnUUQK81lhx9Hr9ahbty6SkpKwY8cO87kA09PTERUVhdOnT+PYsWOoVq0aAODChQtIT09H5cqVLd6iXbBgAZ599tl8TwT9wgsvWJwI+vjx46hfvz5q1KhhcSLoffv2oUWLFqhRowZPBE1EREQuQXUFELh1Kbjo6Gh4e3ujf//+8PPzw88//4wzZ85gxowZGD16tHndwYMHY+HChViwYAEGDx5sXm40GtGtWzfExsaiRYsWaNeuHf7991/88ssvqFatGnbu3ImQkBCLx33vvfcwYcIERERE4PHHH8e1a9fwww8/ICcnBxs2bEDr1q0d9Z+AiIiIyG5UuTurffv22LJlC1q3bo2lS5fiiy++QMWKFfHDDz9YlL+C6HQ6/P7775gyZQouX76Mjz/+GFu3bsVzzz2H7du3W5U/ABg/fjwWL16MkJAQfPHFF1i2bBkeeOABbNu2jeWPiIiIXIYq9wASERERkf2ocg8gEREREdkPCyARERGRxrAAEhEREWkMCyARERGRxrAAEoBbJ8gGAIPBYLWsNHK1PK6Gzw8RkXPxU8BkRUTMJ852Ba6Wx9Xw+SFn4M8daZ27swcg51u5ciW2b9+O7du3IzQ0FPfeey/q1KmDevXqoUaNGvDx8XH2iEXiann0ej3c3Nxc5o8Vnx9ytGvXrsHPzw83b96EwWCAr68vny/SPO4B1LDc3FxMmDABH374Iby8vJCbmwsvLy/k5OTA3d0d9957L7p27YpevXqZr5us5lfNrpbndkajESICNzc3Z49SLHx+SgcRgdFoLPU5AODixYv4+OOPERcXh8uXL6N27dqoXr067rvvPkRFRaFBgwal6gWH0Wg0Pzel5feiIK6Wp9QR0qyFCxdKmTJlpFevXrJ//35JSkqSDRs2yMKFC+WVV16R+vXri06nk2rVqsmnn34qubm5zh65QK6Yp3HjxjJ//nxJSUmxuE2v14vBYHDSZMXD50f9rl+/bvG1wWAQvV7vpGnuzqZNm6RJkyaiKIpUr15d6tWrJ3Xr1hVvb29RFEVq1qwpL7/8ssTHxzt71ELJzMy0+Fqv15fa50bE9fKURiyAGtaiRQtp06aNnDhxwuq2jIwM2bt3r8ycOVPq1KkjiqLI8OHDnTBl4blantatW4uiKKIoigQFBcmAAQNkxYoVkpOTY7Fe3qL06aefytdff63K8sHnR93Pj4hIdHS0REdHyy+//GJVBktbqe3QoYNUqVJFFi1aJAaDQZKTk+Xw4cOyYcMGmTJlijRp0kTc3NykRo0a8vXXXzt73DuKjIyUe+65R+bNmyfXrl2zuC03N9fmc3Pt2jXVvpBytTz//vuvHD582Or3Rs1YADUqJSVFwsLCpH///uZlBoNBjEajxXp6vV7++usv6dixoyiKIosXL3b0qIXiankuXbok5cqVk/r168vTTz8tvr6+5rJRs2ZNGTVqlOzYscPiPocOHZKQkBCpVq2ak6bOH58fdT8/IiLnzp0zZ1AURcLDw2X48OGyefNmq3Vv3rwpIiJHjhyRESNGyPr16x09boESExPFzc1N3n77bZu35+TkyMmTJ+WLL76QWrVqiaIo8sEHHzh4ysJLSkqyeG4URZGePXvKihUrrNbN+9w888wz8t133zl63DtytTwiIk2aNJEKFSrI8OHDZcWKFXLu3DmrF4MiYrHNO3z4sJw7d86RY1pgAdSoixcvSvPmzeX++++X3Nxcm7vf8/6gnjhxQgICAuSZZ55x9KiF4mp54uLixMvLS1577TUREcnKypIlS5ZI586dLTaazZo1k/fff18uXLggCxcuFEVR5IsvvnDy9Nb4/Kj7+RERmT9/viiKIk8//bT06tXLIkdkZKS888478s8//1jcZ/bs2aIoinz00UdOmtq2X3/9Vdzd3WXevHkiIvnuuczJyZH4+Hhp1KiReHp6yqFDhxw5ZqGZfnaeffZZGTVqlERERJifm4CAAHnppZdkz549FveZM2eOKIoiH3/8sXOGLoCr5Tl//rwoiiJlypQRDw8P8+/MuHHj5M8//5SUlBSrn8F//vlHoqOj5c0333TS1CyAmvb888/bfOVrNBrNP6ymP8q5ubnSpk0badasmWRnZzt81sJwpTy///67KIoin376qdVtycnJMnPmTImMjDRvND09PaVixYqiKIrV2ylqwedH3c/P+PHjRVEUOXLkiIjc2ss5e/ZsadasmUUZ7NChg8ybN09OnjwpAwYMEA8PD9Vl2rNnj5QrV06ef/55Ebnz8WXr1q0TRVEkJibGUSMWydSpU0VRFNm/f7+IiKSmpsqyZcukT58+Uq5cOfNzU6NGDXnvvffk2LFjMnDgQHF3d1fdcyPienl+/PFHURRFhg4dKj/99JMMHDhQatasKYqiiLe3t7Rv314+/vhj2bdvn6SlpYmIyNy5c0VRFPnss8+cNjcLoIYlJSVJu3btRFEUeeihh2T58uWSnp5usY7pj+/BgwelQYMG8sgjjzhj1EJxpTxnzpyRDz/8UA4ePGheZuu4mP3798v48eMlNDTU/DaKWvH5Ue/zc+PGDRk1apTodDo5c+aMVY7jx4/LhAkTpHr16uY/zqY/1N26dXPS1Pm7efOmtG3bVhRFkQULFljcZjAYzPlMx5Pt2rVLQkJC5I033nD0qHeUnZ1tLucJCQlWz82ZM2dk9uzZ0qFDB9HpdBZlXY3PjavlERGZMWOGKIoiW7ZsEZFbH3DZvXu3fPzxx9KzZ0/zi7+goCDp27evzJs3T7p16yZubm5OLbQsgBoXHx8vLVq0EEVRxN/fX3r06CEzZ86UrVu3mv8Ynz17VgYOHCg6nU6WL1/u5IkL5kp5bt68me8xJLcfCP3hhx+KoiiqziPC50eteYxGo2zbtk2++uor8x4Kg8Egubm5Vsdp/vnnn/LCCy9I2bJlRVEUWblypTNGzpepUOzZs0fuu+8+URRFunbtKitWrMj3AP158+aJm5ub/P77744ctdBOnTolv//+u8VzY2uP5t69e+Wdd96R8PBwVT43Jq6UR6/Xm3+/d+/ebfX7kpqaKhs2bJDJkydLu3btxN/fX9zc3ERRFOnevbuTpr6FBZBERGTx4sXStm1bcXd3Nx/LEBoaKk2aNJHAwEDx8vKSIUOGOHvMQnO1PLaYNjQXLlyQLl26SGBgoJMnKrxFixa5xPNz+8be1m2l6fm5efOmzUy2ymCnTp3Ez8/PkeMVWWxsrMVb2C1btpQJEybIpk2bJDMzU44dOyY//PCDhIWFSa1atZw9boHyO47RaDSKXq8vdc+Nq+U5deqUudDmPawlr7Nnz8rKlSvNe6edXWhZADUu76uuK1euyMaNG2XSpEnSsmVLCQkJkfr160unTp3kiy++KBUfb3e1PIWxbds2URRFHnvsMWePYqWggpSamlrqnp+C8uRHzc9PUZl+v5YvXy5+fn7y3HPPOXmiwlmyZIn5j67pn5+fn/j7+5sP2P/555+dPeZdMRWO5cuXi7+/v+qfm/xKkklpynOnF4J5z3iQnZ0tnTt3Fn9/f0eNly9eCYTylZGRgfT0dISHhzt7lBLhanlMDAYDtm3bhoiICFStWtXZ45jJ/1/FIyMjA1euXMGxY8dQqVIlNGzYEDqdzmp9tT8/+eWJjIy0uoqB5LmCiVqfn7sxY8YMjBkzBn/++Sdat27t7HHyZTAYLK5ocvToUcTGxiIuLg7Xr19HxYoVUaVKFbz44ouoVq2a8wYtQR9//DFGjx6N+Ph4tGnTxtnjWLj9+SgMNecpCtM2ITY2Fo899hj69OmDmJgYp87EAqhhUsBltoxGo/mPdN7/r2ZaylMaGI1GbNq0CW+99RaOHz+OjIwMAEBwcDA6duyInj17olOnTggODra4n1pzF5SnU6dO6NmzJzp06ICQkBAA6s1xu+LMef36dezevRvt2rWz01TFk9/vtq2MmZmZKFu2rKNGK5bibqsSEhJQu3ZtO0x0944dO4a9e/ciNTUV9evXR1hYGMqVK4dy5crB3d3d5n3UnKeofv31V7z++utYunSp+ZKXzsICqCFHjx5FamoqGjZsaLHhM/0IFLQXQ420nicvNWZbsWIFhg0bhhs3bqBbt24ICwvD4cOHcerUKfz777/Izs5GjRo1MGzYMLzwwguq/2PsanlsUePPUXHIrcObbJanvHuhStOLwfzy5GU0GqEoChRFUd1zeerUKcyZMwcfffQR8taO4OBgtGzZEg899BA6duxoLnp511FjHuDWz5JOpyvyXBcuXEDlypXtNFXhsQBqSJcuXXD+/Hl06NABrVq1QuPGjVGzZk2LV123l42TJ0+iRo0aTpn3TphH3XlatmyJtLQ0LFq0yOKVbmJiInbu3Il169bh999/x6VLl9C+fXvMmjUL9957rxMnLpir5QGAVatWISwsDPXq1YOXl5d5eWFedKjNggULEBERgRYtWsDHx8e8PG8pKk1cLc+AAQPwyy+/oGPHjnjssceQkZGBkydP4ujRo9i7dy8uX76MWrVq4eWXX8bw4cPh5uamytJni9FohIgU6e1tVWSz29GFpCqmyzx5e3uLu7u7+Pj4SKtWrWTcuHHyxx9/SGJiotV9Dh06JG3atJFhw4Y5YeKCMY+68yQlJYm3t7dMnDjRvMzWNTz37NkjAwYMEEVRpEePHpKSklKsD1rYm6vlEbl1vjVfX19p166djBkzRn777Tc5ffq01bymT2WK3Lqk39GjR50xboHOnj0rOp1O6tWrJ3379pU5c+bIwYMHrbKYPs0scuuE3Xv37hWR4n24x55cLc/p06dFp9PJyy+/bHVbUlKSrFmzRt58803zeSa7devm1EukFcarr74qX375paSmplosL03XzGYB1IilS5eKoijyyiuvyKpVq+TZZ581/7IFBwdLt27d5IMPPpD4+Hi5dOmSiIh88803qr10FfOoO8/mzZvF399fxo4dKyL/Xc9TxPan/0aMGCGKoshPP/3k0DkLy9XyiIj873//E0VRpEKFCqLT6SQwMFA6d+4s7733nsTFxcnFixet7vP1119LWFiYrFmzxgkT5++DDz4QRVGkWrVq5pMH16tXT4YMGSJLliyR06dPW93n888/F0VR5Mcff3TCxAVztTyfffaZ+Pr6yurVq0Xk1iX4bv+dMRgMsn37dnn00UdFURR58cUXbZ6HUg3Onj1r/jR5hQoVZPDgwbJ69Wqrcxnq9XrzuULPnDkjv/76q6SkpDhjZJtYADXCtEHZsGGDiIhcvnxZ/v77b/nyyy+lV69eEhISIoqiSEREhDz99NMya9Ys6dy5s+h0OsnMzHTy9NaYR915bty4IZUqVZLmzZtbzZd3g27ae3HmzBkJCAiQV155RZUbfFfLIyLy5JNPiru7u/z000/y3XffSZ8+faRSpUqiKIqEhYVJnz59ZPbs2bJz5065fv26GAwG6devnyiKorqfucGDB4ubm5ts2rRJtm/fLq+++qrUqlVLFEURLy8viYqKkjFjxsjKlSvN52p76qmnVPv742p5PvzwQylTpoz5hUPeyzsajUar35FHHnlEvL295ezZsw6ds7A+++wzURRFmjZtKmXKlDGXwdq1a8uYMWNk9+7dVvf56KOPRFEUmT9/vhMmto0FUANyc3Plo48+ksqVK8uxY8csbtPr9ZKcnCx//vmnTJs2Tdq2bSu+vr7i7e1tfhtLbZhH3XlM3n33XVEURdq0aSPr1q2z+Ycp76XfwsLCzNduVSNXypOamiqdO3eW4OBgEbm19+XSpUuyfft2mTFjhvnEu25ublKvXj0ZPny4TJkyRQIDA+Whhx5y8vSWrl69Kg8//LDFiYJzc3Pl3Llz8tNPP8lTTz1lfgFVrlw56datmwwbNkz8/PxUl0XE9fKIiPz111+iKIo8+eSTVrflLX+mPesxMTHi4+Mj3377rcNmLIpXXnlFFEUx74lduHChtG/f3uI8ky1atJAPP/zQXGIHDx6sumsZswBqRFpamqxdu1auXLkiIraPEbl586acPn1aNmzYYP5h/uOPPxw9aqEwj7rziNw6XqxXr16iKIrUqlVL3nrrLYmLi5OkpCSrS6h9/PHHotPpVHspLhHXynPx4kXp2bOnPProo1ZvW+Xk5EhiYqKsXbtWxo0bJ02bNhVPT0/zno4VK1Y4aWrbrl69Ki+99JIMGDDAYs+Syc2bN+XYsWPy5ZdfSteuXcXHx8d8KS5nX4nBFlfLYzAYJCcnR5577jlRFEWio6Nl3bp1kpWVZbWeaQ/6vHnzRKfTyfr1650xcoEyMjKkT58+oiiKZGRkWNx27tw5mT59utSvX99cBL29vaVt27bi5eWluoLOTwGTldTUVPTp0wd//fUX0tLSnD3OXWMe55o/fz4+++wzHDp0CMHBwYiKikJkZCSCg4NRuXJl7Ny5E/PmzcM999yDnTt3OnvcO3KVPGfPnsXly5cRGRkJd3f3fM+Vl5qaio0bN+Ktt97CjRs3VPkzd/HiRaSmpqJOnTr5fnrUaDTCYDDgzz//xHPPPYerV6+qMgvgenmAW+f/GzZsGDZu3IiwsDA88sgj6NChAxo2bIjq1aubz3aQlJSEZ599Fn///TcuX77s5Kmt5eTkYPHixTh27BgmTpyIsmXLQq/XQ6fTWZymZ//+/YiJicHSpUuRnJwMAFi5ciW6devmrNGtObV+ksMU5jgk00G5a9asEUVRZODAgfYeq9jyXisy72V28mIe5zLNm5OTI3v27JEPPvhAunbtKpUqVTIf2G761717d9mzZ4+TJy6Yq+UpijVr1oivr69q39IuDNPv1Jo1a0rVZezyU1rzzJ07Vxo1aiQ6nU78/f0lKipK+vfvL6NGjZK33npL6tWrJ35+fvL+++87e9R83bhxQy5dumT1QRaj0Wh1doCrV69KZGSkBAQEOHDCwrF92m1yOYU535Dp1Utubi6aNGmCV1991d5jFVve8y3lfdWV98SczONcpnk9PDxw//33o0mTJujXrx/Onj2L1NRUnDt3Dunp6ejSpQvuuecei3OdqZGr5dHr9ea9Lnc6t9yGDRtw/fp1PP/8844csUSZsq1fvx6ZmZkYMmSIkyfKX96TVed3suHSlAf4L9MLL7yAdu3aYevWrVi/fj127NiB3bt3AwC8vb3h4+ODWbNm4bHHHnPyxPnz9vaGt7e31XJFUcy/Uzk5OfD09MSuXbuQmJiI3r17O3rMO+JbwGTl5s2b+Pfff3Hfffc5exQrN27cwLZt27B+/Xp4eHhAURRUr14dDzzwAGrWrGnzPszjfKKGk56WIFfJk5ubCw8PD/PXIgKj0WjxgiQrKwuffvoptm3bhpUrVzpjzBKTnZ2NJUuWIC4uDosWLXL2OAXKyMiAv7+/+Wtbz01pynM7o9GItLQ0ZGVlISMjA0eOHEHFihVx3333ITAw0NnjlZhRo0bhk08+wbZt29CiRQtnj2OBBZBKjaNHj+Ldd9/FkiVLAAA+Pj64fv06ACAgIAAdO3ZEv379EB0dbbHhVCtXy5Obmws3N7cCL1eVtziZ9gio9XJcrpbH5OTJk1i1ahUOHz4MT09P+Pr64r777kP79u3zvTxVWloaMjIyULVqVQdPW/Ju3LiBGzduICgoyNmjWBAR7N+/H9999x1OnToFvV6PsmXLolmzZnj00UcRERFhsa7p506tee6G2n+HimLv3r347bffMHXqVGePYoUF0IXNnDkTjRs3RuvWrS0u81Ra9ezZE7GxsRgzZgxatmwJPz8/pKWlITY2Fj/++CMuXboEAHjyySfxxhtvIDIy0skTF8zV8kyaNAkRERFo27YtqlSpgjJlytzxPmrek+ZqeQBg6dKlGDNmDBITE6EoCnx8fJCVlQUAqFSpErp164YnnngCbdu2hYeHh6rz3LhxA97e3qqdr6i++uorTJkyBcnJyQgMDIROp8OVK1fMt3fs2BFDhw5F9+7dbb79qDbJyckICgqCp6fnHdeVPJceLA3lT82/F0Xi4GMOyUFOnTplPiD93nvvlcmTJ8uBAwdsrms6kDUpKUl++eUXq3PRqYHpUkLjxo3Ld52VK1dKly5dxN3dXRo1aqTqg/BdMY/p5y0iIkKGDBkiy5cvl3PnzlmdIsX083b69Gn57LPPZMuWLc4YuUCulkfk1tULgoODpXbt2rJq1SrZvHmz/P333/Lrr7/KgAEDxMfHRxRFkaCgIBk7dqz5BMNqlJSUJIMGDZJffvlFzpw5Y/N0Kbezdek+tThz5oyUK1dOGjVqJNu3b5cjR45IamqqbN++XcaMGSN169Y1/zz2799fjh8/7uyRC3Tu3Dl56KGH5OOPP5atW7fKpUuX8v0goml5YZ5DZzpy5IjVOfxsncT6drefZklNWABdlOlM5U2aNJGKFSuaNx4PPPCAzJkzx+IM66Yf4E8//VQURZGff/7ZWWPna+7cueLt7S2//vqriIj5j3De65SKiFy7dk1mzJghiqLIQw89pMqz4ou4Xp45c+aIoijSoUMHiYqKEk9PT1EURRo0aCDjxo2T+Ph4uXz5ssWn5kyXrvr++++dOLltrpZHRGTixIlSoUKFfM8Vl5OTIwsWLJDGjRuLTqeTxx9/3HzZQbUZP368KIpiPlH16NGjZcOGDXLx4kWrP7im7VtsbKxMmzZNkpKSnDFygSZNmiQVKlQo8BJ7f/zxhzz44IOiKIo8+OCDcuLECQdOWDQTJ04URVHEw8NDQkNDpX///jJ//nzZt2+f1QsL0/Pzyy+/yJAhQ+Tff/91xsgFSkxMlCZNmsirr74qy5Ytk+PHj+f7c2b63xs3bjh8zqJiAXRRw4YNE51OJ7t27ZKjR4/Ku+++Kw8++KD5Vb6Pj488/vjjsmzZMrl27Zro9Xrp37+/Ki/zJCLy008/iaIohTqxrsFgMP+B2LlzpwOmKzpXy/Paa6+JoiiyY8cOOX/+vHzzzTcyePBgqV27tvnyVQ8++KDMmDFDDh48KMnJyeaTqarx583V8oiIdOzYUSIjI80FyLRHzGAwWPwxO3XqlAwYMEAURZGZM2c6ZdY7adeunZQpU0b69etnPumuh4eHtGrVSv73v//J7t27JS0tzZzr5s2b0rNnTylTpowq/zA//PDDcs8990hiYqKI/LfX6PbnJjc317wtGDVqlFNmLYzOnTuLj4+PvPbaaxIdHS3lypUzl/Vhw4bJTz/9JMePHzf/ruj1ennsscfE09NTrl+/7uTprU2ePNn8e+/r6ytt2rSRiRMnyqpVq+TcuXMW65oK4KJFi6Rz5875vvOmBiyALig9PV0efvhhURTFYvd0VlaWrF+/Xl5//XVp3Lixea9gaGio9O7dW3x9feXhhx924uT5O3HihAQFBck999wj27ZtMy/Pe/48kf/+qK1Zs0bc3Nxk9uzZDp+1MFwpT0ZGhvkC7qZLOYnc+qO7Z88e+eSTT6RXr17m68wGBQVJx44dxdPTU5U/b66WR+TW3r0hQ4ZI2bJlC1WAMjMzpVGjRhIZGSnp6ekOmLDwzp8/Lw0bNpSGDRuKiMi+fftk9uzZ0rdvX6lSpYooiiL+/v7So0cP+fLLLyUxMVHi4uKkUqVKEh0d7eTpbRszZoy4ublZlYm8THubjUajdOjQQerWravKvZnJycnSpEkTqV27tojcekHx+++/y5gxY6RZs2bi7e0tXl5e0rx5cxk3bpz8+eef8ttvv0mFChWka9euTp7etocfflh8fX3lgw8+kOeff16qVq0qiqJISEiI9OjRQ2bMmCFbtmyRlJQU83369OkjOp3O6oonasIC6IJycnJk1qxZMmDAAElNTRWj0Wh1wsqLFy/KsmXL5JlnnpGaNWuay6BaLy1mMBhk6tSpoiiKtG7dWpYvX25x++3HYSxcuFDc3d0lNjbWkWMWmivlMRgMsnjxYhk0aJD5LcPbf96uXr0qGzZskClTpkjHjh2lbNmyoiiKrFq1yhkjF8jV8pgsWrRIFEWRAQMGmK9hevshB3m3FUOHDpXy5cur7pjgv/76S7y8vOTRRx+1WJ6RkSHx8fHy3nvvSefOnSUwMFAURZGwsDCJiopS5WXsTP744w9RFEU6d+4sf/31l83jxvI+N6NGjRJ/f385dOiQo0e9o3/++UeqVKkivXr1slh+48YNOXTokCxatEiGDBkiderUETc3NwkMDJR77rlHtc/PxYsXJSoqSsLDw0Xk1nW09+zZI3PmzJFHHnlEypcvL4qiSPXq1eWpp56SxYsXy8KFCyUkJER1l367HQugC8vOzrYqErf/IRMR2bVrl9SuXVvKlSvnqNGK7cMPPzT/wkVGRsqsWbPk/PnzIiLmV1onTpyQ5s2bS+XKlZ05aqG4Wp7b2fp5O3DggNx3332qPDP+nZTmPJcvX5ZOnTqJoijSt2/fAj9UdPXqVRk8eLBUqlTJgRMWTlZWlkyZMkW+/PJLyc3NtXkgfnJysixfvlzeeustadq0qSiKIoGBgU6a+M6ys7Pl6aefFkVRpE2bNvLTTz/leyhBWlqaDB48WEJCQhw8ZeHcuHFDZs2aJYsXLza/g3H785OWliY7duyQuXPnSs+ePVX9/Jw4cUIaNWokjz/+uMVyvV4vFy5ckM2bN8u7774rbdq0kTJlyoinp6d5T7QaC21eLIAaZTQazZ+62rRpk+ovJWT6w5ueni5LliyRDh06WFx6KyoqSp5++mlp27at+Pj4SEBAgCrfLjVxtTy3fzK2oHU2bNggPj4+qv55c7U8JhkZGfLcc8+Zf84efPBBWbx4saSkpMjNmzclNTVVRES++OIL8ff3l5deesnJExeNrYL+zTffiKIoMnToUCdMVDRTp06V4OBg8wf4pk+fLnv27JFTp05JYmKi3LhxQ/73v/9J2bJlZfjw4c4et8hsfWL2+++/F51OJy+88IITJrqz7OxsWbJkifz222/5fpL85s2bcvLkSYmNjZVhw4aJp6enagttXiyALsjWRlAk/+sBjx49WhRFkd27d9tzrGLLb+64uDh55ZVXpGnTplK1alWpVKmSuLu7S7du3WTt2rWF+iPuDFrJk9/P4ZQpU0RRFNm1a5c9xyo2V8tjYvrjlZiYKB999JFERkaai6CHh4e0bt1aunfvLrVq1TLviVLjJzJtXW/V1jqm53HcuHGq3r6J/PezlZaWJt9//7307NlT/Pz8RFEUcXd3l3vuuUciIyPN5fChhx6SkydPOnlq2/I+PwWd+sV025gxY1T//BTFr7/+Kp6enjJkyBBnj3JHPBG0i0pKSkJYWBhycnKg1+vzvS6piOCPP/7ATz/9hJiYGMcOWQQJCQmoUKEC0tLS4O3tjYoVK5pvu379OhISEuDr64vAwEB4e3vD19fXidPemavmuXbtGsqUKYPy5cvnu258fDzWrFmDadOmOXDConG1PLZkZ2djzZo1WLFiBfbv34+MjAxcu3YNnp6eeOqpp/DSSy+hSpUqzh6z0GydQPjChQt44okncPbsWZw8edJJkxVdbm4uduzYgbi4OBw8eBBXrlzBhQsXUK5cOfTr1w/PPvssAgICnD1mkdh6fi5fvowXXngBR44cwdGjR500WcEkz0mqC+P111/HRx99hF27dqFp06b2HO2usQC6EBHBypUrMX/+fBw8eBCZmZlo2LAhGjZsiCZNmqBx48aoWbMmvLy8SsWZzLOzs/Hjjz9izpw52Lt3L3Q6HWrXro1atWqhSZMmaNGiBRo3blxqrhuppTz3338/WrdujUaNGpWKy9gBrpcnr0uXLuHy5csoX7480tPTERwcbFFqr169ivPnz5sLn7+/v2q3D3mzZGZmIjg4GOXKlbO5ruk59fb2Ru/evR07aDHIrXflLIpSVlYWMjMzUbFiRWRnZ6v6qk4GgwEJCQm4evWqeVmNGjUsXuDmlZubiw0bNsDd3R2dOnVy1Jh2c/XqVYwePRp79uzBgQMHnD3OHbEAupBJkyZhxowZ8PHxQXh4OHJzc5GTk4PExESICCIjI9G7d28MHDjQ4hfSdA1TtRk9ejQ+/fRTREREoHbt2vDw8EBaWhoOHTqE9PR0hIeHo3v37njmmWdU/0oL0G6eZ599Fvfff7/5fqX956205AFu7QEbP3481q1bh6SkJPj5+aF69eqoV68eoqKi0KpVKzRs2ND8DoGaXxgWlKVFixZo06YNGjRooOqCZGL672w0GmE0GuHu7m61jtFohKIo5ufDdB+1PkfHjh3D2LFjsWrVKuTk5MDLywuBgYGIiIhAq1at0LVrV7Rq1Ur172bcDYPBgL1790JE0KxZM2ePc2eOfs+Z7OPUqVPi4+Mj3bp1kyNHjojIrU/9/f333/Ljjz/KK6+8InXq1BFFUaRRo0bm01Xkd1yTs508eVK8vb2lT58+5lNxZGRkyNmzZ2Xnzp3y4YcfSqtWrcTDw0OqVasmCxcuFJH8jzlxNuZhHke7cOGCtGjRwnzMWJ8+faRfv37SokUL8wnh69evL1OnTlXl+eTyKkoW06foRcTmKbDUID09Xc6cOWOxTK/Xq/qyYQVJSkqSBg0aiE6nk0GDBsno0aPlzTfflO7du0tAQID5U77PPvusxcnsC3MpNbIfFkAX8fbbb0tQUJCsX79eRKyve5meni7btm2TkSNHiqIoUqlSJdm7d68TJi2c9957T4KCgmTDhg0iYn09xdzcXDl58qR88sknEhISIoqiFHgZJWdjHuZxtEmTJklAQIB88skn5mVXr16VxMREiY+PlwkTJsi9994rOp1OWrZsab6GsRr/ILtSFpFb5/EzXZrzm2++sTpZcG5urlVxvXDhgly8eFGVmSZMmCCBgYEyb94887Ls7GzJycmRs2fPyty5c6V169ai0+nk3nvvNV+OUI1ZRG6d62/Tpk0WJ4J3RSyALmLgwIFSuXJlSU5OFhHr6xLm9cMPP0hAQIC0aNHCoTMWxbBhw6RcuXLmSyMVtKFYu3atVK5cWerWravaX1jmYR5Hu/fee6V79+7mPZq3Z7p586bs37/fXEbq1asnFy9edMaod+RKWUREGjRoYHHaJ0VRpFevXlYn4jflzMjIkKeeekqio6Pv+AloZ4iMjJSuXbua/5vb+v25fPmyzJo1S4KCgsTPz0/++ecfR49ZaK+//rr5VDzvvPNOgSfcNmU9fvy47Nu3T7Vna7BFd+c3iak0aNiwIZKTk/Hnn38CgPn4krzHisj/H+7Zr18/PPbYY/j3339x7Ngxp8x7J/fffz/S09OxfPly8zEvBoPBnCGvzp07Y/DgwUhKSsI///zjhGnvjHmYx5EuXrwIEUF2djZCQkIAWH+K0cvLCw0bNsT06dPx6aef4tixY/joo4+cMW6BXCkLAJw8eRLJyclo27YtNm/ejBdffBHh4eH47bff0L17dwQFBWH48OHYu3evOeeJEyewatUq3Lx50+bxgs505coV8/GyFSpUAGD7E7PBwcF48cUXMWfOHGRmZuLTTz919KiFtn79eiiKgtOnT2PSpElo0KABOnTogK+++gpJSUkW6yqKgqysLEyePBkvvviikyYuHhZAFxEVFQVfX19MnDgRe/bsAQDzJ8lExFwGjUYjAKB27dq4ceMGMjIynDZzQaKiohAaGoqJEyfijz/+AAC4ubmZD4I2GAwAYM4TEhICvV6PmzdvOm3mgjAP8ziKiCAkJAT169fHzp07sWvXLvNyU4683N3d8corr+C+++7D7t27kZmZ6eiR8+VKWUxOnDiBlJQUNG3aFA888ADmzJmDAwcO4IcffkDv3r1hNBrxxRdf4P7770etWrUwffp0/PDDD0hLS8Mbb7zh7PEtiAjKly+Pxo0bY+fOnVi5cqX5hZNer7da393dHf369UOrVq3w999/IzU11QlTF+z06dO4dOkSoqKiEBcXh7fffhsPPPAAtm/fjhdffBH33HMP+vXrh99++808/z///IPY2FiUKVMGHh4eTk5QBI7c3Uj2YdoF/fXXX4ubm5soiiIvvPCCrF+/XjIyMqzWv379ujzxxBNSvnx5R49aKKY8q1evNl9SJzo6WpYtW2a+UkFemZmZ0rdvX+ZxEOZRdx6Tr776ynyc2e1vYRkMBtHr9ebs6enp0q1bN7nvvvucMeoduVKWbdu2SXh4uHz11VciYn289pkzZ2TWrFny4IMPWrxFrOYrS6xatUoURZE6depYXa/c9OEW0/OTlpYmjz76qNSpU8cZo95RXFyc6HQ6GTFihHnZtWvXJDY2Vl577TVp2LCh+TkJCwuTkSNHytChQ0VRFPOxjaUFC6ALyczMlC+++EIqVKggiqJIhQoVpGfPnjJt2jRZv369pKamys6dO2Xo0KHi6ekpo0ePdvbIBcrNzZWffvrJ4hcuMjJShg8fLj///LMcOXJEfvnlF+nXr5+4ubnJW2+95eyRC8Q8zONo//vf/0Sn04miKDJo0CCJjY2VGzdumG83/VFev369hIWFqfrqBa6SJScnRw4fPmw+Xlvk1uy2PgF8/Phx8zWC1X7pt++++04qVqwoiqJI+/btZenSpRbXMzY9P3/88YeEhoaq9vnZt2+f1K5dWz777DMRsf5A2IULF+T777+XQYMGSfXq1UtFQc8PC6ALuP2A28zMTPnkk0+kZcuW4u7ubv4B1el04unpKYqiyDPPPCPnzp1z0sRF9+uvv8rDDz9slUdRFPH09JTXXnvNYoOqdsyjbqU9j2mbcPXqVZk5c6b5RaG7u7s0b95cRo0aJStWrJD4+HiZOXOmVK9eXYKDg+XAgQNOntyaK2UpjNvL4NSpU0VRFNmzZ48Tp7qzmzdvynfffSf333+/+XemYsWK0rdvX/n666/l22+/lTFjxkj58uUlNDS0wA9WOFtGRobV3n9bpxNKSkqSl19+WRRFkWHDhjlqvBLDE0G7sJSUFBw/fhw7duzAn3/+CYPBgDp16uCee+7Bc8895+zx7kj+/9jFvCfZTU5OxsaNG7F161Z4eHggNDQU9erVQ48ePZw4aeEwj7q5Uh657WTBN2/exMKFC/Htt99i+/btVuvfe++9GDt2LJ566ilHjlkorpQF+O+SaAWdQNyU+fjx4+jRowf0ej1OnDjh4EmLR0SwYsUKfPXVV1i7dq3VsYAtW7bEhAkT8NBDDzlpwrtz+3Zi8uTJeOedd7B7926LE8SXBiyApdylS5dw8OBBHD9+HJmZmYiKikK9evUQHBxstXG5/TJCt29Y1cDW9SLzc/sGlHnsj3nUnacwzp49i/Xr1+PQoUOoVKkSKlSogDZt2qBWrVrOHq3IXCmLLceOHcOjjz6KHj164IMPPnD2OAUSG5exS09Px6ZNm3Dy5EmEhoaibNmyaNasmfnTwqXdyZMn8eijj+LatWs4deqUs8cpMhbAUmz16tV49913rV4FBwUFoWPHjujXrx969Ohh8amkovzBc7b8ZjUYDNDpdFAUBXq9XnWnRcgP86ibq+RZs2YNDh06hH379qFixYpo2rQpatWqhfDwcJQvX75UfUrRlbIAlnkqVKiAZs2aoVatWoiIiED58uXh5uZm84WFWn/u8tuLaTAYoChKqflbU1ynTp3C0KFD0a5dO4wfP97Z4xQZC2AplZiYiAcffBBZWVkYPHgw2rdvj5MnT2Lv3r3Yv38/Dhw4gOzsbNx7770YN24cevfuDU9PT9Xutbh48SI++OADdOnSBc2bN7e4uLvpR1SNc+eHedTN1fIAQFpaGt5//318+OGHcHNzszhNSlBQEFq3bo1evXrhkUceQVBQkPk2NW4TXCkLUPg8jz76qMXPolqvM337iyVbe/9uXy7/f+oeNRZZk+L+91br83RHdj3CkOxm/PjxEhgYKD///LPVbYmJibJ06VJ56qmnzAfjTp8+3QlTFt6kSZNEURSpXr26PPzww/Lhhx/Krl27rK60YDrlg4jIxo0bZfXq1c4Y946Yh3kc7YMPPhAfHx/p1auXbNy4UY4dOyY//PCDTJ06Vbp3726+hF2TJk3k119/dfa4BXKlLCKul2fOnDnSt29fWblypVy7ds3iNoPBoMrrLxfk9nkLew3p7Oxse43kECyApVTz5s3lwQcflMuXL4vIrVNY2DqNQFxcnDRu3Fi8vLxk/vz5jh6z0Bo1aiSenp7SokUL8yeVq1WrJk899ZTMmzdPjhw5YrF+VlaWPPLII6LT6SxOBaEWzMM8jhYRESEPP/ywpKSkWN2WlJQkK1eulBdeeMH8yeavv/7aCVMWjitlEXG9PNWqVRNFUcTb21uaN28uEydOlO3bt1udkcJ0jsOsrCz5+OOPJS4uzhnj3pGrFdrCYgEsha5duyadOnWSevXqmS8invcH9PZXL3///bcEBgbKI488Yr5dTc6ePSvVqlWT+++/X3JycmT79u0yceJEiYyMFEVRxM3NTRo2bCgvv/yyLFu2TNLT02XXrl1SqVIl6dGjh7PHt8I8zONoR44ckbJly8q4cePMy2z94crOzpY//vhDatSoIUFBQbJt2zZHj3pHrpRFxPXyHDp0SBRFkaZNm0rnzp3N7zKVLVtWoqOj5dNPP7V6AfXnn3+KoijSunVrJ01dMFcrtIXFAlhKvfnmm6Iois29enl/aE0bmZ49e0qdOnXk9OnTDpuxsHbu3ClBQUEyaNAgEbl14k2DwSAXL16U1atXy4svvigRERGiKIr4+PhI27ZtpWPHjqIoiqxYscK5w9vAPMzjaP/8849UqVJF+vXrJyK3/lDd/qIw73bht99+U+2hIa6URcT18nz//feiKIp89NFHIiJy7NgxmT59ujRq1MhcBitXrixPPPGEfPvtt5KamiozZ85U7ZUyXLHQFhYLYCl17tw5adCggSiKIq+88or89ddfVm9NmV6tpKenS58+faRq1arOGPWOEhIS5LHHHpPvvvvO5u05OTly+vRpWbRokfTt21eCgoJUfeZ15mEeZ2jevLn4+fnJqlWrrG4zFQxT8bhy5YpUr15devfu7dAZC8uVsoi4Vp65c+eKoig2s+zatUtee+01CQ8PNxepOnXqSKVKlSQgIMDxwxaCqxXaomABLMV+/fVX86VomjZtKu+8845s3LhRTp8+bVEGFy9eLCEhITJ06FAnTluwtLQ0m8fH5GXaQH755ZeqP/M68zCPo5gKxM6dOyUsLEwURZGRI0fKzp07rV4Umj7ksm3bNgkNDbW43qkauFIWEdfMs337dnnttdfk33//tVie140bN2TlypUyaNAgCQgIEEVR5OWXX3b0uIXiaoW2KFgAS5nbf9GuXLkir7/+ulStWtV8/d8OHTrI008/LS+88IIMGDBAvLy8pF69enL06FEnTZ0/W8cjmt6Sy88bb7whiqLIX3/9Zc/RioV5mMdZ9Hq9xMTESOXKlUVRFKlfv7689tpr8uOPP8rhw4fNGc+dOydPPPGEuLu7qzaTK2URcb08165dy/cTsLf/jg0fPlwURZG9e/c6YLKiccVCWxQsgKWQ6YczMTHRvOE4ePCgvP/++xIdHW0ug4qiSFBQkHTo0EHV11005blw4YLVH2K9Xm/xy5iYmCgNGzaU4OBgh85YFMzDPM506dIlmTRpktSrV090Op2ULVtW6tatK/fff7907txZwsPDxdvbW1566SVnj3pHrpRFxPXy5Mf0O/Tvv//K/fffL7Vq1XLyRAVzlUJbVDwRdCmi1+uxdetWfPPNNzh+/DgURYGPjw+aNWuGvn37onHjxhARJCYm4saNGzh58iTq1auH8PBwuLu7q+4kqbfn0el0KFOmDCIjI/H444+jVatWVvdJSUnBokWLEBoain79+jlh6vwxD/M4k+S5RumNGzeQkJCA3bt3Y+vWrdi5cyeOHj2KkJAQhIeH4/nnn8fTTz8NX19fZ49tkytlAVwvT2GtXLkSjzzyCN544w1Mnz7d2eMUm+lv54kTJ9CvXz+kp6cjISHB2WPdPed1TyqqDz/8UPz9/UVRFKldu7bUq1fPvKfP9LbC7Nmz5eLFi84etVDulOeee+6Rjz76SC5cuGBxv+zsbFWel4l5bmEe9TAYDJKVlSW5ubmSkpKi6ncC7sSVsoiU7jyFPZVYcnKyxMTEyJUrV+w8kWOsWLFCFEWRMWPGOHuUEsECWEqcPHlSfH195YEHHpCTJ0/KuXPnJDc3VxITE2XOnDnSvn178x+yDh06yO7du509coGKkqdjx46qPh5GhHmYx/GuX78uR48elevXr1vdZjAYLP5I3/4HW22F1pWyiGgrz53YukCB2mi10LIAlhITJ06UChUqyPr1683Lbv+hPXDggAwcOFC8vb2lbt26smfPHkePWWh3k0dtJ7IWYR7mcbz3339fmjZtKtOmTZO4uDhJSkqy+mN7+znmLl26ZD49lJq4UhYRbea5nZrzuHqhLSwWwFLisccekxo1asiZM2dE5L9z/BmNRqsfyE8++UQURZHBgwc7fM7CYh7mcSRXyyMi5tOKuLu7S/ny5aVHjx4ya9Ys2bVrl81T3GRmZsrrr78uzzzzjOr2MrlSFhHmyZtHjYXJ1QptcbEAlhLvvPOOKIoihw8fznedvK8mH3/8calataqcOHHCEeMVGfMwjyO5Wp5jx45J2bJlpVWrVvL5559Lz549pUKFCqIoikRERMigQYNk0aJFcujQIbl69aqIiOzYsUMCAgKkZ8+eTp39dq6URYR5RNSdR8T1Cm1xsQCWElu2bBFFUaRRo0ayYcMGmx9Zz7s3Y9y4ceLj4yP79+939KiFwjzM40iulmfFihXi7u4uU6ZMERGR06dPS2xsrEyZMkXatm0rZcuWFXd3d2nYsKGMHDlS1qxZYz6fodquXuBKWUSYR+15XLHQFhcLYCmh1+tl9OjR5k8rfv7555KcnGxz3dTUVBk4cKCEhIQ4eMrCYx7mcSRXy/Pjjz+KoiiydOlSi+U5OTmSkJAgP/30k7z66qsSGRkpnp6e4uvrKz4+Pqq8nJ0rZRFhHrXncbVCezdYAEuZL7/8UmrWrCmKokhYWJi8/PLL8scff8iBAwfk8OHDkpSUJG+99ZZ4e3vLqFGjnD3uHTGPujGPOhmNRvnnn3/k5MmT5q9vl5mZKX///bd8//330qVLF/N1w9XGlbKIMI/a87haob0bLICljNFolOPHj8sbb7xhcX3CihUrSpUqVcTNzU0URZEnn3xSEhMTnT3uHTGPujFP6WPrD/Qrr7wiiqLI33//7YSJis+Vsogwjxq4WqG9G7wSSCmWlZWFXbt2Yfny5Th//jwuXboEf39/9O3bF48//ji8vb2dPWKRMI+6MU/pYjQaodPpcPr0afTs2RNXr17F2bNnnT1WsbhSFoB51EpsXC1rxIgR+Pzzz/HXX3+hcePGTprMPtydPQAVn6+vL9q3b4/27dsjNzcXHh4ezh7prjCPujFP6aLT6QAASUlJyM3NxbBhw5w8UfG5UhaAedTKVP7yFtrNmzejSpUqLlf+AIB7AImIXJiI4Ny5cwgKCir115d1pSwA86jd1q1bMWTIEAwcOBBvvfWWs8cpcSyARERERLdxtUJ7OxZAIiIiIo3ROXsAIiIiInIsFkAiIiIijWEBJCIiItIYFkAiIiIijWEBJCIiItIYFkAiIiIijWEBJCIiItIYFkAiIiIijfk/rtu+fgO5ONIAAAAASUVORK5CYII=", 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" ] }, - "execution_count": 30, + "execution_count": 19, "metadata": {}, "output_type": "execute_result" } @@ -658,6 +679,7 @@ ] }, { + "attachments": {}, "cell_type": "markdown", "id": "939ec324", "metadata": { @@ -682,34 +704,46 @@ }, { "cell_type": "code", - "execution_count": 19, + "execution_count": 20, "id": "02ad6d3e", "metadata": {}, "outputs": [ + { + "name": "stderr", + "output_type": "stream", + "text": [ + "/tmp/ipykernel_21335/1309103975.py:9: DeprecationWarning: The class ``qiskit.utils.quantum_instance.QuantumInstance`` is deprecated as of qiskit-terra 0.24.0. It will be removed no earlier than 3 months after the release date. For code migration guidelines, visit https://qisk.it/qi_migration.\n", + " qi = QuantumInstance(local_simulator, seed_transpiler=42, seed_simulator=42)\n", + "/tmp/ipykernel_21335/1309103975.py:13: DeprecationWarning: The class ``qiskit.algorithms.minimum_eigen_solvers.vqe.VQE`` is deprecated as of qiskit-terra 0.24.0. It will be removed no earlier than 3 months after the release date. Instead, use the class ``qiskit.algorithms.minimum_eigensolvers.VQE``. See https://qisk.it/algo_migration for a migration guide.\n", + " vqe = VQE(ansatz, optimizer=slsqp, quantum_instance=qi)\n" + ] + }, { "name": "stdout", "output_type": "stream", "text": [ "{ 'aux_operator_eigenvalues': None,\n", " 'cost_function_evals': 9,\n", - " 'eigenstate': { '00': 0.04419417382415922,\n", - " '01': 0.94631274560792,\n", - " '10': 0.19515618744994995,\n", - " '11': 0.2538762001448738},\n", - " 'eigenvalue': (-1.6891153397630962+0j),\n", - " 'optimal_parameters': { ParameterVectorElement(θ[0]): -1.5057852302979455,\n", - " ParameterVectorElement(θ[1]): 0.17806892747075853,\n", - " ParameterVectorElement(θ[2]): -2.9377191205349478,\n", - " ParameterVectorElement(θ[3]): -6.1111063638168925,\n", - " ParameterVectorElement(θ[4]): 0.5757868603404876,\n", - " ParameterVectorElement(θ[5]): 0.6859617452099496,\n", - " ParameterVectorElement(θ[6]): -5.657884129072659,\n", - " ParameterVectorElement(θ[7]): 0.7981284053630464},\n", - " 'optimal_point': array([-1.50578523, 0.17806893, -2.93771912, -6.11110636, 0.57578686,\n", - " 0.68596175, -5.65788413, 0.79812841]),\n", - " 'optimal_value': -1.6891153397630962,\n", + " 'eigenstate': { '00': 0.5854685623498498,\n", + " '01': 0.5837981778834189,\n", + " '10': 0.46770717334674267,\n", + " '11': 0.3125},\n", + " 'eigenvalue': (-1.2938597123240512+0j),\n", + " 'optimal_circuit': None,\n", + " 'optimal_parameters': { ParameterVectorElement(θ[1]): -2.7502662569061473,\n", + " ParameterVectorElement(θ[0]): -1.4898253895470077,\n", + " ParameterVectorElement(θ[2]): 5.777835248686062,\n", + " ParameterVectorElement(θ[3]): 5.998464701792347,\n", + " ParameterVectorElement(θ[4]): 1.6774540702480465,\n", + " ParameterVectorElement(θ[5]): -3.1634349542322076,\n", + " ParameterVectorElement(θ[6]): 4.089977645429185,\n", + " ParameterVectorElement(θ[7]): -5.51571636504145},\n", + " 'optimal_point': array([-1.48982539, -2.75026626, 5.77783525, 5.9984647 , 1.67745407,\n", + " -3.16343495, 4.08997765, -5.51571637]),\n", + " 'optimal_value': -1.2938597123240512,\n", " 'optimizer_evals': None,\n", - " 'optimizer_time': 0.29915356636047363}\n" + " 'optimizer_result': None,\n", + " 'optimizer_time': 1.0542807579040527}\n" ] } ], @@ -733,6 +767,7 @@ ] }, { + "attachments": {}, "cell_type": "markdown", "id": "86c36457", "metadata": { @@ -752,7 +787,7 @@ }, { "cell_type": "code", - "execution_count": 4, + "execution_count": 21, "id": "5968d451", "metadata": {}, "outputs": [ @@ -760,53 +795,53 @@ "name": "stdout", "output_type": "stream", "text": [ - "\"\"\"Example of Hybrid Job payload with VQE.\"\"\"\r\n", - "from braket.jobs import save_job_result\r\n", - "from qiskit.opflow import (\r\n", - " I,\r\n", - " X,\r\n", - " Z,\r\n", - ")\r\n", - "from qiskit.algorithms import VQE\r\n", - "from qiskit.algorithms.optimizers import SLSQP\r\n", - "from qiskit.circuit.library import TwoLocal\r\n", - "from qiskit.utils import QuantumInstance\r\n", - "\r\n", - "from qiskit_braket_provider import AWSBraketProvider\r\n", - "\r\n", - "\r\n", - "def main():\r\n", - " backend = AWSBraketProvider().get_backend(\"SV1\")\r\n", - "\r\n", - " h2_op = (\r\n", - " (-1.052373245772859 * I ^ I)\r\n", - " + (0.39793742484318045 * I ^ Z)\r\n", - " + (-0.39793742484318045 * Z ^ I)\r\n", - " + (-0.01128010425623538 * Z ^ Z)\r\n", - " + (0.18093119978423156 * X ^ X)\r\n", - " )\r\n", - "\r\n", - " quantum_instance = QuantumInstance(\r\n", - " backend, seed_transpiler=42, seed_simulator=42, shots=10\r\n", - " )\r\n", - " ansatz = TwoLocal(rotation_blocks=\"ry\", entanglement_blocks=\"cz\")\r\n", - " slsqp = SLSQP(maxiter=1)\r\n", - "\r\n", - " vqe = VQE(ansatz, optimizer=slsqp, quantum_instance=quantum_instance)\r\n", - "\r\n", - " vqe_result = vqe.compute_minimum_eigenvalue(h2_op)\r\n", - "\r\n", - " save_job_result(\r\n", - " {\r\n", - " \"VQE\": {\r\n", - " \"eigenstate\": vqe_result.eigenstate,\r\n", - " \"eigenvalue\": vqe_result.eigenvalue.real,\r\n", - " \"optimal_parameters\": list(vqe_result.optimal_parameters.values()),\r\n", - " \"optimal_point\": vqe_result.optimal_point.tolist(),\r\n", - " \"optimal_value\": vqe_result.optimal_value.real,\r\n", - " }\r\n", - " }\r\n", - " )\r\n" + "\"\"\"Example of Hybrid Job payload with VQE.\"\"\"\n", + "from braket.jobs import save_job_result\n", + "from qiskit.opflow import (\n", + " I,\n", + " X,\n", + " Z,\n", + ")\n", + "from qiskit.algorithms import VQE\n", + "from qiskit.algorithms.optimizers import SLSQP\n", + "from qiskit.circuit.library import TwoLocal\n", + "from qiskit.utils import QuantumInstance\n", + "\n", + "from qiskit_braket_provider import AWSBraketProvider\n", + "\n", + "\n", + "def main():\n", + " backend = AWSBraketProvider().get_backend(\"SV1\")\n", + "\n", + " h2_op = (\n", + " (-1.052373245772859 * I ^ I)\n", + " + (0.39793742484318045 * I ^ Z)\n", + " + (-0.39793742484318045 * Z ^ I)\n", + " + (-0.01128010425623538 * Z ^ Z)\n", + " + (0.18093119978423156 * X ^ X)\n", + " )\n", + "\n", + " quantum_instance = QuantumInstance(\n", + " backend, seed_transpiler=42, seed_simulator=42, shots=10\n", + " )\n", + " ansatz = TwoLocal(rotation_blocks=\"ry\", entanglement_blocks=\"cz\")\n", + " slsqp = SLSQP(maxiter=1)\n", + "\n", + " vqe = VQE(ansatz, optimizer=slsqp, quantum_instance=quantum_instance)\n", + "\n", + " vqe_result = vqe.compute_minimum_eigenvalue(h2_op)\n", + "\n", + " save_job_result(\n", + " {\n", + " \"VQE\": {\n", + " \"eigenstate\": vqe_result.eigenstate,\n", + " \"eigenvalue\": vqe_result.eigenvalue.real,\n", + " \"optimal_parameters\": list(vqe_result.optimal_parameters.values()),\n", + " \"optimal_point\": vqe_result.optimal_point.tolist(),\n", + " \"optimal_value\": vqe_result.optimal_value.real,\n", + " }\n", + " }\n", + " )\n" ] } ], @@ -815,6 +850,7 @@ ] }, { + "attachments": {}, "cell_type": "markdown", "id": "9b1aa5f7", "metadata": { @@ -828,7 +864,7 @@ }, { "cell_type": "code", - "execution_count": 5, + "execution_count": 30, "id": "646bfb43", "metadata": { "slideshow": { @@ -840,11 +876,11 @@ "name": "stdout", "output_type": "stream", "text": [ - "FROM 292282985366.dkr.ecr.us-west-2.amazonaws.com/amazon-braket-base-jobs:1.0-cpu-py37-ubuntu18.04\r\n", - "\r\n", - "RUN python3 -m pip install --upgrade pip\r\n", - "\r\n", - "RUN python3 -m pip install --no-cache --upgrade git+https://github.com/qiskit-community/qiskit-braket-provider\r\n" + "FROM 292282985366.dkr.ecr.us-west-2.amazonaws.com/amazon-braket-base-jobs:1.0-cpu-py37-ubuntu18.04\n", + "\n", + "RUN python3 -m pip install --upgrade pip\n", + "\n", + "RUN python3 -m pip install --no-cache --upgrade git+https://github.com/qiskit-community/qiskit-braket-provider\n" ] } ], @@ -853,6 +889,7 @@ ] }, { + "attachments": {}, "cell_type": "markdown", "id": "1bcded1f", "metadata": {}, @@ -862,7 +899,7 @@ }, { "cell_type": "code", - "execution_count": null, + "execution_count": 31, "id": "55cd14e3", "metadata": { "slideshow": { @@ -885,14 +922,25 @@ }, { "cell_type": "code", - "execution_count": null, + "execution_count": 27, "id": "1ec1b936", "metadata": { "slideshow": { "slide_type": "slide" } }, - "outputs": [], + "outputs": [ + { + "data": { + "text/plain": [ + "{}" + ] + }, + "execution_count": 27, + "metadata": {}, + "output_type": "execute_result" + } + ], "source": [ "# print(job.result())\n", "AwsQuantumJob(\"\").result()" @@ -915,7 +963,7 @@ "name": "python", "nbconvert_exporter": "python", "pygments_lexer": "ipython3", - "version": "3.9.6" + "version": "3.8.10" } }, "nbformat": 4, diff --git a/docs/tutorials/3_tutorial_minimum_eigen_optimizer.ipynb b/docs/tutorials/3_tutorial_minimum_eigen_optimizer.ipynb index a6e78440..2f5bfd24 100644 --- a/docs/tutorials/3_tutorial_minimum_eigen_optimizer.ipynb +++ b/docs/tutorials/3_tutorial_minimum_eigen_optimizer.ipynb @@ -1,6 +1,7 @@ { "cells": [ { + "attachments": {}, "cell_type": "markdown", "id": "d58530d2", "metadata": {}, @@ -12,17 +13,54 @@ }, { "cell_type": "code", - "execution_count": null, + "execution_count": 1, "id": "704bfb64", "metadata": {}, - "outputs": [], + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "Collecting qiskit_optimization\n", + " Downloading qiskit_optimization-0.5.0-py3-none-any.whl (156 kB)\n", + "\u001b[2K \u001b[90m━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━\u001b[0m \u001b[32m156.5/156.5 kB\u001b[0m \u001b[31m1.8 MB/s\u001b[0m eta \u001b[36m0:00:00\u001b[0m00:01\u001b[0m00:01\u001b[0m\n", + "\u001b[?25hRequirement already satisfied: qiskit-terra>=0.22.4 in /home/robotastray/qiskit-braket-provider/venv/lib/python3.8/site-packages (from qiskit_optimization) (0.24.1)\n", + "Requirement already satisfied: scipy>=1.4 in /home/robotastray/qiskit-braket-provider/venv/lib/python3.8/site-packages (from qiskit_optimization) (1.10.1)\n", + "Requirement already satisfied: numpy>=1.17 in /home/robotastray/qiskit-braket-provider/venv/lib/python3.8/site-packages (from qiskit_optimization) (1.23.5)\n", + "Collecting docplex!=2.24.231,>=2.21.207 (from qiskit_optimization)\n", + " Downloading docplex-2.25.236.tar.gz (633 kB)\n", + "\u001b[2K \u001b[90m━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━\u001b[0m \u001b[32m633.5/633.5 kB\u001b[0m \u001b[31m4.1 MB/s\u001b[0m eta \u001b[36m0:00:00\u001b[0m00:01\u001b[0m00:01\u001b[0m\n", + "\u001b[?25h Preparing metadata (setup.py) ... \u001b[?25ldone\n", + "\u001b[?25hRequirement already satisfied: setuptools>=40.1.0 in /home/robotastray/qiskit-braket-provider/venv/lib/python3.8/site-packages (from qiskit_optimization) (67.7.2)\n", + "Requirement already satisfied: networkx>=2.6.3 in /home/robotastray/qiskit-braket-provider/venv/lib/python3.8/site-packages (from qiskit_optimization) (3.1)\n", + "Requirement already satisfied: six in /home/robotastray/qiskit-braket-provider/venv/lib/python3.8/site-packages (from docplex!=2.24.231,>=2.21.207->qiskit_optimization) (1.16.0)\n", + "Requirement already satisfied: rustworkx>=0.12.0 in /home/robotastray/qiskit-braket-provider/venv/lib/python3.8/site-packages (from qiskit-terra>=0.22.4->qiskit_optimization) (0.13.0)\n", + "Requirement already satisfied: ply>=3.10 in /home/robotastray/qiskit-braket-provider/venv/lib/python3.8/site-packages (from qiskit-terra>=0.22.4->qiskit_optimization) (3.11)\n", + "Requirement already satisfied: psutil>=5 in /home/robotastray/qiskit-braket-provider/venv/lib/python3.8/site-packages (from qiskit-terra>=0.22.4->qiskit_optimization) (5.9.5)\n", + "Requirement already satisfied: sympy>=1.3 in /home/robotastray/qiskit-braket-provider/venv/lib/python3.8/site-packages (from qiskit-terra>=0.22.4->qiskit_optimization) (1.12)\n", + "Requirement already satisfied: dill>=0.3 in /home/robotastray/qiskit-braket-provider/venv/lib/python3.8/site-packages (from qiskit-terra>=0.22.4->qiskit_optimization) (0.3.6)\n", + "Requirement already satisfied: python-dateutil>=2.8.0 in /home/robotastray/qiskit-braket-provider/venv/lib/python3.8/site-packages (from qiskit-terra>=0.22.4->qiskit_optimization) (2.8.2)\n", + "Requirement already satisfied: stevedore>=3.0.0 in /home/robotastray/qiskit-braket-provider/venv/lib/python3.8/site-packages (from qiskit-terra>=0.22.4->qiskit_optimization) (5.1.0)\n", + "Requirement already satisfied: symengine<0.10,>=0.9 in /home/robotastray/qiskit-braket-provider/venv/lib/python3.8/site-packages (from qiskit-terra>=0.22.4->qiskit_optimization) (0.9.2)\n", + "Requirement already satisfied: pbr!=2.1.0,>=2.0.0 in /home/robotastray/qiskit-braket-provider/venv/lib/python3.8/site-packages (from stevedore>=3.0.0->qiskit-terra>=0.22.4->qiskit_optimization) (5.11.1)\n", + "Requirement already satisfied: mpmath>=0.19 in /home/robotastray/qiskit-braket-provider/venv/lib/python3.8/site-packages (from sympy>=1.3->qiskit-terra>=0.22.4->qiskit_optimization) (1.3.0)\n", + "Building wheels for collected packages: docplex\n", + " Building wheel for docplex (setup.py) ... \u001b[?25ldone\n", + "\u001b[?25h Created wheel for docplex: filename=docplex-2.25.236-py3-none-any.whl size=671350 sha256=9249c6a84de2faf8bdcbab214a249d5d0f59baacde525363554a1e68347f1283\n", + " Stored in directory: /home/robotastray/.cache/pip/wheels/b8/98/f8/22c3fe8d29be988cc4584363f494a459fb8f09c16d8e438ac7\n", + "Successfully built docplex\n", + "Installing collected packages: docplex, qiskit_optimization\n", + "Successfully installed docplex-2.25.236 qiskit_optimization-0.5.0\n" + ] + } + ], "source": [ "! pip install qiskit_optimization" ] }, { "cell_type": "code", - "execution_count": 8, + "execution_count": 2, "id": "2c692b55", "metadata": {}, "outputs": [], @@ -46,6 +84,7 @@ ] }, { + "attachments": {}, "cell_type": "markdown", "id": "bd534390", "metadata": {}, @@ -55,7 +94,7 @@ }, { "cell_type": "code", - "execution_count": 5, + "execution_count": 3, "id": "f55baa58", "metadata": {}, "outputs": [ @@ -97,7 +136,7 @@ }, { "cell_type": "code", - "execution_count": 6, + "execution_count": 4, "id": "eae79719", "metadata": {}, "outputs": [ @@ -107,12 +146,12 @@ "text": [ "offset: 1.5\n", "operator:\n", - "-1.75 * ZII\n", + "-0.5 * IIZ\n", "+ 0.25 * IZI\n", - "+ 0.5 * ZZI\n", - "- 0.5 * IIZ\n", + "- 1.75 * ZII\n", + "+ 0.25 * IZZ\n", "- 0.25 * ZIZ\n", - "+ 0.25 * IZZ\n" + "+ 0.5 * ZZI\n" ] } ], @@ -125,7 +164,7 @@ }, { "cell_type": "code", - "execution_count": 7, + "execution_count": 5, "id": "ec6b4990", "metadata": {}, "outputs": [ @@ -160,6 +199,7 @@ ] }, { + "attachments": {}, "cell_type": "markdown", "id": "dd5b2f10", "metadata": {}, @@ -169,10 +209,23 @@ }, { "cell_type": "code", - "execution_count": 13, + "execution_count": 6, "id": "e17f6bc4", "metadata": {}, - "outputs": [], + "outputs": [ + { + "name": "stderr", + "output_type": "stream", + "text": [ + "/tmp/ipykernel_69023/2374560280.py:3: DeprecationWarning: The class ``qiskit.utils.quantum_instance.QuantumInstance`` is deprecated as of qiskit-terra 0.24.0. It will be removed no earlier than 3 months after the release date. For code migration guidelines, visit https://qisk.it/qi_migration.\n", + " quantum_instance = QuantumInstance(\n", + "/tmp/ipykernel_69023/2374560280.py:8: DeprecationWarning: The class ``qiskit.algorithms.minimum_eigen_solvers.qaoa.QAOA`` is deprecated as of qiskit-terra 0.24.0. It will be removed no earlier than 3 months after the release date. Instead, use the class ``qiskit.algorithms.minimum_eigensolvers.QAOA``. See https://qisk.it/algo_migration for a migration guide.\n", + " qaoa_mes = QAOA(quantum_instance=quantum_instance, initial_point=[0.0, 0.0])\n", + "/tmp/ipykernel_69023/2374560280.py:9: DeprecationWarning: The class ``qiskit.algorithms.minimum_eigen_solvers.numpy_minimum_eigen_solver.NumPyMinimumEigensolver`` is deprecated as of qiskit-terra 0.24.0. It will be removed no earlier than 3 months after the release date. Instead, use the class ``qiskit.algorithms.minimum_eigensolvers.NumPyMinimumEigensolver``. See https://qisk.it/algo_migration for a migration guide.\n", + " exact_mes = NumPyMinimumEigensolver()\n" + ] + } + ], "source": [ "algorithm_globals.random_seed = 10598\n", "\n", @@ -187,7 +240,7 @@ }, { "cell_type": "code", - "execution_count": 14, + "execution_count": 7, "id": "9e3248ad", "metadata": {}, "outputs": [], @@ -200,7 +253,7 @@ }, { "cell_type": "code", - "execution_count": 15, + "execution_count": 8, "id": "81d2e400", "metadata": {}, "outputs": [ @@ -208,9 +261,7 @@ "name": "stdout", "output_type": "stream", "text": [ - "optimal function value: -2.0\n", - "optimal value: [0. 1. 0.]\n", - "status: SUCCESS\n" + "fval=-2.0, x=0.0, y=1.0, z=0.0, status=SUCCESS\n" ] } ], @@ -221,7 +272,7 @@ }, { "cell_type": "code", - "execution_count": 16, + "execution_count": 10, "id": "59e7a201", "metadata": {}, "outputs": [ @@ -229,9 +280,7 @@ "name": "stdout", "output_type": "stream", "text": [ - "optimal function value: -2.0\n", - "optimal value: [0. 1. 0.]\n", - "status: SUCCESS\n" + "fval=-2.0, x=0.0, y=1.0, z=0.0, status=SUCCESS\n" ] } ], @@ -241,6 +290,7 @@ ] }, { + "attachments": {}, "cell_type": "markdown", "id": "c345243c", "metadata": {}, @@ -250,7 +300,7 @@ }, { "cell_type": "code", - "execution_count": 17, + "execution_count": 11, "id": "c54be53e", "metadata": {}, "outputs": [ @@ -259,14 +309,13 @@ "output_type": "stream", "text": [ "variable order: ['x', 'y', 'z']\n", - "SolutionSample(x=array([0., 1., 0.]), fval=-2.0, probability=0.07031249999999999, status=)\n", - "SolutionSample(x=array([0., 0., 0.]), fval=0.0, probability=0.0625, status=)\n", - "SolutionSample(x=array([1., 1., 0.]), fval=0.0, probability=0.08496093750000001, status=)\n", - "SolutionSample(x=array([1., 0., 0.]), fval=1.0, probability=0.08007812500000001, status=)\n", - "SolutionSample(x=array([0., 0., 1.]), fval=3.0, probability=0.1611328125, status=)\n", - "SolutionSample(x=array([1., 0., 1.]), fval=3.0, probability=0.20800781249999997, status=)\n", - "SolutionSample(x=array([0., 1., 1.]), fval=3.0, probability=0.16015625, status=)\n", - "SolutionSample(x=array([1., 1., 1.]), fval=4.0, probability=0.1728515625, status=)\n" + "SolutionSample(x=array([0., 1., 0.]), fval=-2.0, probability=0.123046875, status=)\n", + "SolutionSample(x=array([1., 1., 0.]), fval=0.0, probability=0.302734375, status=)\n", + "SolutionSample(x=array([1., 0., 0.]), fval=1.0, probability=0.0888671875, status=)\n", + "SolutionSample(x=array([0., 0., 1.]), fval=3.0, probability=0.22851562500000003, status=)\n", + "SolutionSample(x=array([1., 0., 1.]), fval=3.0, probability=0.12500000000000003, status=)\n", + "SolutionSample(x=array([0., 1., 1.]), fval=3.0, probability=0.025390624999999997, status=)\n", + "SolutionSample(x=array([1., 1., 1.]), fval=4.0, probability=0.10644531250000001, status=)\n" ] } ], @@ -278,7 +327,7 @@ }, { "cell_type": "code", - "execution_count": 18, + "execution_count": 12, "id": "651b9550", "metadata": {}, "outputs": [], @@ -301,7 +350,7 @@ }, { "cell_type": "code", - "execution_count": 19, + "execution_count": 13, "id": "224a2a4a", "metadata": {}, "outputs": [ @@ -309,14 +358,13 @@ "name": "stdout", "output_type": "stream", "text": [ - "SolutionSample(x=array([0., 1., 0.]), fval=-2.0, probability=0.07031249999999999, status=)\n", - "SolutionSample(x=array([0., 0., 0.]), fval=0.0, probability=0.0625, status=)\n", - "SolutionSample(x=array([1., 1., 0.]), fval=0.0, probability=0.08496093750000001, status=)\n", - "SolutionSample(x=array([1., 0., 0.]), fval=1.0, probability=0.08007812500000001, status=)\n", - "SolutionSample(x=array([0., 0., 1.]), fval=3.0, probability=0.1611328125, status=)\n", - "SolutionSample(x=array([1., 0., 1.]), fval=3.0, probability=0.20800781249999997, status=)\n", - "SolutionSample(x=array([0., 1., 1.]), fval=3.0, probability=0.16015625, status=)\n", - "SolutionSample(x=array([1., 1., 1.]), fval=4.0, probability=0.1728515625, status=)\n" + "SolutionSample(x=array([0., 1., 0.]), fval=-2.0, probability=0.123046875, status=)\n", + "SolutionSample(x=array([1., 1., 0.]), fval=0.0, probability=0.302734375, status=)\n", + "SolutionSample(x=array([1., 0., 0.]), fval=1.0, probability=0.0888671875, status=)\n", + "SolutionSample(x=array([0., 0., 1.]), fval=3.0, probability=0.22851562500000003, status=)\n", + "SolutionSample(x=array([1., 0., 1.]), fval=3.0, probability=0.12500000000000003, status=)\n", + "SolutionSample(x=array([0., 1., 1.]), fval=3.0, probability=0.025390624999999997, status=)\n", + "SolutionSample(x=array([1., 1., 1.]), fval=4.0, probability=0.10644531250000001, status=)\n" ] } ], @@ -332,7 +380,7 @@ }, { "cell_type": "code", - "execution_count": 20, + "execution_count": 14, "id": "9da37a65", "metadata": {}, "outputs": [], @@ -343,17 +391,17 @@ }, { "cell_type": "code", - "execution_count": 21, + "execution_count": 15, "id": "3768185e", "metadata": {}, "outputs": [ { "data": { "text/plain": [ - "1.5" + "1.7142857142857142" ] }, - "execution_count": 21, + "execution_count": 15, "metadata": {}, "output_type": "execute_result" } @@ -364,17 +412,17 @@ }, { "cell_type": "code", - "execution_count": 22, + "execution_count": 16, "id": "63c14a9b", "metadata": {}, "outputs": [ { "data": { "text/plain": [ - "1.9364916731037085" + "1.979486637221574" ] }, - "execution_count": 22, + "execution_count": 16, "metadata": {}, "output_type": "execute_result" } @@ -385,24 +433,23 @@ }, { "cell_type": "code", - "execution_count": 23, + "execution_count": 17, "id": "e4c4baac", "metadata": {}, "outputs": [ { "data": { "text/plain": [ - "{'x=0 y=1 z=0': 0.07031249999999999,\n", - " 'x=0 y=0 z=0': 0.0625,\n", - " 'x=1 y=1 z=0': 0.08496093750000001,\n", - " 'x=1 y=0 z=0': 0.08007812500000001,\n", - " 'x=0 y=0 z=1': 0.1611328125,\n", - " 'x=1 y=0 z=1': 0.20800781249999997,\n", - " 'x=0 y=1 z=1': 0.16015625,\n", - " 'x=1 y=1 z=1': 0.1728515625}" + "{'x=0 y=1 z=0': 0.123046875,\n", + " 'x=1 y=1 z=0': 0.302734375,\n", + " 'x=1 y=0 z=0': 0.0888671875,\n", + " 'x=0 y=0 z=1': 0.22851562500000003,\n", + " 'x=1 y=0 z=1': 0.12500000000000003,\n", + " 'x=0 y=1 z=1': 0.025390624999999997,\n", + " 'x=1 y=1 z=1': 0.10644531250000001}" ] }, - "execution_count": 23, + "execution_count": 17, "metadata": {}, "output_type": "execute_result" } @@ -419,18 +466,18 @@ }, { "cell_type": "code", - "execution_count": 24, + "execution_count": 18, "id": "d101a797", "metadata": {}, "outputs": [ { "data": { - "image/png": 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\n", 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", 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" + "
" ] }, - "execution_count": 24, + "execution_count": 18, "metadata": {}, "output_type": "execute_result" } @@ -440,6 +487,7 @@ ] }, { + "attachments": {}, "cell_type": "markdown", "id": "08aa7318", "metadata": {}, @@ -449,7 +497,7 @@ }, { "cell_type": "code", - "execution_count": 25, + "execution_count": 19, "id": "cca567a1", "metadata": {}, "outputs": [], @@ -461,7 +509,7 @@ }, { "cell_type": "code", - "execution_count": 26, + "execution_count": 20, "id": "4eaa9994", "metadata": {}, "outputs": [ @@ -469,9 +517,7 @@ "name": "stdout", "output_type": "stream", "text": [ - "optimal function value: -2.0\n", - "optimal value: [0. 1. 0.]\n", - "status: SUCCESS\n" + "fval=-2.0, x=0.0, y=1.0, z=0.0, status=SUCCESS\n" ] } ], @@ -482,7 +528,7 @@ }, { "cell_type": "code", - "execution_count": 27, + "execution_count": 21, "id": "0772b179", "metadata": {}, "outputs": [], @@ -496,7 +542,7 @@ }, { "cell_type": "code", - "execution_count": 28, + "execution_count": 22, "id": "96a34ccb", "metadata": {}, "outputs": [ @@ -506,7 +552,7 @@ "{'x=0 y=1 z=0': 1.0}" ] }, - "execution_count": 28, + "execution_count": 22, "metadata": {}, "output_type": "execute_result" } @@ -523,18 +569,18 @@ }, { "cell_type": "code", - "execution_count": 29, + "execution_count": 23, "id": "d3a65a6b", "metadata": {}, "outputs": [ { "data": { - "image/png": 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\n", + "image/png": 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", "text/plain": [ - "
" + "
" ] }, - "execution_count": 29, + "execution_count": 23, "metadata": {}, "output_type": "execute_result" } @@ -568,7 +614,7 @@ "name": "python", "nbconvert_exporter": "python", "pygments_lexer": "ipython3", - "version": "3.9.7" + "version": "3.8.10" } }, "nbformat": 4, diff --git a/qiskit_braket_provider/__init__.py b/qiskit_braket_provider/__init__.py index 1ac9c836..d1c6c366 100644 --- a/qiskit_braket_provider/__init__.py +++ b/qiskit_braket_provider/__init__.py @@ -2,7 +2,8 @@ from .providers import ( AWSBraketProvider, - AWSBraketJob, + AmazonBraketTask, AWSBraketBackend, + AWSBraketJob, BraketLocalBackend, ) diff --git a/qiskit_braket_provider/providers/__init__.py b/qiskit_braket_provider/providers/__init__.py index b1473056..dafae28b 100644 --- a/qiskit_braket_provider/providers/__init__.py +++ b/qiskit_braket_provider/providers/__init__.py @@ -17,9 +17,10 @@ AWSBraketBackend BraketLocalBackend AWSBraketProvider - AWSBraketJob + AmazonBraketTask """ from .braket_backend import AWSBraketBackend, BraketLocalBackend from .braket_provider import AWSBraketProvider +from .braket_job import AmazonBraketTask from .braket_job import AWSBraketJob diff --git a/qiskit_braket_provider/providers/braket_backend.py b/qiskit_braket_provider/providers/braket_backend.py index 70ae66df..a5d2f393 100644 --- a/qiskit_braket_provider/providers/braket_backend.py +++ b/qiskit_braket_provider/providers/braket_backend.py @@ -19,7 +19,7 @@ convert_qiskit_to_braket_circuits, wrap_circuits_in_verbatim_box, ) -from .braket_job import AWSBraketJob +from .braket_job import AmazonBraketTask from .. import version from ..exception import QiskitBraketException @@ -100,7 +100,7 @@ def control_channel(self, qubits: Iterable[int]): def run( self, run_input: Union[QuantumCircuit, List[QuantumCircuit]], **options - ) -> AWSBraketJob: + ) -> AmazonBraketTask: convert_input = ( [run_input] if isinstance(run_input, QuantumCircuit) else list(run_input) ) @@ -125,10 +125,10 @@ def run( logger.error("State of %s: %s.", task.id, task.state()) raise ex - job_id = TASK_ID_DIVIDER.join(task.id for task in tasks) + task_id = TASK_ID_DIVIDER.join(task.id for task in tasks) - return AWSBraketJob( - job_id=job_id, + return AmazonBraketTask( + task_id=task_id, tasks=tasks, backend=self, shots=shots, @@ -179,19 +179,19 @@ def __init__( # pylint: disable=too-many-arguments self._device = device self._target = aws_device_to_target(device=device) - def retrieve_job(self, job_id: str) -> AWSBraketJob: + def retrieve_job(self, task_id: str) -> AmazonBraketTask: """Return a single job submitted to AWS backend. Args: - job_id: ID of the job to retrieve. + task_id: ID of the task to retrieve. Returns: The job with the given ID. """ - task_ids = job_id.split(TASK_ID_DIVIDER) + task_ids = task_id.split(TASK_ID_DIVIDER) - return AWSBraketJob( - job_id=job_id, + return AmazonBraketTask( + task_id=task_id, backend=self, tasks=[AwsQuantumTask(arn=task_id) for task_id in task_ids], ) @@ -253,8 +253,8 @@ def run(self, run_input, **options): braket_circuits, **options ) tasks: List[AwsQuantumTask] = batch_task.tasks - job_id = TASK_ID_DIVIDER.join(task.id for task in tasks) + task_id = TASK_ID_DIVIDER.join(task.id for task in tasks) - return AWSBraketJob( - job_id=job_id, tasks=tasks, backend=self, shots=options.get("shots") + return AmazonBraketTask( + task_id=task_id, tasks=tasks, backend=self, shots=options.get("shots") ) diff --git a/qiskit_braket_provider/providers/braket_job.py b/qiskit_braket_provider/providers/braket_job.py index fd2a472f..63a96f12 100644 --- a/qiskit_braket_provider/providers/braket_job.py +++ b/qiskit_braket_provider/providers/braket_job.py @@ -2,6 +2,7 @@ import os from datetime import datetime from typing import List, Optional, Union +from warnings import warn from braket.aws import AwsQuantumTask from braket.tasks import GateModelQuantumTaskResult @@ -77,26 +78,26 @@ def _get_result_from_aws_tasks( return experiment_results -class AWSBraketJob(JobV1): - """AWSBraketJob.""" +class AmazonBraketTask(JobV1): + """AmazonBraketTask.""" def __init__( self, - job_id: str, + task_id: str, backend: BackendV2, tasks: Union[List[LocalQuantumTask], List[AwsQuantumTask]], - **metadata: Optional[dict] + **metadata: Optional[dict], ): - """AWSBraketJob for local execution of circuits. + """AmazonBraketTask for local execution of circuits. Args: - job_id: id of the job + task_id: id of the task backend: Local simulator tasks: Executed tasks **metadata: """ - super().__init__(backend=backend, job_id=job_id, metadata=metadata) - self._job_id = job_id + super().__init__(backend=backend, job_id=task_id, metadata=metadata) + self._task_id = task_id self._backend = backend self._metadata = metadata self._tasks = tasks @@ -118,12 +119,16 @@ def shots(self) -> int: def submit(self): return + def task_id(self) -> str: + """Return a unique id identifying the task.""" + return self._task_id + def result(self) -> Result: experiment_results = _get_result_from_aws_tasks(tasks=self._tasks) return Result( backend_name=self._backend, backend_version=self._backend.version, - job_id=self._job_id, + job_id=self._task_id, qobj_id=0, success=self.status() not in AwsQuantumTask.NO_RESULT_TERMINAL_STATES, results=experiment_results, @@ -147,3 +152,32 @@ def status(self): status = JobStatus.RUNNING return status + + +class AWSBraketJob(AmazonBraketTask): + """AWSBraketJob.""" + + def __init_subclass__(cls, **kwargs): + """This throws a deprecation warning on subclassing.""" + warn(f"{cls.__name__} is deprecated.", DeprecationWarning, stacklevel=2) + super().__init_subclass__(**kwargs) + + def __init__( + self, + job_id: str, + backend: BackendV2, + tasks: Union[List[LocalQuantumTask], List[AwsQuantumTask]], + **metadata: Optional[dict], + ): + """This throws a deprecation warning on initialization.""" + warn( + f"{self.__class__.__name__} is deprecated.", + DeprecationWarning, + stacklevel=2, + ) + super().__init__(task_id=job_id, backend=backend, tasks=tasks, **metadata) + self._job_id = job_id + self._backend = backend + self._metadata = metadata + self._tasks = tasks + self._date_of_creation = datetime.now() diff --git a/tests/providers/test_braket_backend.py b/tests/providers/test_braket_backend.py index 61f1b769..197906cd 100644 --- a/tests/providers/test_braket_backend.py +++ b/tests/providers/test_braket_backend.py @@ -214,7 +214,7 @@ def test_random_circuits(self): @unittest.skip("Call to external resources.") def test_retrieve_job(self): - """Tests retrieve job by id.""" + """Tests retrieve task by id.""" backend = AWSBraketProvider().get_backend("SV1") circuits = [ transpile( @@ -223,13 +223,13 @@ def test_retrieve_job(self): for seed in range(3) ] job = backend.run(circuits, shots=10) - job_id = job.job_id() - retrieved_job = backend.retrieve_job(job_id) + task_id = job.task_id() + retrieved_job = backend.retrieve_job(task_id) job_result: Result = job.result() retrieved_job_result: Result = retrieved_job.result() - self.assertEqual(job_result.job_id, retrieved_job_result.job_id) + self.assertEqual(job_result.task_id, retrieved_job_result.task_id) self.assertEqual(job_result.status, retrieved_job_result.status) self.assertEqual( job_result.backend_version, retrieved_job_result.backend_version diff --git a/tests/providers/test_braket_job.py b/tests/providers/test_braket_job.py index 4b2259da..5e171f4b 100644 --- a/tests/providers/test_braket_job.py +++ b/tests/providers/test_braket_job.py @@ -4,12 +4,48 @@ from qiskit.providers import JobStatus -from qiskit_braket_provider.providers import AWSBraketJob, BraketLocalBackend +from qiskit_braket_provider.providers import ( + AmazonBraketTask, + BraketLocalBackend, + AWSBraketJob, +) from tests.providers.mocks import MOCK_LOCAL_QUANTUM_TASK +class TestAmazonBraketTask(TestCase): + """Tests AmazonBraketTask.""" + + def _get_task(self): + return AmazonBraketTask( + backend=BraketLocalBackend(name="default"), + task_id="AwesomeId", + tasks=[MOCK_LOCAL_QUANTUM_TASK], + shots=10, + ) + + def test_task(self): + """Tests task.""" + task = self._get_task() + + self.assertTrue(isinstance(task, AmazonBraketTask)) + self.assertEqual(task.shots, 10) + + self.assertEqual(task.status(), JobStatus.DONE) + + def test_result(self): + """Tests result.""" + task = self._get_task() + + self.assertEqual(task.result().job_id, "AwesomeId") + self.assertEqual(task.result().results[0].data.counts, {"01": 1, "10": 2}) + self.assertEqual(task.result().results[0].data.memory, ["10", "10", "01"]) + self.assertEqual(task.result().results[0].status, "COMPLETED") + self.assertEqual(task.result().results[0].shots, 3) + self.assertEqual(task.result().get_memory(), ["10", "10", "01"]) + + class TestAWSBraketJob(TestCase): - """Tests AWSBraketJob.""" + """Tests AWSBraketJob""" def _get_job(self): return AWSBraketJob( @@ -19,16 +55,17 @@ def _get_job(self): shots=10, ) - def test_job(self): + def test_AWS_job(self): """Tests job.""" job = self._get_job() self.assertTrue(isinstance(job, AWSBraketJob)) self.assertEqual(job.shots, 10) + self.assertEqual(job.result().job_id, "AwesomeId") self.assertEqual(job.status(), JobStatus.DONE) - def test_result(self): + def test_AWS_result(self): """Tests result.""" job = self._get_job()