diff --git a/tutorials/submitting-transpiled-circuits/notebook.ipynb b/tutorials/submitting-transpiled-circuits/notebook.ipynb new file mode 100644 index 00000000000..419b8affe2b --- /dev/null +++ b/tutorials/submitting-transpiled-circuits/notebook.ipynb @@ -0,0 +1,377 @@ +{ + "cells": [ + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "# Submit pre-transpiled circuits\n", + "\n", + "## Background\n", + "\n", + "To get the best performance from your circuits, the Qiskit Runtime service will pass all circuits through Qiskit's transpiler before running them. While this is usually a good thing, we might sometimes want to disable this by passing the argument `skip_transpilation=True` to the primitive we're using.\n", + "\n", + "For example, we may know better than the transpiler in some cases, or want to target a specific subset of qubits on a specific device. In this tutorial, we'll disable automatic transpilation to test the performance of different transpiler settings. This example will take you through the full process of creating, transpiling, and submitting circuits.\n", + "\n", + "## Setup\n" + ] + }, + { + "cell_type": "code", + "execution_count": 2, + "metadata": {}, + "outputs": [], + "source": [ + "# General\n", + "import warnings\n", + "\n", + "warnings.filterwarnings(\"ignore\")\n", + "\n", + "# Create circuit to test transpiler on\n", + "from qiskit import QuantumCircuit, transpile\n", + "from qiskit.circuit.library import GroverOperator, Diagonal\n", + "\n", + "# Use Statevector object to calculate the ideal output\n", + "from qiskit.quantum_info import Statevector\n", + "from qiskit.visualization import plot_histogram\n", + "\n", + "# Qiskit Runtime\n", + "from qiskit_ibm_runtime import QiskitRuntimeService, Batch, Sampler" + ] + }, + { + "cell_type": "code", + "execution_count": 3, + "metadata": {}, + "outputs": [ + { + "data": { + "text/plain": [ + "'ibmq_mumbai'" + ] + }, + "execution_count": 3, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "# To run on hardware, select the backend with the fewest number of jobs in the queue\n", + "service = QiskitRuntimeService(channel=\"ibm_quantum\")\n", + "backend = service.least_busy(operational=True, simulator=False)\n", + "backend.name" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "## Step 1: Map classical inputs to a quantum problem\n", + "\n", + "In the following code cell, we create a small circuit that our transpiler will try to optimize. In this example, we create a circuit that carries out Grover's algorithm, with an oracle that marks the state `111`. We then simulate the ideal distribution (what we'd expect to measure if we ran this on a perfect quantum computer, an infinite number of times) for comparison later.\n" + ] + }, + { + "cell_type": "code", + "execution_count": 4, + "metadata": {}, + "outputs": [ + { + "data": { + "image/png": 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", + "text/plain": [ + "
" + ] + }, + "execution_count": 4, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "oracle = Diagonal([1] * 7 + [-1])\n", + "qc = QuantumCircuit(3)\n", + "qc.h([0, 1, 2])\n", + "qc = qc.compose(GroverOperator(oracle))\n", + "\n", + "qc.draw(output=\"mpl\", style=\"iqp\")" + ] + }, + { + "cell_type": "code", + "execution_count": 5, + "metadata": {}, + "outputs": [ + { + "data": { + "image/png": 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TNWnSJN1yyy0aMWKEbrrpJlmWle/tJiQkSMr8WjUnAQEBznVyEx8fr/T0dJ04cULPP/+8XnnlFd1zzz1KTU3V+++/r//+97/q27ev9u7dK19f3xy3MXXqVD333HPZ2leuXKny5ctLkurUqaPWrVtr165dioyMdK7TqFEjNW7cWFu2bFFsbKyzvVWrVgoJCdHGjRt1+vRpZ3v79u1VrVo1rVy50uUH17VrV5UrV05Lly51qaF37946e/as1q1b52zz9vZWnz59FBcXp7CwMGe7v7+/unXrpqioKO3cudPZXrVqVXXo0EHh4eHat2+fs50+0Sf6RJ/oE32yR59ulacV9c9p27Zt+aqjUC+ASE5O1tdff63Zs2c7vwqtWbOm7r//fj3wwAOqWbPmRbfRq1cvrVq1SuHh4apfv3625TVr1lRSUlKege7o0aPO13rsscc0ffp0l+WDBg3SggUL9Nlnn+nuu+/OtS8XHpmrXbu24uLinCchXh6ffOgTfaJP9Ik+0aeS16eHZ3j+yNz7/y7an1N8fLyqVKly0QsgCvUqgLJlyyo0NFTR0dHat2+foqOjdfjwYT333HOaMmWKHnjgAb366qvOI1s5yToil1tYS0xMVKVKlfKs4/yjev369cu2vF+/flqwYIF++eWXXMNc2bJlVbZs2WztPj4+8vFx3YG8vLzk5eWVbd3cLrLIrf3C7brT7nA45HBkPxUyt/bcaqdP9Kmg7fSJPkn0KbcaC9pOnwreJ0/w1M8p2+vla618WLlypQYOHKhatWrpySeflGVZeuaZZ/Tnn39qwYIFuuaaa/Tee+/pkUceyXM7WefK5XReXExMjJKSknI8n+58fn5+ziNzFStWzLY8q+3s2bP56BkAAEDJdUlh7siRI3rhhRdUr1493XzzzVq4cKG6du2qhQsX6tChQ3ruuedUr1493XHHHQoLC1Pv3r31v//9L89tdu7cWVJmOLzQihUrXNbJS7du3SRJf/zxR7ZlWW1169a96HYAAABKMrfD3C233KK6detq8uTJOnv2rJ588klFRERo2bJluu2223I8XNihQ4eLXrzQvXt31atXT1988YXLyYMJCQmaMmWKypQpo6FDhzrbo6OjtXfv3mzbffDBByVJL730kk6dOuVsj4mJ0ZtvvimHw6H+/fu70XMAAICSw+1z5pYuXapu3bpp1KhRuv322/P1vW7fvn1Vo0aNvAvy9tasWbMUGhqqTp06uUzndejQIU2bNs3liNqECRM0Z84cffzxxxo+fLizvUOHDho7dqxef/11tWjRQn379lVqaqr+97//6fjx45oyZYoaNmzobvcBAABKBLfD3P79+3O82jQvV199ta6++uqLrte1a1f9+OOPmjx5subPn6/U1FQ1b95cL7/8sgYNGpTv13vttdfUvHlzzZgxQ5988oksy1Lr1q313nvv6fbbby9Q7QAAACWR27cmue+++3TbbbfleLVolsWLF+ubb77RRx995HaBJQVzswIAUHIwN+s/3D5n7pNPPnE5py0nv/76a77mUQUAAIB7Cu3WJDk5d+4cE9oDAAAUoUtKWrlN02WMUVRUlJYtW3bRCx4AAADgvgIdmcuaXiLrtiPPPvus8/H5/7y9vXXllVdq+/btGjx4cJEUDgAAgAIemevUqZPzaNzGjRtVp06dHG+86+XlpcqVK6tbt24aMWJEoRQKAACA7AoU5tavX+/8f4fDoXvvvVeTJk0q7JoAAACQT26fM5eRkVGYdQAAAMANRXo1KwAAAIpWvo/M3XfffbIsS1OmTFFQUJDuu+++fD3PsizNnj3b7QIBAACQu3zPAOFwOGRZlvbs2aOGDRvK4cjfQT3LspSenn5JRZYEzAABAEDJwQwQ/8j3kbm//vpLklSzZk2XxwAAAPCcfIe5kJCQPB8DAACg+HEBBAAAgI3l+8hcZGSk2y9Sp04dt58LAACA3OU7zNWtWzfXuVjzYlmW0tLSCvw8AAAAXFy+w9zQoUPdCnMAAAAoOvkOc5988kkRlgEAAAB3cAEEAACAjRHmAAAAbIzpvAAAAGyM6bzyiem8AAAoOZjO6x9M5wUAAGBjTOcFAABgY1wAAQAAYGOXHOa+/fZb3XrrrapTp44CAwNVp04d3Xbbbfruu+8KoTwAAADkJd9fs14oLS1Nd911lxYuXChjjLy9vVWlShXFxMTo+++/16JFi9S/f3998cUX8vZ2+2UAAACQB7ePzE2dOlVff/21brzxRv3www86d+6coqOjde7cOW3cuFEdO3bUwoUL9dJLLxVmvQAAADhPvm9NcqF69erJ19dXu3btyvHIW2pqqlq0aKHk5GQdOHDgkgv1NG5NAgBAycGtSf7h9pG56Oho9e3bN9evUH18fNS3b19FR0e7+xIAAAC4CLfDXO3atZWUlJTnOmfOnFGdOnXcfQkAAABchNth7oEHHtCCBQtyPfJ25MgRzZ8/Xw888IDbxQEAACBv+b7MNDIy0uXxwIED9dNPP6l169YaM2aMOnbsqKCgIB07dkw//PCD3nzzTXXs2FEDBgwo9KIBAACQqcBzs17IGJNre9bz0tLSLrFMz+MCCAAASg4ugPhHvo/MDR06NMfQBgAAAM/Jd5j75JNPirAMAAAAuIO5WQEAAGyMMAcAAGBjlzRp6unTp/XOO+9o9erVOnr0qJKTk7OtY1mWIiIiLuVlAAAAkAu3w1xsbKw6dOigiIgIBQQEOK+4SElJ0dmzZyVJNWrUkI+PT6EVCwAAAFduf8367LPPKiIiQp9++qlOnjwpSXr88cd15swZbd68WW3btlXdunX1+++/F1qxAAAAcOV2mFu6dKm6d++uu+++O9stS6677jotW7ZMBw8e1HPPPXfJRQIAACBnboe56OhotW7d2vnYy8vL+fWqJFWqVEk333yzFixYcGkVAgAAIFduh7nAwEClpqY6H1eqVEmHDx92WScgIEDHjh1zvzoAAADkye0wV69ePR08eND5uHXr1lq1apVOnDghSTp79qwWLVqkOnXqXHKRAAAAyJnbYa5Xr15as2aN/v77b0nSqFGjdPz4cbVs2VIDBgzQ1VdfrYiICA0fPrywagUAAMAF3A5zDz74oD788ENnmPvXv/6lV199VWfOnNHChQsVExOjsWPHavz48YVWLAAAAFxZxhhTmBtMT09XXFycqlWrlu0qVzvLuo9eQkKCAgICPF0OAACXtRHTPV2B9OGYot1+frPHJc0AkRMvLy8FBQUV9mYBAACQg0sOc9HR0Zo3b5527NihhIQEBQYGqnXr1ho8eLCqV69eGDUCAAAgF5cU5mbMmKHx48crOTlZ539bO3fuXD311FOaNm2aHn744UsuEgAAADlzO8zNmzdPjz76qK644go99dRTuvHGGxUUFKRjx45p48aNevPNN53LBw4cWJg1AwAA4P9z+wKIa665RocPH9bOnTtVo0aNbMsPHz6s1q1bq06dOtq2bdslF+ppXAABAEDJwQUQ/3D71iR79uzRwIEDcwxyklSrVi0NGDBAe/bscfclAAAAcBFuh7mKFSvKz88vz3UqVKigihUruvsSAAAAuAi3w1y/fv20aNEipaWl5bg8NTVVixYt0q233up2cQAAAMib22HulVdekZ+fn3r16qVNmza5LAsLC1OvXr3k7++vl1566ZKLBAAAQM7yfTVrvXr1srWlpKRo+/btuuGGG+Tt7a0rrrhCcXFxzqN11atX1zXXXKOIiIjCqxgAAABO+Q5zGRkZ2abn8vHxUZ06dVzaLrwgIiMj4xLKAwAAQF7yHeYOHjxYhGUAAADAHW6fMwcAAADPu+S5WSUpLS1N+/btU2JiogICAtSoUSN5exfKpgEAAJCHSzoyFx8frxEjRigwMFAtWrRQx44d1aJFC1WsWFEjR47UiRMnCqtOAAAA5MDtw2fx8fFq166d/vzzT1WuXFk33nijqlevrpiYGP3yyy+aNWuWNmzYoLCwMFWuXLkwawYAAMD/5/aRuRdeeEF//vmnxo8fr0OHDmn58uX6+OOPtWzZMh06dEhPPvmkwsPD9eKLLxZmvQAAADiPZYwx7jyxXr16qlu3rtauXZvrOt26ddPBgwd14MABtwssKfI72S0AACh6I6Z7ugLpwzFFu/38Zg+3j8wdPXpU7du3z3Od9u3b6+jRo+6+BAAAAC7C7TAXGBioQ4cO5bnOoUOHFBgY6O5LAAAA4CLcDnOdO3fWV199pdWrV+e4fM2aNfrqq6/UpUsXd18CAAAAF+H21ayTJ0/WkiVLFBoaqt69e6tz584KCgrSsWPHtH79ei1btkzly5fXpEmTCrNeAAAAnMftMNesWTOtWLFCw4cP15IlS7RkyRJZlqWs6ymuuuoqffLJJ2rWrFmhFQsAAABXlzRNQ8eOHRUeHq6ffvpJO3bscM4A0bp1a91www2yLKuw6gQAAEAO3A5z9913n5o3b67HH39cHTt2VMeOHQuzLgAAAOSD2xdAfPHFFzp+/Hhh1gIAAIACcjvMXXXVVYqOji7MWgAAAFBAboe5++67T0uWLNGRI0cKsx6nrVu3qnfv3qpYsaL8/PzUrl07LViwwO3tnTx5UjVr1pRlWbrpppsKsVIAAADPcfucuf79+2vdunXq0KGD/u///k/XXXedgoKCcrzooU6dOgXa9rp16xQaGipfX18NHjxY/v7+WrhwoQYNGqSoqCiNGzeuwPWOHj1aCQkJBX4eAABASeb23KwOh8N5K5K8rlq1LEtpaWn53m5aWpoaN26sw4cPa9OmTWrVqpUkKSEhQW3bttXBgwe1f/9+hYSE5HubCxcu1B133KF33nlHo0ePVmhoqJYvX57v50vMzQoAQEnC3Kz/cPvI3NChQ4vk1iNr165VRESE7r33XmeQkzKnD5s4caKGDx+uOXPm5PtmxLGxsXrooYd0zz33qE+fPho9enSh1wwAAOApboe5Tz75pBDL+Mf69eslSb169cq2LDQ0VJK0YcOGfG/vwQcflJeXl958802+ZgUAAKXOJd00uCiEh4dLkho0aJBtWXBwsCpUqOBc52Lmzp2rb775Rt99950qVapEmAMAAKXOJYe55ORkLV26VDt27FBCQoICAwPVunVr9e7dW2XLli3w9rICV2BgYI7LAwIC8hXKjh49qn//+9+68847deuttxa4juTkZCUnJzsfJyYmSpJSU1OVmpoqKfO8QS8vL6WnpysjI8O5blZ7Wlqazj8l0cvLSw6HI9f2rO1m8fbO/PFceM5hbu0+Pj7KyMhQenq6s82yLHl7e+fanlvt9Ik+0Sf6RJ/oU8nuk488rTh+TvlxSWHu+++/18iRIxUbG+vyw7csS9WqVdMHH3ygvn37XspLuO2BBx6Qj4+P3nrrLbeeP3XqVD333HPZ2leuXKny5ctLyrxKt3Xr1tq1a5ciIyOd6zRq1EiNGzfWli1bFBsb62xv1aqVQkJCtHHjRp0+fdrZ3r59e1WrVk0rV650+cF17dpV5cqV09KlS11q6N27t86ePat169Y527y9vdWnTx/FxcUpLCzM2e7v769u3bopKipKO3fudLZXrVpVHTp0UHh4uPbt2+dsp0/0iT7RJ/pEn+zRp4IfqClsRf1z2rZtW77qcPtq1jVr1uimm26Sl5eX7rnnHt14440KCgrSsWPHtHHjRs2dO1fp6elasWKFunXrlu/tDhgwQF9//bV++eUXtWnTJttyf39/VapUyaXTF5ozZ46GDx+ur776SnfccYez/eDBg7ryyivzdTVrTkfmateurbi4OOcVJZfHJx/6RJ/oE32iT/Sp5PXp4RmePzL3/r+L9ucUHx+vKlWqXPRqVrfDXMeOHbVr1y79/PPPuvrqq7Mt37Vrl2644Qa1atVKP/zwQ763O3HiRE2dOlVffvmlBg8e7LIsJiZG1atXV7du3bRmzZpctzFmzBi9+eabF32tli1buiTnvHBrEgAASg5uTfIPt79m3bFjh+66664cg5wktWjRQgMHDtS8efMKtN3OnTtr6tSpWrlyZbYwt2LFCuc6eWnfvr2SkpKytSclJWn+/PmqVauWQkNDC3wzYwAAgJLG7TBXvnx5Va1aNc91qlWr5jy/LL+6d++uevXq6YsvvtC///1vl5sGT5kyRWXKlNHQoUOd60dHRyshIUHVq1d3XjQxaNAgDRo0KNu2Dx48qPnz56tZs2aaNWtWgeoCAAAoidyem7VHjx5avXp1nuusXr1aPXv2LNB2vb29NWvWLGVkZKhTp04aOXKkxo0bp5YtW2r//v2aMmWK6tat61x/woQJatKkib799lt3ugEAAGBrboe5adOm6fjx4xo6dKiioqJclkVFRemee+5RXFycpk2bVuBtd+3aVT/++KNuuOEGzZ8/X++++66CgoI0b948t+ZlBQAAKK3cvgCiW7duOnnypHbt2iUvLy/VqVPHeTVrZGSk0tPT1aJFC1WqVMn1BS0rz4sXSiougAAAoOTgAoh/uH3OXNa0W1LmJcgHDhzQgQMHXNb59ddfsz2vKOZzBQAAuFy5HebOvx8KAAAAPMPtc+YAAADgeYUW5iIjI7Vx48bC2hwAAADyodDC3Mcff6yuXbsW1uYAAACQD3zNCgAAYGOEOQAAABsjzAEAANhYoYW5wMBAJq4HAAAoZoUW5saMGaO//vqrsDYHAACAfOBrVgAAABvL9wwQWfeQa9u2rXx9fQt0T7lOnToVvDIAAABcVL7DXJcuXWRZlvbs2aOGDRs6H+dHenq62wUCAAAgd/kOc5MmTZJlWbriiitcHgMAAMBz8h3mnn322TwfAwAAoPhxAQQAAICNuR3mTp8+rQMHDig1NdWlff78+RoyZIjuv/9+bd++/ZILBAAAQO7y/TXrhf7v//5Pc+fO1bFjx+Tj4yNJevfddzV69GgZYyRJ8+bN07Zt29S4cePCqRYAAAAu3D4yt2HDBvXo0UPly5d3tr300kuqWbOmNm7cqAULFsgYo1dffbVQCgUAAEB2bh+Zi46O1k033eR8vGfPHkVFRemVV15Rx44dJUlff/11ge5HBwAAgIJx+8hccnKyypQp43y8YcMGWZalXr16Odvq1aunI0eOXFqFAAAAyJXbYa5WrVratWuX8/HixYtVuXJltWjRwtl24sQJVahQ4dIqBAAAQK7c/pr15ptv1owZM/TEE0/I19dXy5cv19ChQ13W2b9/v+rUqXPJRQIAACBnboe5CRMmaNGiRXr99dclSdWrV9fzzz/vXH78+HH99NNPGj169KVXCQAAgBy5HeaCg4P1+++/a82aNZKkTp06KSAgwLk8Li5Or776qkJDQy+9SgAAAOTI7TAnSeXKldMtt9yS47KmTZuqadOml7J5AAAAXATTeQEAANjYJR2ZS09P14IFC7R69WodPXpUycnJ2daxLMv5VSwAAAAKl9th7syZM+rVq5c2bdokY4wsy3JO4yXJ+diyrEIpFAAAANm5/TXrf//7X4WFhem5555TXFycjDF69tlnFR0drfnz56tevXoaMGBAjkfrAAAAUDjcDnPffPON2rVrp6efflqVK1d2tgcFBWnAgAFat26dVq9ezdysAAAARcjtMBcZGal27dr9syGHw+UoXK1atdSnTx/NmTPn0ioEAABArtwOc35+fnI4/nl6YGCgoqOjXdYJDg5WZGSk+9UBAAAgT26HuZCQEJegdvXVV2vt2rXOo3PGGK1Zs0bVq1e/9CoBAACQI7fDXPfu3bVu3TqlpaVJkoYNG6bIyEi1b99e48ePV8eOHbVz507179+/0IoFAACAK7dvTTJixAhVqVJFsbGxql69uu677z7t2LFDM2fO1M6dOyVJ/fv317PPPltIpQIAAOBCljn/5nCFIDY2VgcOHFBISIiCg4MLc9MelZiYqMDAQCUkJLjMQQsAAIrfiOmerkD6cEzRbj+/2eOSZoDISdWqVVW1atXC3iwAAABywNysAAAANub2kbl69erlaz3LshQREeHuywAAACAPboe5jIyMHOddTUhI0KlTpyRJ1atXV5kyZdwuDgAAAHlzO8wdPHgwz2Vjx47VsWPHtGrVKndfAgAAABdRJOfM1a1bV/Pnz9fJkyf11FNPFcVLAAAAQEV4AYSPj4969uypBQsWFNVLAAAAXPaK9GrWv//+W/Hx8UX5EgAAAJe1IgtzP/zwg7788ks1atSoqF4CAADgsuf2BRDdunXLsT0tLU1HjhxxXiAxadIkd18CAAAAF+F2mFu/fn2O7ZZlqVKlSurVq5fGjh2rnj17uvsSAAAAuIhLus8cAAAAPOuS52Y9fvy4jhw5ooyMDNWsWVPBwcGFURcAAADywa0LIJKTk/XKK6+oQYMGql69uq699lq1bdtWNWvW1BVXXKHHH388z5sKAwAAoHAUOMxFRUXpuuuu04QJExQREaHq1aurbdu2atu2rapXr674+Hi9+eabuvbaa7V69Wrn86Kjo7nnHAAAQCErUJhLTU1V7969tXv3bt15553as2ePDh8+rLCwMIWFhenw4cPas2ePhgwZovj4eN122206ePCgIiIi1LFjR+3du7eo+gEAAHBZKtA5c++//75+//13TZ48WZMnT85xnUaNGumzzz5Tw4YNNXnyZA0ZMkQHDx5UXFyc2rRpUyhFAwAAIFOBjswtWLBA9evXz9e9455++mk1aNBAYWFhOnfunFasWKE+ffq4XSgAAACyK1CY++OPP9SrVy9ZlnXRdS3Lcq67efNmdenSxd0aAQAAkIsChbmkpCQFBgbme/2AgAB5e3urfv36BS4MAAAAF1egMFetWjX9+eef+V4/IiJC1apVK3BRAAAAyJ8Chbn27dtr2bJliomJuei6MTExWrJkiTp27Oh2cQAAAMhbgcLcgw8+qKSkJN1+++2Ki4vLdb0TJ07o9ttv199//61Ro0ZdcpEAAADIWYFuTdK1a1eNGDFCH374oZo0aaJRo0apW7duql27tqTMGwqvWbNGH374oeLi4jRy5EgufAAAAChCBZ6bdebMmQoICNAbb7yhqVOnaurUqS7LjTFyOBx64oknsi0DAABA4SpwmPPy8tKrr76qkSNH6pNPPlFYWJjzHLrg4GB16NBBw4YNU4MGDQq9WAAAALgqcJjL0qBBA7344ouFWQsAAAAKqEAXQAAAAKBkIcwBAADYGGEOAADAxghzAAAANkaYAwAAsDHCHAAAgI0R5gAAAGyMMAcAAGBjhDkAAAAbI8wBAADYGGEOAADAxkpsmNu6dat69+6tihUrys/PT+3atdOCBQvy9VxjjJYtW6aHHnpILVq0UGBgoMqXL6+WLVtqypQpOnfuXBFXDwAAUDy8PV1ATtatW6fQ0FD5+vpq8ODB8vf318KFCzVo0CBFRUVp3LhxeT4/OTlZvXv3VtmyZdWlSxeFhobq3LlzWrFihZ566il99913Wr9+vcqXL19MPQIAACgaljHGeLqI86Wlpalx48Y6fPiwNm3apFatWkmSEhIS1LZtWx08eFD79+9XSEhIrttITU3VK6+8oocffliVKlVyae/fv78WLVqkV155RePHj893XYmJiQoMDFRCQoICAgLc7h8AALh0I6Z7ugLpwzFFu/38Zo8S9zXr2rVrFRERobvuussZ5CQpMDBQEydOVEpKiubMmZPnNnx8fPTUU0+5BLms9gkTJkiSNmzYUOi1AwAAFLcSF+bWr18vSerVq1e2ZaGhoZIuLYj5+PhIkry9S+Q3zAAAAAVS4hJNeHi4JKlBgwbZlgUHB6tChQrOddzx0UcfSco5LJ4vOTlZycnJzseJiYmSMr+qTU1NlSQ5HA55eXkpPT1dGRkZznWz2tPS0nT+t9heXl5yOBy5tmdtN0tW4ExLS8tXu4+PjzIyMpSenu5ssyxL3t7eubbnVjt9ok/0iT7RJ/pUsvvkI08rjp9TfpS4MJeQkCAp82vVnAQEBDjXKahly5bp/fffV5MmTXT//ffnue7UqVP13HPPZWtfuXKl88KJOnXqqHXr1tq1a5ciIyOd6zRq1EiNGzfWli1bFBsb62xv1aqVQkJCtHHjRp0+fdrZ3r59e1WrVk0rV650+cF17dpV5cqV09KlS11q6N27t86ePat169Y527y9vdWnTx/FxcUpLCzM2e7v769u3bopKipKO3fudLZXrVpVHTp0UHh4uPbt2+dsp0/0iT7RJ/pEn+zRp1vlaUX9c9q2bVu+6ihxF0D06tVLq1atUnh4uOrXr59tec2aNZWUlFTgQLd161Z1795d3t7e+uGHH9SsWbM818/pyFzt2rUVFxfnPAnx8vjkQ5/oE32iT/SJPpW8Pj08w/NH5t7/d9H+nOLj41WlSpWLXgBR4o7MZR2Ryy2sJSYmZruw4WJ++eUX9erVSw6HQytWrLhokJOksmXLqmzZstnafXx8nOfdZfHy8pKXl1e2dXM7Ly+39gu36067w+GQw5H9VMjc2nOrnT7Rp4K20yf6JNGn3GosaDt9KnifPMFTP6dsr5evtYpR1rlyOZ0XFxMTo6SkpBzPp8vNL7/8op49eyojI0MrVqzQddddV2i1AgAAeFqJC3OdO3eWlHlu2oVWrFjhss7FZAW59PR0LV++XNdff33hFQoAAFAClLgw1717d9WrV09ffPGFy8mDCQkJmjJlisqUKaOhQ4c626Ojo7V3795sX8tu27ZNPXv2VFpampYtW6b27dsXVxcAAACKTYk7Z87b21uzZs1SaGioOnXq5DKd16FDhzRt2jTVrVvXuf6ECRM0Z84cffzxxxo+fLgkKT4+Xj179tSpU6d00003adWqVVq1apXL61SsWFFjxowpvo4BAAAUgRIX5qTMS55//PFHTZ48WfPnz1dqaqqaN2+ul19+WYMGDbro8xMTE3Xy5ElJ0vLly7V8+fJs64SEhBDmAACA7ZW4W5OUVMzNCgBAycHcrP8ocefMAQAAIP8IcwAAADZGmAMAALAxwhwAAICNEeYAAABsjDAHAABgY4Q5AAAAGyPMAQAA2BhhDgAAwMYIcwAAADZGmAMAALAxwhwAAICNEeYAAABsjDAHAABgY4Q5AAAAGyPMAQAA2BhhDgAAwMYIcwAAADZGmAMAALAxwhwAAICNEeYAAABsjDAHAABgY4Q5AAAAGyPMAQAA2BhhDgAAwMYIcwAAADZGmAMAALAxwhwAAICNEeYAAABsjDAHAABgY4Q5AAAAGyPMAQAA2BhhDgAAwMYIcwAAADZGmAMAALAxwhwAAICNEeYAAABsjDAHAABgY4Q5AAAAGyPMAQAA2BhhDgAAwMYIcwAAADZGmAMAALAxwhwAAICNEeYAAABsjDAHAABgY4Q5AAAAGyPMAQAA2BhhDgAAwMYIcwAAADZGmAMAALAxwhwAAICNEeYAAABsjDBXgsyYMUN169aVr6+vrr/+em3ZsiXP9b/66is1btxYvr6+at68uZYuXeqy/Nlnn1Xjxo3l5+enSpUqqUePHtq8ebPLOi+++KI6dOig8uXLq2LFioXdJbcwDpkYh0yMA2OQhXHIxDjgQoS5EmL+/PkaO3asJk+erO3bt6tly5YKDQ3V8ePHc1z/559/1p133qn7779fO3bs0G233abbbrtNu3fvdq7TsGFDvfPOO/rtt9/0448/qm7duurVq5diY2Od66SkpGjAgAF66KGHiryP+cE4ZGIcMjEOjEEWxiET44AcGeRLQkKCkWQSEhKKZPtt27Y1jzzyiPNxenq6qVGjhpk6dWqO6w8cOND06dPHpe366683o0aNyvU1svqwevXqbMs+/vhjExgY6F7xhYhxyMQ4ZGIcGIMsjEMmxuEfD7zh+X9FLb/ZgyNzJUBKSoq2bdumHj16ONscDod69OihsLCwHJ8TFhbmsr4khYaG5rp+SkqKPvjgAwUGBqply5aFV3whYhwyMQ6ZGAfGIAvjkIlxQG4IcyVAXFyc0tPTFRQU5NIeFBSkmJiYHJ8TExOTr/UXL16sChUqyNfXV2+88YZWrVqlK664onA7UEgYh0yMQybGgTHIwjhkYhyQG8JcKde1a1ft3LlTP//8s2666SYNHDgw13MrSjPGIRPjkIlxYAyyMA6ZGAd7I8yVAFdccYW8vLx07Ngxl/Zjx44pODg4x+cEBwfna30/Pz/Vr19f7dq10+zZs+Xt7a3Zs2cXbgcKCeOQiXHIxDgwBlkYh0yMA3JDmCsBypQpozZt2mjNmjXOtoyMDK1Zs0bt27fP8Tnt27d3WV+SVq1alev65283OTn50osuAoxDJsYhE+PAGGRhHDIxDsiNt6cLQKaxY8dq2LBhuvbaa9W2bVtNnz5dZ86c0b333itJGjp0qGrWrKmpU6dKkh577DF17txZr732mvr06aN58+bpl19+0QcffCBJOnPmjF588UX169dP1atXV1xcnGbMmKEjR45owIABzteNjIxUfHy8IiMjlZ6erp07d0qS6tevrwoVKhTvIIhxyMI4ZGIcGIMsjEMmxgE5KvoLa0uHor41iTHGvP3226ZOnTqmTJkypm3btmbTpk3OZZ07dzbDhg1zWX/BggWmYcOGpkyZMqZZs2ZmyZIlzmVnz541t99+u6lRo4YpU6aMqV69uunXr5/ZsmWLyzaGDRtmJGX7t27duiLr58UwDpkYh0yMA2OQhXHIxDhk8vRtSUrSrUksY4wp0rRYSiQmJiowMFAJCQkKCAjwdDkAAFzWRkz3dAXSh2OKdvv5zR6cMwcAAGBjhDkAAAAbI8wBAADYGFezljCXwzkA+eHpcWAMMjEOmRiHTIwDY5ClJIwD/sGROQAAABsjzAEAANgYYQ4AAMDGCHMAAAA2RpgDAACwMcIcAACAjRHmAAAAbKzEhrmtW7eqd+/eqlixovz8/NSuXTstWLCgQNtITk7W888/rwYNGsjX11c1atTQyJEjdfz48SKqGgAAoHiVyJsGr1u3TqGhofL19dXgwYPl7++vhQsXatCgQYqKitK4ceMuuo2MjAzdeuutWrFihdq1a6f+/fsrPDxcs2bN0po1a7Rp0yZVrVq1GHoDAABQdErckbm0tDSNGDFCDodDGzdu1AcffKDXXntNv/76qxo2bKiJEyfq0KFDF93OnDlztGLFCt155536+eef9dJLL2nhwoWaOXOmDhw4oKeffroYegMAAFC0SlyYW7t2rSIiInTXXXepVatWzvbAwEBNnDhRKSkpmjNnzkW38+GHH0qSpk6dKsuynO2jRo1SvXr19Pnnn+vs2bOFXj8AAEBxKnFhbv369ZKkXr16ZVsWGhoqSdqwYUOe2zh37pw2b96sRo0aKSQkxGWZZVnq2bOnzpw5o19++aVwigYAAPCQEnfOXHh4uCSpQYMG2ZYFBwerQoUKznVyExERoYyMjBy3cf62w8PDdeONN+a4TnJyspKTk52PExISJEnx8fFKTU2VJDkcDnl5eSk9PV0ZGRnOdbPa09LSZIxxtnt5ecnhcOTanpqaqpRzPnn2rTgkJqpQ+3Q+b+/MXS4tLS3Pdk+PQ2KiCr1PWXx8fJSRkaH09HRnm2VZ8vb2dmn39BhI0okT+etrfvt0fntu+9iF7SVpHAqrT+78PqWc8/xn7xMnUovkfe98F/t9SjlnyZNOnEgtsve9LBf7fSoJ+0JCQma/C/t97/z2i/0+lYT3hlOniuZ9L6s9Pj5eklz2sxyZEqZnz55GkgkPD89xeY0aNUxAQECe2/jpp5+MJDNkyJAcl3/wwQdGknn99ddz3cbkyZONJP7xj3/84x//+Mc/j/6LiorKM/eUuCNzJcWECRM0duxY5+OMjAzFx8erSpUqLufglSSJiYmqXbu2oqKiFBAQ4OlyPIZxyMQ4ZGIcGIMsjEMmxiGTHcbBGKPTp0+rRo0aea5X4sJcYGCgpH++1rxQYmKiKlWqdMnbOH+9nJQtW1Zly5Z1aatYsWKer1tSBAQElNgdszgxDpkYh0yMA2OQhXHIxDhkKunjkFdWyeL5L94vcP75bBeKiYlRUlJSrufCZalXr54cDkeu59bldV4eAACAnZS4MNe5c2dJ0sqVK7MtW7Fihcs6uSlXrpzatm2rffv2ZbsnnTFGq1atkp+fn6699tpCqhoAAMAzSlyY6969u+rVq6cvvvhCO3fudLYnJCRoypQpKlOmjIYOHepsj46O1t69e7N9pTpy5EhJmee+mfOuAnn//fd14MABDRkyROXKlSvazhSzsmXLavLkydm+Hr7cMA6ZGIdMjANjkIVxyMQ4ZCpN42AZc7HrXYtfbtN5HTp0SNOmTXOZzmv48OGaM2eOPv74Yw0fPtzZnpGRod69ezun8+rcubP+/PNPffPNN6pbt642b97MdF4AAMD2StyROUnq2rWrfvzxR91www2aP3++3n33XQUFBWnevHn5mpdVyrxHy//+9z89++yzio2N1RtvvKGffvpJ999/v8LCwghyAACgVCiRR+YAAACQPyXyyBwAAADyhzAHAABgY4Q5AAAAGyPMAQAA2BhhrpTI7ToWrm8BAKB0I8yVEpZl6ciRI5KklJQU/f333852XH4I9wDywntB6cKtSWzOGKPFixdr9uzZ+u2335SUlKQWLVqoefPmatOmjVq1aqX69eurbNmyMsYQ7i4j4eHhqlatmk6fPq1y5cqpSpUqni4JJQzvCTgf+4N9EeZsbtKkSZo2bZrKly+v2rVrKzU1VSkpKYqKipIxRi1bttQdd9yhoUOHKigoyNPlFrn09HQ5HI7L9g0pOTlZX331lWbOnKkdO3bI4XCoQYMGql+/vtq0aaMOHTrommuukb+/v6dLLXLGGKWnp8vLy+uy3R+yHD9+XLGxsapSpYpOnz6tqlWrqmLFip4uCx6Qnp6u8PBwnTx5UlLm78lVV111Wfx9KM0IczZ28OBBNWvWTF26dNFrr72mxo0bKy4uTlFRUYqIiNDGjRu1YsUKhYeHq2XLlpoyZYpuvvlmZWRkyOEoXd+wR0VFqXbt2s7HGRkZMsbIy8vLg1UVv3HjxunNN99USEiIGjRoIB8fH506dUq//fabEhMTVbt2bd1yyy2677771KZNG0+XW2QiIiJ01VVXOR9nZGQoIyND3t7eHqyq+EVHR+upp57SqlWrdOTIEfn7++vKK69UkyZNdP3116tjx45q3rx5qZibMjdZR5su133gfPv27dOECRO0dOlSpaSkqGzZsqpUqZLq1q2r9u3b66abblKHDh3k5+fn6VJRUAa29fzzz5vKlSub1atXG2OMSU1NdVmekJBgfv75ZzNmzBhjWZYJDg42O3bs8EClReuvv/4ylmWZ0NBQ88knn5i4uDiX5WlpaSY9Pd0YY0xGRoYxxpjk5ORir7OoHThwwPj6+poBAwaY48ePG2OMSUxMNJGRkWbz5s3m1VdfNR06dDA+Pj6mbt26Zs6cOcaYf8aktPjzzz+NZVmmSZMm5tVXXzXR0dEuy9PS0kxaWpox5p++JyUlmZiYmGy/Q3YWHR1t2rVrZyzLMjfffLMZMGCAGTRokGnXrp0pX768sSzLNGvWzDz33HPm6NGjni63yCQkJJhDhw65tJ2/D1wujhw5Ypo3b24cDocZNmyYGTdunHnyySfNLbfcYgIDA41lWaZSpUrmvvvuM5s3b/Z0uUUiPj7erF+/3pw7d87TpRQ6wpyNDR061FSvXt3ExMQYY/75w5TTH+d58+aZwMBA065du2KtsThMmTLFWJbl/HfFFVeYYcOGmSVLlmT745wV4t577z3TvXt3s2/fPk+UXCRefPFFU7lyZbNmzRpjjMn2xyo1NdUcOHDATJ8+3VStWtVYlmWWL1/uiVKL1Msvv+yyP1iWZbp06WLmzp1rUlJSXNY9f39o27at2b59uydKLhKTJk0ygYGBZvr06c62kydPmqioKLNx40bz9NNPm6ZNmxqHw2Hat29vfvzxR2NM6Qv3Y8eONZZlmRtvvNF89NFH5syZMy7LU1NTnR/2skRHR5tjx46VqrF4+umnTaVKlcysWbOcbcnJySYlJcVERkaa999/39xwww3G4XCYpk2bmsWLFxtjStf+8MQTTxjLssw111xjXnjhBbN79+5c183q9/79+83OnTuzvXeUNIQ5G5s2bZqxLMt89dVXzrYL35TO/0W89957zRVXXGH27t1bbDUWh1tuucX4+/ubWbNmmWHDhjmPOliWZerXr2+eeOIJs2XLFpfn/Otf/zKWZZmkpCQPVV34Hn74YVOxYkUTFRVljMn7TXjlypWmevXqplGjRqXuU2r//v1NuXLlzBdffGEmTZpkmjZt6twffHx8zODBg52BN0tp3B+aNm1qbrnlFudR2gv3h3Pnzplff/3VGXYaN25sjh075olSi1Tz5s2zhfvbb7/dLFmyxGW9rPFJTEw0Q4YMMaGhoaXqSG3Lli3NTTfd5PwZ5/T+EBsba95++21TuXJl4+/vb/7444/iLrNItWrVyjgcDlO5cmXnvtC1a1fz/vvvm8OHD2dbPykpydx5552mXbt2hDkUnY0bN5oKFSqYxo0bm61bt7osy8jIcAa7rP9OmTLF+Pn5ZQs2dnb8+HHTtm1bU7NmTWfb2bNnzeeff266d+/u8gZ+3XXXmbfeesssWLDAVK9e3fTt29eDlRe+2bNnG8uyzIwZM5xv1GlpabmGugkTJpgKFSqUqqNRsbGxpkOHDiY4ONjZlpycbJYtW2buv/9+U716def+ULVqVfOf//zHzJ07t9TtDzExMaZJkyamZ8+eF103NTXVvPXWW8ayLPPkk08WQ3XFJyIiwlStWtV07tzZbNy40Tz00EOmTp06zn2gUqVK5uGHH3b5HdixY4epVKmS6dy5s+cKL2RxcXHm2muvzdc3M6mpqWbevHnGsiwzatSoYqiuePz111+mRo0apl27dmbnzp3mhRdeMJ06dTK+vr7Gsizj7+9vBg4caL799ltz4sQJY4wxW7ZsMZUrVzZdu3b1cPUXR5izqaw/0B9++KHx8vIylmWZkSNHmtWrV5vExMRs6//999/mzjvvNFWqVCnuUotUZGSkufHGG02fPn2MMdnPhTt69KiZNm2ay6fzrF/eCz+Z291vv/1matasaSpXrmwWLVrksiwjI8P5tWtWuH/99deNr6+v+fnnn4u91qISExNjbrrpJtOzZ0+Tmpqa7dN0bGys+fTTT02/fv2Mn5+fS9gvLftD1ge5O+64wwQEBDjPfzp/H8hJ8+bNTbdu3czp06eLq9Qit3LlSmNZlhk3bpyz7dSpU2b+/PlmwIABznPFLMsyV111lXnppZfMk08+aSzLcn7NaHdZfytGjBhhLMsyixYtcn7Iy+vI4w033GCuu+46Z7Cxu7Vr1xqHw2H+/e9/O9tOnz5tVqxYYR5//HHTokUL575Qs2ZNM2bMGDNq1Cjb7AuEOZtLSkoy7777rqlWrZqxLMtUq1bN3HrrrWbKlClm9erVJj4+3mzevNmMGjXKlClTxuVNrTRISUkxa9euNT///LPLRQ7nX/SQZd++feaRRx4xlmWZypUre6LcIpP1hr1s2TJTq1Yt5wUhCxYsMPHx8dnWT0pKMgMHDix14d4YY8LDw83u3buz7Q8XHqGMjIw0zz//vClfvrypVKmSJ0otUh988IHzXLELzw1KT093GZOEhATTu3dvc/XVV3ui1CLz888/m9q1a5sPPvjAGJP9IrFDhw6Zt99+23Tp0sUl2JfG/WHp0qXGsizTsGFDs2LFCpdlWReEZO0Pp06dMrfddptp2LChJ0otEjt37jQNGjQwb731ljEm+znF0dHR5ssvvzTDhg0zV155pe32BcKcTV34hykpKclMnz7dtG/f3nh7ezt3RIfDYcqUKWMsyzL33ntvjucFlAYXBrcsWZ8+s35xt2zZYsqXL29GjhxZnOUVm9TUVPP111+7fMps2bKleeSRR8zChQvNnj17zDfffGMGDRpkvLy8zH/+8x9Pl1yssoJd1v4QFhZWqveHl156yTgcDmNZlhk2bJhZsWKFOXv2rHN51vvI6tWrTc2aNc2IESM8VWqRSElJMb///rvzIjFjcj9CuX//fnP33Xcby7LMI488UpxlFpvPP//cBAUFOc8Vmz9/vst5oln7w5IlS0yNGjVK3f6QmJiY7cNtTn87jhw5YkaPHm0syzIPP/xwcZV3SbjPXCkTFxen/fv3a9OmTfrhhx+Unp6uhg0bqkmTJrr//vs9XV6hy7oprDFGGRkZF72v3KOPPqoZM2Zo69atpfo+a5L03XffadasWVqxYoXS09MlZU7vZoyRj4+PHnnkET355JOX9c1CR48erZkzZ5a6/cH8/3urnTp1Sh999JFefvllxcbGysvLS23atNENN9ygrl27KjAwUFu3btU777yj06dPa+3atWrevLmnyy82F75vPP/883r22WdL3f6QJTk5WQsXLtTrr7+u7du3S5KqVaumzp07q2fPnipbtqx2796t2bNnq2zZslq5cqWaNWvm4aqLx4X7wuTJk/XCCy/YZl8gzNnQ8ePH9dtvv2n//v1KSkpS27Zt1bhxY11xxRXZwkxycrLLDUHNZTxdS2JiokaNGqV169YpJibG0+UUiZxCbUxMjNatW6effvpJPj4+qlGjhho3bqy+fft6sFLPO3PmjB555BEtXbpUx48f93Q5herC3/Nz585pzpw5+vTTTxUWFpZt/aZNm2rChAkaMmRIcZZZ5LJukJ71oS8nWWO1f/9+9e3bV2lpaYqIiCjmSouXMUaLFi3SBx98oJUrVyotLc1lefv27fX000/r5ptv9lCFnnXgwAHddtttOn36tP766y9Pl5MvhDmbWbZsmf773/9me0OuXLmyunfvrkGDBqlv377y8fFxLiuNMz5IuYfaKlWqOO/yfuGbeHJyso4fP+4yW4TdFeTne+F4lKZw7+5+npiYqICAgCKoqGSKjIzU6tWrtXv3bgUHB6tatWrq2LGj6tev7+nSPGrfvn267bbb1LdvX73yyiueLqdImMxTq1x+TxISErR+/XodOHBANWrUUIUKFXTdddepWrVqHqzUs/766y+NGjVKnTt31lNPPeXpcvKFMGcjUVFR6tKli86cOaPhw4era9euOnDggHbs2KFff/1Vu3btUnJyspo2baqJEyfqjjvuUJkyZUrVH+wseYXaHj16OEPt5TZ1T26B5vw5a9PS0kr9uOQn2KWlpcmyrFI35dvy5cu1e/du7dy5U0FBQbr22mtVv3591a5dW1WqVHH5oFeanT8O1apV03XXXaf69esrJCREVapUcZ6eceF7Y2n7/cjtqGR6erosyyqVH/QvlNeR2aJ4nkcU4/l5uERPPfWUqVSpklm4cGG2ZVFRUWb+/PlmyJAhzhPfX375ZQ9UWfQiIyNNvXr1TFBQkHnyySfN8uXLzcyZM82IESNM27Ztnbceufrqq83nn3/uvF1JbhdJ2FVMTIwZO3asWb58uTl58qTLsoyMjFJ15/a8MA6ZTp48af7v//7PWJblchGUZVmmSpUqpl+/fubjjz/OdquJ0jY++R2HC/eV0ja9V043kM/pPfD89ovdrsRu8jsGF7LjdI+EORu5/vrrTZcuXUxsbKwxxrhcpXm+tWvXmtatW5uyZcua2bNnF3eZRY5Qm2nSpEnGsixz5ZVXmj59+phXX33VbNmyJduMDlm3oTDGmHXr1plly5Z5otwiwzhkeuWVV0z58uXN7bffbtatW2f27dtn5s2bZ5577jlzyy23OKdwu+aaa8y3337r6XKLDOOQaebMmWbgwIFm8eLF2e4dmJ6eXuo+3ObkchoDwpxNnD592vTo0cM0btzYObfg+TvihZ84tm/fbipVqmT69evnXF5aEGoztWrVypQpU8a0a9fOefuZunXrmiFDhphZs2aZPXv2uKx/5swZ069fP+NwOFxuT2F3jEOmkJAQ06dPHxMXF5dt2ZEjR8zixYvNyJEjnUerPvzwQw9UWfQYh0x169Z13iT9+uuvN88884wJCwvL9rcg60jcmTNnzBtvvGHWrl3riXKLxOU0BoQ5G8m6M3lOweT8nTMr1N16662mYcOG5uDBg8VWY1Ej1GaKjIw0devWNW3atDEpKSkmLCzMPPPMM6Zly5bGsizj5eVlWrRoYUaPHm0WLFhgEhISzJYtW0xwcHCpmraKcci0Z88eU6FCBTNx4kRnW05HHpKTk82SJUtMvXr1TOXKlUvV7B/GMA5Zdu/ebSzLMtdee63p2bOn81uKChUqmNDQUPPmm29m+5Dzww8/GMuyzA033OChqgvX5TYGhDkbOXz4sHNaqkcffdRs27Yt25GFrE8YCQkJZsCAAaZOnTqeKLVIEWqN2bx5s6lcubIZNmyYMcY4Z7w4duyYWbZsmXnwwQdNSEiIsSzLlC9f3nTq1Mk5V+2FU33ZGeOQ6Y8//jC1atUygwYNMsZkvg9c+CHn/N+N7777rlSegsA4ZPryyy+NZVnm9ddfN8Zkzn7z8ssvm1atWjlDTfXq1c2dd95pPv30UxMfH29ee+0120xdlR+X2xgQ5mzm22+/dU41cu2115oXXnjBrFu3zhw8eNAl2M2dO9dUrVq1VE2UnIVQmzll1b/+9S/z+eef57g8JSXFHDx40Hz22Wdm4MCBpnLlyraamia/GId/XH/99cbf398sXbo027KsAJMVbE6cOGGuvPJKc8cddxRrjcWBcTDm/fffN5Zl5TgGW7ZsMY8//ripXbu2M9Q0bNjQBAcHm8DAwOIvtohcbmNAmLOBC78aPHHihHniiSdMnTp1nPOxduvWzdx9991m5MiR5p577jFly5Y1jRs3Nnv37vVQ1UWLUJs5f2JO5wWdL+uP1nvvvWerqWkK4nIfh6z3h82bN5uaNWsay7LMmDFjzObNm7N9yMm6KOTnn382NWrUcJl03O4Yh0wZGRkmLCzMPP744+bPP/90aT/f2bNnzeLFi82wYcNMYGCgsSzLjB49urjLLRKX4xgQ5mwiayeMiopy/mH67bffzNSpU01oaKgz2GVNIt+tW7dsk2vbHaE2U07n/WV9vZib8ePHG8uyzLZt24qytGLFOLhKS0szn3zyialevbqxLMs0a9bMPP744+arr74yv//+u3NcDh8+bO68807j7e3NOJTicTh9+nSut9i48HfnkUceMZZlmR07dhRDZcXnchoDbhpcwqWlpemnn37SRx99pP3798uyLJUvX17XXXedBg4cqNatW8sYo6ioKJ09e1YHDhxQ48aNVbt2bXl7e5e6GwZn9efw4cOqUaOGHA6Hdu/ercWLF2v9+vXas2ePoqKiJEmVKlVSq1at9NZbb5W6+QWzxiEmJkbVqlVzufHn+TcIlqTDhw+rT58+Onr0qGJjYz1VcpFgHLKLjY3VO++8owULFmj//v0qX768atasqQoVKqhy5crau3evYmNjde+992rmzJmeLrfIMA55y/rdiYiI0KBBg5SQkKDw8HBPl1WsStMYEOZKuGnTpumFF17Q6dOnVb9+fXl5eWnfvn3O5U2bNtXDDz+sO+64o1RPv0KozXThODgcDpUrV04tW7ZU//791aFDh2zPiYuL02effaYaNWpo0KBBHqi68DEO2Znz5uU9e/aswsPDtXXrVv3000/avHmz9u7dq6pVq6p27dp64IEHdPfdd8vPz8/TZRc6xqFgFi9erH79+mn8+PF6+eWXPV2OR5SKMfDA0UDk04EDB4yfn5+58cYbzYEDB8zhw4dNamqqiYqKMjNnzjRdu3Z1frXarVs3s3XrVk+XXGReffVVExAQYCzLMg0aNDCNGzd2ubN7s2bNzIwZM8yxY8c8XWqRutg4NGnSxLz++usmOjra5XnJycml6gaZjEP+pKenmzNnzpjU1FQTFxdX6k69yK/LcRzyexummJgY88knn2SbGaQ0uJzGgDBXgj3zzDOmWrVqZvXq1c62C3fOXbt2maFDhxpfX1/TqFEj88svvxR3mUWOUJupIOPQvXv3UnkekDGMQ5a///7b7N271/z999/ZlqWnp7u8V1z4vlGaAi3jkCmvcbiY0jKV2eU8BoS5Euxf//qXqVevnjl06JAx5p/bbWRkZGTb8aZPn24syzLDhw8v9jqLGqE206WMQ2m5WbIxjEOWqVOnmmuvvdZMmTLFrF271hw5ciTb+8KF91U7fvx4qZp70xjGIUt+xuFCpW0cLucxIMyVYC+88IKxLMv8/vvvua5z/htU//79TZ06dUxERERxlFdsCLWZGIdMjEOmrNtveHt7mypVqpi+ffuat99+22zZsiXHW7UkJSWZJ554wtx7772l6ogU45DpUsbB7kelslzOY0CYK8F+/PFHY1mWadWqlVmzZk2Ol1if/wds4sSJpnz58ubXX38t7lKLFKE2E+OQiXHIvJt9hQoVTIcOHcw777xjbr31VlOtWjVjWZYJCQkxw4YNM5999pnZvXu3OXnypDHGmE2bNpnAwEBz6623erT2wsQ4ZGIcGAPCXAmWlpZmxo0b5zyh+5133jExMTE5rhsfH2+GDh1qqlatWsxVFj1CbSbGIRPjYMyiRYuMt7e3efbZZ40xxhw8eNCsWLHCPPvss6ZTp06mQoUKxtvb27Ro0cKMGTPGLF++3HmPPTtOVZQbxiET48AYEOZs4L333jNXXXWVsSzL1KxZ04wePdosWbLE7Nq1y/z+++/myJEj5j//+Y/x9fU1Y8eO9XS5hY5Qm4lxyMQ4GPPVV18Zy7LM/PnzXdpTUlJMeHi4+frrr81jjz1mWrZsacqUKWP8/PxM+fLlS900ZoxDJsaBMSDM2UBGRobZv3+/GT9+vMtcckFBQaZWrVrGy8vLWJZl7rrrLhMVFeXpcovM5R5qszAOmS7nccjIyDB//PGHOXDggPPxhZKSksz27dvNl19+aXr16uWcy7g0YRwyMQ6MAWHOZpKSkszatWvNmDFjzMCBA02XLl1Mv379zNy5c7PNP1jaEGozMQ6ZGIec5fRH7NFHHzWWZZnt27d7oCLPYBwyMQ6XxxgwA4SNpaamysfHx9NleMSZM2e0ZcsWff/99zp69KiOHz+ugIAADRw4UP3795evr6+nSywWjEMmxiG7jIwMORwOHTx4ULfeeqtOnjypyMhIT5dV7BiHTIxD6R4Db08XAPddrkFOkvz8/NS1a1d17dr1sg61jEMmxiG7rHlqjxw5otTUVD388MMersgzGIdMjEPpHgOOzAFAKWaM0eHDh1W5cuXLeg5SxiET41A6x4AwBwAAYGMOTxcAAAAA9xHmAAAAbIwwBwAAYGOEOQAAABsjzAEAANgYYQ4AAMDGCHMAAAA2RpgDAACwMcIcAACAjf0/SO1gh5hmP28AAAAASUVORK5CYII=", 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" + ] + }, + "execution_count": 5, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "ideal_distribution = Statevector.from_instruction(qc).probabilities_dict()\n", + "\n", + "plot_histogram(ideal_distribution)" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "## Step 2: Optimize problem for quantum execution.\n", + "\n", + "Next, we transpile the circuits for our backend. We're going to compare the performance of the transpiler with `optimization_level` set to `0` (lowest) against `3` (highest). The lowest optimization level just does the bare minimum needed to get the circuit running on the device; it maps the circuit qubits to the device qubits, and adds swaps gates to allow all 2-qubit operations. The highest optimization level is much smarter and uses lots of tricks to reduce the overall gate count. Since multi-qubit gates have high error rates, and qubits decohere over time, the shorter circuits should give better results.\n", + "\n", + "In the following cell, we transpile `qc` for both values of `optimization_level`, print the number of CNOT gates, and add the transpiled circuits to a list. Some of the transpiler's algorithms are randomized, so we set a seed for reproducibility.\n" + ] + }, + { + "cell_type": "code", + "execution_count": 6, + "metadata": {}, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "CNOTs (optimization_level=0): 27\n", + "CNOTs (optimization_level=3): 14\n" + ] + } + ], + "source": [ + "# Need to add measurements to the circuit\n", + "qc.measure_all()\n", + "\n", + "circuits = []\n", + "for optimization_level in [0, 3]:\n", + " t_qc = transpile(qc, backend, optimization_level=optimization_level, seed_transpiler=0)\n", + " print(f\"CNOTs (optimization_level={optimization_level}): \", t_qc.count_ops()[\"cx\"])\n", + " circuits.append(t_qc)" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "Since CNOTs usually have a high error rate, the circuit transpiled with `optimization_level=3` should perform much better.\n", + "\n", + "Another way we can improve performance is through [dynamic decoupling](https://docs.quantum-computing.ibm.com/api/qiskit-ibm-provider/qiskit_ibm_provider.transpiler.passes.scheduling.PadDynamicalDecoupling#paddynamicaldecoupling), where we apply a sequence of gates to idling qubits. This cancels out some unwanted interactions with the environment. In the following cell, we add dynamic decoupling to the circuit transpiled with `optimization_level=3`, and add it to our list.\n" + ] + }, + { + "cell_type": "code", + "execution_count": 7, + "metadata": {}, + "outputs": [], + "source": [ + "from qiskit.transpiler import PassManager\n", + "from qiskit_ibm_runtime.transpiler.passes.scheduling import (\n", + " ASAPScheduleAnalysis,\n", + " PadDynamicalDecoupling,\n", + ")\n", + "from qiskit.circuit.library import XGate\n", + "\n", + "# Get gate durations so the transpiler knows how long each operation takes\n", + "durations = backend.target.durations()\n", + "\n", + "# This is the sequence we'll apply to idling qubits\n", + "dd_sequence = [XGate(), XGate()]\n", + "\n", + "# Run scheduling and dynamic decoupling passes on circuit\n", + "pm = PassManager([ASAPScheduleAnalysis(durations), PadDynamicalDecoupling(durations, dd_sequence)])\n", + "circ_dd = pm.run(circuits[1])\n", + "\n", + "# Add this new circuit to our list\n", + "circuits.append(circ_dd)" + ] + }, + { + "cell_type": "code", + "execution_count": 8, + "metadata": {}, + "outputs": [ + { + "data": { + "image/png": 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+ "text/plain": [ + "
" + ] + }, + "execution_count": 8, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "circ_dd.draw(output=\"mpl\", style=\"iqp\", idle_wires=False)" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "## Step 3: Execute using Qiskit Primitives.\n", + "\n", + "At this point, we have a list of circuits transpiled for our system. In the following cell, we create an instance of the sampler primitive, and start a batched job using the context manager (`with ...:`), which automatically opens and closes the Batch for us. This is where we pass the `skip_transpilation=True` argument.\n", + "\n", + "Within the context manager, we sample the circuits and store the results to `result`.\n" + ] + }, + { + "cell_type": "code", + "execution_count": 9, + "metadata": {}, + "outputs": [], + "source": [ + "with Batch(service=service, backend=backend):\n", + " sampler = Sampler()\n", + " job = sampler.run(\n", + " circuits=circuits, # sample all three circuits\n", + " skip_transpilation=True,\n", + " shots=8000,\n", + " )\n", + " result = job.result()" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "## Step 4: Post-process, return result in classical format.\n", + "\n", + "Finally, we can plot the results from the device runs against the ideal distribution. You can see the results with `optimization_level=3` are closer to the ideal distribution due to the lower gate count, and `optimization_level=3 + dd` is even closer due to the dynamic decoupling we applied.\n" + ] + }, + { + "cell_type": "code", + "execution_count": 10, + "metadata": {}, + "outputs": [ + { + "data": { + "image/png": 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", + "text/plain": [ + "
" + ] + }, + "execution_count": 10, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "binary_prob = [quasi_dist.binary_probabilities() for quasi_dist in result.quasi_dists]\n", + "plot_histogram(\n", + " binary_prob + [ideal_distribution],\n", + " bar_labels=False,\n", + " legend=[\n", + " \"optimization_level=0\",\n", + " \"optimization_level=3\",\n", + " \"optimization_level=3 + dd\",\n", + " \"ideal distribution\",\n", + " ],\n", + ")" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "We can confirm this by computing the [Hellinger fidelity](https://docs.quantum-computing.ibm.com/api/qiskit/quantum_info) between each set of results and the ideal distribution (higher is better, and 1 is perfect fidelity).\n" + ] + }, + { + "cell_type": "code", + "execution_count": 11, + "metadata": {}, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "0.873\n", + "0.983\n", + "0.981\n" + ] + } + ], + "source": [ + "from qiskit.quantum_info import hellinger_fidelity\n", + "\n", + "for counts in result.quasi_dists:\n", + " print(f\"{hellinger_fidelity(counts.binary_probabilities(), ideal_distribution):.3f}\")" + ] + }, + { + "cell_type": "code", + "execution_count": 12, + "metadata": {}, + "outputs": [ + { + "data": { + "text/plain": [ + "'0.19.1'" + ] + }, + "execution_count": 12, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "import qiskit_ibm_runtime\n", + "\n", + "qiskit_ibm_runtime.version.get_version_info()" + ] + }, + { + "cell_type": "code", + "execution_count": 13, + "metadata": {}, + "outputs": [ + { + "data": { + "text/plain": [ + "'1.0.0rc1'" + ] + }, + "execution_count": 13, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "import qiskit\n", + "\n", + "qiskit.version.get_version_info()" + ] + } + ], + "metadata": { + "kernelspec": { + "display_name": "env", + "language": "python", + "name": "python3" + }, + "language_info": { + "codemirror_mode": { + "name": "ipython", + "version": 3 + }, + "file_extension": ".py", + "mimetype": "text/x-python", + "name": "python", + "nbconvert_exporter": "python", + "pygments_lexer": "ipython3", + "version": "3.9.6" + } + }, + "nbformat": 4, + "nbformat_minor": 4 +}