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Refactor reconstruct_expectation_values (#391)
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* Refactor reconstruct_experiments

* weight-->coeff

* cleanups

* cleanups

* New workflow works with cutting_evaluation

* Tests passing

* re-add CuttingExperimentResults

* cleanup

* mypy

* fix inits

* release notes

* Remove private generate_cutting_experiments

* Revert "Remove private generate_cutting_experiments"

This reverts commit cd95e28.

* fix sphinx

* Add num_qpd_bit checks and tests

* fix hanging jobs :(

* Update circuit_knitting/cutting/cutting_evaluation.py

Co-authored-by: Jim Garrison <garrison@ibm.com>

* Update circuit_knitting/cutting/cutting_reconstruction.py

Co-authored-by: Jim Garrison <garrison@ibm.com>

* Update circuit_knitting/cutting/cutting_reconstruction.py

Co-authored-by: Jim Garrison <garrison@ibm.com>

* Update circuit_knitting/cutting/cutting_reconstruction.py

Co-authored-by: Jim Garrison <garrison@ibm.com>

* Update circuit_knitting/cutting/cutting_reconstruction.py

Co-authored-by: Jim Garrison <garrison@ibm.com>

* Update circuit_knitting/cutting/cutting_reconstruction.py

Co-authored-by: Jim Garrison <garrison@ibm.com>

* Update circuit_knitting/cutting/cutting_reconstruction.py

Co-authored-by: Jim Garrison <garrison@ibm.com>

* Update circuit_knitting/cutting/cutting_reconstruction.py

Co-authored-by: Jim Garrison <garrison@ibm.com>

* peer review

* Fix links in release notes

* quasi-dist(s)

* Update circuit_knitting/cutting/cutting_reconstruction.py

Co-authored-by: Jim Garrison <garrison@ibm.com>

* Update releasenotes/notes/refactor-reconstruct-45e00c3df1bdd4ff.yaml

Co-authored-by: Jim Garrison <garrison@ibm.com>

---------

Co-authored-by: Jim Garrison <garrison@ibm.com>
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@caleb-johnson @garrison
caleb-johnson and garrison authored Sep 8, 2023
1 parent 88e2195 commit 2d8ac11
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174 changes: 47 additions & 127 deletions circuit_knitting/cutting/cutting_evaluation.py
View file
Original file line number Diff line number Diff line change
Expand Up @@ -16,14 +16,12 @@
from typing import NamedTuple
from collections import defaultdict
from collections.abc import Sequence
from itertools import chain

import numpy as np
from qiskit.circuit import QuantumCircuit, ClassicalRegister
from qiskit.quantum_info import PauliList
from qiskit.primitives import BaseSampler, Sampler as TerraSampler
from qiskit.primitives import BaseSampler, Sampler as TerraSampler, SamplerResult
from qiskit_aer.primitives import Sampler as AerSampler
from qiskit.result import QuasiDistribution

from ..utils.observable_grouping import CommutingObservableGroup, ObservableCollection
from ..utils.iteration import strict_zip
Expand All @@ -41,7 +39,7 @@
class CuttingExperimentResults(NamedTuple):
"""Circuit cutting subexperiment results and sampling coefficients."""

quasi_dists: list[list[list[tuple[QuasiDistribution, int]]]]
results: SamplerResult | dict[str | int, SamplerResult]
coeffs: Sequence[tuple[float, WeightType]]


Expand All @@ -64,10 +62,8 @@ def execute_experiments(
samplers: Sampler(s) on which to run the sub-experiments.
Returns:
- A 3D list of length-2 tuples holding the quasi-distributions and QPD bit information
for each sub-experiment. The shape of the list is: (``num_unique_samples``, ``num_partitions``, ``num_commuting_observ_groups``)
- Coefficients corresponding to each unique subexperiment's
sampling frequency
- One :class:`~qiskit.primitives.SamplerResult` instance for each partition.
- Coefficients corresponding to each unique subexperiment's contribution to the reconstructed result
Raises:
ValueError: The number of requested samples must be at least one.
Expand Down Expand Up @@ -119,59 +115,52 @@ def execute_experiments(
_validate_samplers(samplers)

# Generate the sub-experiments to run on backend
(
_,
coefficients,
subexperiments,
) = _generate_cutting_experiments(
circuits,
subobservables,
num_samples,
subexperiments, coefficients = _generate_cutting_experiments(
circuits, subobservables, num_samples
)

# Create a list of samplers to use -- one for each batch
# Set up subexperiments and samplers
subexperiments_dict: dict[str | int, list[QuantumCircuit]] = {}
if isinstance(subexperiments, list):
subexperiments_dict = {"A": subexperiments}
else:
assert isinstance(subexperiments, dict)
subexperiments_dict = subexperiments
if isinstance(samplers, BaseSampler):
samplers_by_batch = [samplers]
batches = [
[
sample[i]
for sample in subexperiments
for i in range(len(subexperiments[0]))
]
]
samplers_dict = {key: samplers for key in subexperiments_dict.keys()}
else:
samplers_by_batch = [samplers[key] for key in sorted(samplers.keys())]
batches = [
[sample[i] for sample in subexperiments]
for i in range(len(subexperiments[0]))
]

# There should be one batch per input sampler
assert len(samplers_by_batch) == len(batches)

# Run each batch of sub-experiments
quasi_dists_by_batch = [
_run_experiments_batch(
batches[i],
samplers_by_batch[i],
)
for i in range(len(samplers_by_batch))
]

# Build the output data structure to match the shape of input subexperiments
quasi_dists: list[list[list[tuple[dict[str, int], int]]]] = [
[] for _ in range(len(subexperiments))
]
count = 0
for i in range(len(subexperiments)):
for j in range(len(subexperiments[0])):
if len(samplers_by_batch) == 1:
quasi_dists[i].append(quasi_dists_by_batch[0][count])
count += 1
else:
quasi_dists[i].append(quasi_dists_by_batch[j][i])
assert isinstance(samplers, dict)
samplers_dict = samplers

# Make sure the first two cregs in each circuit are for QPD and observable measurements
# Run a job for each partition and collect results
results = {}
for label in sorted(subexperiments_dict.keys()):
for circ in subexperiments_dict[label]:
if (
len(circ.cregs) != 2
or circ.cregs[1].name != "observable_measurements"
or circ.cregs[0].name != "qpd_measurements"
or sum([reg.size for reg in circ.cregs]) != circ.num_clbits
):
# If the classical bits/registers are in any other format than expected, the user must have
# input them, so we can just raise this generic error in any case.
raise ValueError(
"Circuits input to execute_experiments should contain no classical registers or bits."
)
results[label] = samplers_dict[label].run(subexperiments_dict[label]).result()

for label, result in results.items():
for i, metadata in enumerate(result.metadata):
metadata["num_qpd_bits"] = len(subexperiments_dict[label][i].cregs[0])

return CuttingExperimentResults(quasi_dists, coefficients)
# If the input was a circuit, the output results should be a single SamplerResult instance
results_out = results
if isinstance(circuits, QuantumCircuit):
assert len(results_out.keys()) == 1
results_out = results[list(results.keys())[0]]

return CuttingExperimentResults(results=results_out, coeffs=coefficients)


def _append_measurement_circuit(
Expand Down Expand Up @@ -246,7 +235,6 @@ def _generate_cutting_experiments(
) -> tuple[
list[QuantumCircuit] | dict[str | int, list[QuantumCircuit]],
list[tuple[float, WeightType]],
list[list[list[QuantumCircuit]]],
]:
if isinstance(circuits, QuantumCircuit) and not isinstance(observables, PauliList):
raise ValueError(
Expand Down Expand Up @@ -295,7 +283,7 @@ def _generate_cutting_experiments(

# Calculate terms in coefficient calculation
kappa = np.prod([basis.kappa for basis in bases])
num_samples = sum([value[0] for value in random_samples.values()]) # type: ignore
num_samples = sum([value[0] for value in random_samples.values()])

# Sort samples in descending order of frequency
sorted_samples = sorted(random_samples.items(), key=lambda x: x[1][0], reverse=True)
Expand Down Expand Up @@ -323,25 +311,6 @@ def _generate_cutting_experiments(
meas_qc = _append_measurement_circuit(decomp_qc, cog)
subexperiments_dict[label].append(meas_qc)

# Generate legacy subexperiments list
subexperiments_legacy: list[list[list[QuantumCircuit]]] = []
for z, (map_ids, (redundancy, weight_type)) in enumerate(sorted_samples):
subexperiments_legacy.append([])
for i, (subcircuit, label) in enumerate(
strict_zip(subcircuit_list, sorted(subsystem_observables.keys()))
):
map_ids_tmp = map_ids
if is_separated:
map_ids_tmp = tuple(map_ids[j] for j in subcirc_map_ids[i])
decomp_qc = decompose_qpd_instructions(
subcircuit, subcirc_qpd_gate_ids[i], map_ids_tmp
)
subexperiments_legacy[-1].append([])
so = subsystem_observables[label]
for j, cog in enumerate(so.groups):
meas_qc = _append_measurement_circuit(decomp_qc, cog)
subexperiments_legacy[-1][-1].append(meas_qc)

# If the input was a single quantum circuit, return the subexperiments as a list
subexperiments_out: list[QuantumCircuit] | dict[
str | int, list[QuantumCircuit]
Expand All @@ -351,56 +320,7 @@ def _generate_cutting_experiments(
assert len(subexperiments_out.keys()) == 1
subexperiments_out = list(subexperiments_dict.values())[0]

return subexperiments_out, weights, subexperiments_legacy


def _run_experiments_batch(
subexperiments: Sequence[Sequence[QuantumCircuit]],
sampler: BaseSampler,
) -> list[list[tuple[QuasiDistribution, int]]]:
"""Run subexperiments on the backend."""
num_qpd_bits_flat = []

# Run all the experiments in one big batch
experiments_flat = list(chain.from_iterable(subexperiments))

for circ in experiments_flat:
if (
len(circ.cregs) != 2
or circ.cregs[1].name != "observable_measurements"
or circ.cregs[0].name != "qpd_measurements"
or sum([reg.size for reg in circ.cregs]) != circ.num_clbits
):
# If the classical bits/registers are in any other format than expected, the user must have
# input them, so we can just raise this generic error in any case.
raise ValueError(
"Circuits input to execute_experiments should contain no classical registers or bits."
)

num_qpd_bits_flat.append(len(circ.cregs[0]))

# Run all of the batched experiments
quasi_dists_flat = sampler.run(experiments_flat).result().quasi_dists

# Reshape the output data to match the input
quasi_dists_reshaped: list[list[QuasiDistribution]] = [[] for _ in subexperiments]
num_qpd_bits: list[list[int]] = [[] for _ in subexperiments]
count = 0
for i, subcirc in enumerate(subexperiments):
for j in range(len(subcirc)):
quasi_dists_reshaped[i].append(quasi_dists_flat[count])
num_qpd_bits[i].append(num_qpd_bits_flat[count])
count += 1

# Create the counts tuples, which include the number of QPD measurement bits
quasi_dists: list[list[tuple[dict[str, float], int]]] = [
[] for _ in range(len(subexperiments))
]
for i, sample in enumerate(quasi_dists_reshaped):
for j, prob_dict in enumerate(sample):
quasi_dists[i].append((prob_dict, num_qpd_bits[i][j]))

return quasi_dists
return subexperiments_out, weights


def _get_mapping_ids_by_partition(
Expand Down
2 changes: 1 addition & 1 deletion circuit_knitting/cutting/cutting_experiments.py
View file
Original file line number Diff line number Diff line change
Expand Up @@ -69,7 +69,7 @@ def generate_cutting_experiments(
to the same cut.
ValueError: :class:`SingleQubitQPDGate` instances are not allowed in unseparated circuits.
"""
subexperiments, weights, _ = _generate_cutting_experiments(
subexperiments, weights = _generate_cutting_experiments(
circuits, observables, num_samples
)
return subexperiments, weights
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