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fix: QNSPSA with max_evals_grouped exceeding 1 (#9182) (#9189)
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Co-authored-by: Julien Gacon <gaconju@gmail.com>

Co-authored-by: Julien Gacon <gaconju@gmail.com>
Co-authored-by: mergify[bot] <37929162+mergify[bot]@users.noreply.github.com>
(cherry picked from commit 324c875)

Co-authored-by: Max Rossmannek <oss@zurich.ibm.com>
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mergify[bot] and mrossinek authored Nov 23, 2022
1 parent 12c8847 commit 01cb4f9
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Showing 3 changed files with 50 additions and 2 deletions.
12 changes: 11 additions & 1 deletion qiskit/algorithms/optimizers/qnspsa.py
Original file line number Diff line number Diff line change
Expand Up @@ -311,8 +311,18 @@ def get_fidelity(

fid = ComputeUncompute(sampler)

num_parameters = circuit.num_parameters

def fidelity(values_x, values_y):
result = fid.run(circuit, circuit, values_x, values_y).result()
values_x = np.reshape(values_x, (-1, num_parameters)).tolist()
batch_size_x = len(values_x)

values_y = np.reshape(values_y, (-1, num_parameters)).tolist()
batch_size_y = len(values_y)

result = fid.run(
batch_size_x * [circuit], batch_size_y * [circuit], values_x, values_y
).result()
return np.asarray(result.fidelities)

return fidelity
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Original file line number Diff line number Diff line change
@@ -0,0 +1,5 @@
---
fixes:
- |
Fixes a bug causing QNSPSA to fail when ``max_evals_grouped`` was set to a
value larger than 1.
35 changes: 34 additions & 1 deletion test/python/algorithms/optimizers/test_spsa.py
Original file line number Diff line number Diff line change
Expand Up @@ -19,7 +19,7 @@

from qiskit.algorithms.optimizers import SPSA, QNSPSA
from qiskit.circuit.library import PauliTwoDesign
from qiskit.primitives import Sampler
from qiskit.primitives import Estimator, Sampler
from qiskit.providers.basicaer import StatevectorSimulatorPy
from qiskit.opflow import I, Z, StateFn, MatrixExpectation
from qiskit.utils import algorithm_globals
Expand Down Expand Up @@ -222,3 +222,36 @@ def test_qnspsa_fidelity_primitives(self):
result = fidelity(initial_point, initial_point)

self.assertAlmostEqual(result[0], 1)

def test_qnspsa_max_evals_grouped(self):
"""Test using max_evals_grouped with QNSPSA."""
circuit = PauliTwoDesign(3, reps=1, seed=1)
num_parameters = circuit.num_parameters
obs = Z ^ Z ^ I

estimator = Estimator(options={"seed": 12})

initial_point = np.array(
[0.82311034, 0.02611798, 0.21077064, 0.61842177, 0.09828447, 0.62013131]
)

def objective(x):
x = np.reshape(x, (-1, num_parameters)).tolist()
n = len(x)
return estimator.run(n * [circuit], n * [obs.primitive], x).result().values.real

fidelity = QNSPSA.get_fidelity(circuit)
optimizer = QNSPSA(fidelity)
optimizer.maxiter = 1
optimizer.learning_rate = 0.05
optimizer.perturbation = 0.05
optimizer.set_max_evals_grouped(50) # greater than 1

result = optimizer.minimize(objective, initial_point)

with self.subTest("check final accuracy"):
self.assertAlmostEqual(result.fun[0], 0.473, places=3)

with self.subTest("check number of function calls"):
expected_nfev = 8 # 7 * maxiter + 1
self.assertEqual(result.nfev, expected_nfev)

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