def test_run_1qubit(self):
"""Test for 1-qubit cases"""
qc = QuantumCircuit(1)
qc2 = QuantumCircuit(1)
qc2.x(0)
op = SparsePauliOp.from_list([("I", 1)])
op2 = SparsePauliOp.from_list([("Z", 1)])
est = Estimator()
result = est.run([qc], [op], [[]]).result()
self.assertIsInstance(result, EstimatorResult)
np.testing.assert_allclose(result.values, [1])
result = est.run([qc], [op2], [[]]).result()
self.assertIsInstance(result, EstimatorResult)
np.testing.assert_allclose(result.values, [1])
result = est.run([qc2], [op], [[]]).result()
self.assertIsInstance(result, EstimatorResult)
np.testing.assert_allclose(result.values, [1])
result = est.run([qc2], [op2], [[]]).result()
self.assertIsInstance(result, EstimatorResult)
np.testing.assert_allclose(result.values, [-1])
def test_estiamtor_run_no_params(self):
"""test for estimator without parameters"""
circuit = self.ansatz.bind_parameters([0, 1, 1, 2, 3, 5])
est = Estimator()
result = est.run([circuit], [self.observable]).result()
self.assertIsInstance(result, EstimatorResult)
np.testing.assert_allclose(result.values, [-1.284366511861733])
def test_run_with_shots_option(self):
"""test with shots option."""
est = Estimator()
result = est.run(
[self.ansatz],
[self.observable],
parameter_values=[[0, 1, 1, 2, 3, 5]],
shots=1024,
seed=15,
).result()
self.assertIsInstance(result, EstimatorResult)
np.testing.assert_allclose(result.values, [-1.307397243478641])
def test_run_numpy_params(self):
"""Test for numpy array as parameter values"""
qc = RealAmplitudes(num_qubits=2, reps=2)
op = SparsePauliOp.from_list([("IZ", 1), ("XI", 2), ("ZY", -1)])
k = 5
params_array = np.random.rand(k, qc.num_parameters)
params_list = params_array.tolist()
params_list_array = list(params_array)
estimator = Estimator()
target = estimator.run([qc] * k, [op] * k, params_list).result()
with self.subTest("ndarrary"):
result = estimator.run([qc] * k, [op] * k, params_array).result()
self.assertEqual(len(result.metadata), k)
np.testing.assert_allclose(result.values, target.values)
with self.subTest("list of ndarray"):
result = estimator.run([qc] * k, [op] * k,
params_list_array).result()
self.assertEqual(len(result.metadata), k)
np.testing.assert_allclose(result.values, target.values)
def test_run_2qubits(self):
"""Test for 2-qubit cases (to check endian)"""
qc = QuantumCircuit(2)
qc2 = QuantumCircuit(2)
qc2.x(0)
op = SparsePauliOp.from_list([("II", 1)])
op2 = SparsePauliOp.from_list([("ZI", 1)])
op3 = SparsePauliOp.from_list([("IZ", 1)])
est = Estimator()
result = est.run([qc], [op], [[]]).result()
self.assertIsInstance(result, EstimatorResult)
np.testing.assert_allclose(result.values, [1])
result = est.run([qc2], [op], [[]]).result()
self.assertIsInstance(result, EstimatorResult)
np.testing.assert_allclose(result.values, [1])
result = est.run([qc], [op2], [[]]).result()
self.assertIsInstance(result, EstimatorResult)
np.testing.assert_allclose(result.values, [1])
result = est.run([qc2], [op2], [[]]).result()
self.assertIsInstance(result, EstimatorResult)
np.testing.assert_allclose(result.values, [1])
result = est.run([qc], [op3], [[]]).result()
self.assertIsInstance(result, EstimatorResult)
np.testing.assert_allclose(result.values, [1])
result = est.run([qc2], [op3], [[]]).result()
self.assertIsInstance(result, EstimatorResult)
np.testing.assert_allclose(result.values, [-1])
def test_estimator_run(self):
"""Test Estimator.run()"""
psi1, psi2 = self.psi
hamiltonian1, hamiltonian2, hamiltonian3 = self.hamiltonian
theta1, theta2, theta3 = self.theta
estimator = Estimator()
# Specify the circuit and observable by indices.
# calculate [ <psi1(theta1)|H1|psi1(theta1)> ]
job = estimator.run([psi1], [hamiltonian1], [theta1])
self.assertIsInstance(job, JobV1)
result = job.result()
self.assertIsInstance(result, EstimatorResult)
np.testing.assert_allclose(result.values, [1.5555572817900956])
# Objects can be passed instead of indices.
# Note that passing objects has an overhead
# since the corresponding indices need to be searched.
# User can append a circuit and observable.
# calculate [ <psi2(theta2)|H2|psi2(theta2)> ]
result2 = estimator.run([psi2], [hamiltonian1], [theta2]).result()
np.testing.assert_allclose(result2.values, [2.97797666])
# calculate [ <psi1(theta1)|H2|psi1(theta1)>, <psi1(theta1)|H3|psi1(theta1)> ]
result3 = estimator.run([psi1, psi1], [hamiltonian2, hamiltonian3],
[theta1] * 2).result()
np.testing.assert_allclose(result3.values, [-0.551653, 0.07535239])
# calculate [ <psi1(theta1)|H1|psi1(theta1)>,
# <psi2(theta2)|H2|psi2(theta2)>,
# <psi1(theta3)|H3|psi1(theta3)> ]
result4 = estimator.run([psi1, psi2, psi1],
[hamiltonian1, hamiltonian2, hamiltonian3],
[theta1, theta2, theta3]).result()
np.testing.assert_allclose(result4.values,
[1.55555728, 0.17849238, -1.08766318])
def test_run_errors(self):
"""Test for errors"""
qc = QuantumCircuit(1)
qc2 = QuantumCircuit(2)
op = SparsePauliOp.from_list([("I", 1)])
op2 = SparsePauliOp.from_list([("II", 1)])
est = Estimator()
with self.assertRaises(QiskitError):
est.run([qc], [op2], [[]]).result()
with self.assertRaises(QiskitError):
est.run([qc2], [op], [[]]).result()
with self.assertRaises(QiskitError):
est.run([qc], [op], [[1e4]]).result()
with self.assertRaises(QiskitError):
est.run([qc2], [op2], [[1, 2]]).result()
with self.assertRaises(QiskitError):
est.run([qc, qc2], [op2], [[1]]).result()
with self.assertRaises(QiskitError):
est.run([qc], [op, op2], [[1]]).result()