def test_bind_parameter_list(self):
""" bind parameters list test """
thetas = ParameterVector('θ', length=6)
op = (thetas[1] * I ^ Z) + \
(thetas[2] * X ^ X) + \
(thetas[3] * Z ^ I) + \
(thetas[4] * Y ^ Z) + \
(thetas[5] * Z ^ Z)
op = thetas[0] * op
evolution = PauliTrotterEvolution(trotter_mode='trotter', reps=1)
# wf = (Pl^Pl) + (Ze^Ze)
wf = (op).exp_i() @ CX @ (H ^ I) @ Zero
evo = evolution.convert(wf)
param_list = np.transpose(
[np.arange(10, 16),
np.arange(2, 8),
np.arange(30, 36)]).tolist()
means = evo.assign_parameters({thetas: param_list})
self.assertIsInstance(means, ListOp)
# Check that the no parameters are in the circuit
for p in thetas[1:]:
for circop in means.oplist:
self.assertNotIn(p, circop.to_circuit().parameters)
# Check that original circuit is unchanged
for p in thetas:
self.assertIn(p, evo.to_circuit().parameters)
def trotter_circ(q, exp_args, n_steps):
qc = QuantumCircuit(q)
for i in range(n_steps):
for sub_op in exp_args:
qc += PauliTrotterEvolution().convert(
EvolvedOp(sub_op)).to_circuit()
return qc
def test_bind_parameters(self):
""" bind parameters test """
thetas = ParameterVector('θ', length=6)
op = (thetas[1] * I ^ Z) + \
(thetas[2] * X ^ X) + \
(thetas[3] * Z ^ I) + \
(thetas[4] * Y ^ Z) + \
(thetas[5] * Z ^ Z)
op = thetas[0] * op
evolution = PauliTrotterEvolution(trotter_mode='trotter', reps=1)
# wf = (Pl^Pl) + (Ze^Ze)
wf = (op).exp_i() @ CX @ (H ^ I) @ Zero
wf = wf.bind_parameters({thetas: np.arange(10, 16)})
mean = evolution.convert(wf)
circuit_params = mean.to_circuit().parameters
# Check that the no parameters are in the circuit
for p in thetas[1:]:
self.assertNotIn(p, circuit_params)
def test_parameterized_evolution(self):
""" parameterized evolution test """
thetas = ParameterVector('θ', length=7)
op = (thetas[0] * I ^ I) + \
(thetas[1] * I ^ Z) + \
(thetas[2] * X ^ X) + \
(thetas[3] * Z ^ I) + \
(thetas[4] * Y ^ Z) + \
(thetas[5] * Z ^ Z)
op = op * thetas[6]
evolution = PauliTrotterEvolution(trotter_mode='trotter', reps=1)
# wf = (Pl^Pl) + (Ze^Ze)
wf = (op).exp_i() @ CX @ (H ^ I) @ Zero
mean = evolution.convert(wf)
circuit_params = mean.to_circuit().parameters
# Check that the non-identity parameters are in the circuit
for p in thetas[1:]:
self.assertIn(p, circuit_params)
self.assertNotIn(thetas[0], circuit_params)
def test_parameterized_evolution(self):
""" parameterized evolution test """
thetas = ParameterVector('θ', length=7)
op = (thetas[0] * I ^ I) + \
(thetas[1] * I ^ Z) + \
(thetas[2] * X ^ X) + \
(thetas[3] * Z ^ I) + \
(thetas[4] * Y ^ Z) + \
(thetas[5] * Z ^ Z)
op = op * thetas[6]
evolution = PauliTrotterEvolution(trotter_mode='trotter', reps=1)
# wf = (Pl^Pl) + (Ze^Ze)
wf = (op).exp_i() @ CX @ (H ^ I) @ Zero
mean = evolution.convert(wf)
circuit = mean.to_circuit()
# Check that all parameters are in the circuit
for p in thetas:
self.assertIn(p, circuit.parameters)
# Check that the identity-parameters only exist as global phase
self.assertNotIn(thetas[0], circuit._parameter_table.get_keys())
def test_trotter_with_identity(self):
""" trotterization of operator with identity term """
op = (2.0 * I ^ I) + (Z ^ Y)
exact_matrix = scipy.linalg.expm(-1j * op.to_matrix())
evo = PauliTrotterEvolution(trotter_mode='suzuki', reps=2)
with self.subTest('all PauliOp terms'):
circ_op = evo.convert(EvolvedOp(op))
circuit_matrix = qiskit.quantum_info.Operator(circ_op.to_circuit()).data
np.testing.assert_array_almost_equal(exact_matrix, circuit_matrix)
with self.subTest('MatrixOp identity term'):
op = (2.0 * I ^ I).to_matrix_op() + (Z ^ Y)
circ_op = evo.convert(EvolvedOp(op))
circuit_matrix = qiskit.quantum_info.Operator(circ_op.to_circuit()).data
np.testing.assert_array_almost_equal(exact_matrix, circuit_matrix)
with self.subTest('CircuitOp identity term'):
op = (2.0 * I ^ I).to_circuit_op() + (Z ^ Y)
circ_op = evo.convert(EvolvedOp(op))
circuit_matrix = qiskit.quantum_info.Operator(circ_op.to_circuit()).data
np.testing.assert_array_almost_equal(exact_matrix, circuit_matrix)
def trotter_circuit(self):
'''Creates time evolution circuit with time as free parameter
according the method specified by self.trot_options'''
evo_H = self.evo_H # this may be different from self.H
evo_time = Parameter('t') # evolution time, to be set later
self.evo_time = evo_time
evo_op = (evo_time * evo_H).exp_i() # evolution operator
if self.trot_options['product_formula'] == 'lietrotter':
num_reps = self.trot_options['reps']
trotterized_op = PauliTrotterEvolution(trotter_mode='trotter',
reps=num_reps).convert(evo_op)
qc = trotterized_op.to_circuit()
elif self.trot_options['product_formula'] == 'suzuki':
num_reps = self.trot_options['reps']
order = self.trot_options['order']
trotterized_op = PauliTrotterEvolution(
trotter_mode=Suzuki(order=order, reps=num_reps)).convert(evo_op)
qc = trotterized_op.to_circuit()
return qc
