def sample_observable(state, obs, n_sample):
"""Function
Args:
state (qulacs.QuantumState):
obs (qulacs.Observable)
n_sample (int): number of samples for each observable
Return:
:float: sampled expectation value of the observable
Author(s): Takashi Tsuchimochi
"""
n_term = obs.get_term_count()
n_qubits = obs.get_qubit_count()
exp = 0
buf_state = QuantumState(n_qubits)
for i in range(n_term):
pauli_term = obs.get_term(i)
coef = pauli_term.get_coef()
pauli_id = pauli_term.get_pauli_id_list()
pauli_index = pauli_term.get_index_list()
if len(pauli_id) == 0: # means identity
exp += coef
continue
buf_state.load(state)
measurement_circuit = QuantumCircuit(n_qubits)
mask = "".join(["1" if n_qubits - 1 - k in pauli_index else "0"
for k in range(n_qubits)])
for single_pauli, index in zip(pauli_id, pauli_index):
if single_pauli == 1:
measurement_circuit.add_H_gate(index)
elif single_pauli == 2:
measurement_circuit.add_Sdag_gate(index)
measurement_circuit.add_H_gate(index)
measurement_circuit.update_quantum_state(buf_state)
samples = buf_state.sampling(n_sample)
mask = int(mask, 2)
exp += (coef
*sum(list(map(lambda x: (-1)**(bin(x & mask).count("1")),
samples)))
/n_sample)
return exp
def adaptive_sample_observable(state, obs, n_sample):
"""
Args:
state (qulacs.QuantumState):
obs (qulacs.Observable)
n_sample (int): number of samples for each observable
Return:
:float: sampled expectation value of the observable
"""
n_term = obs.get_term_count()
n_qubits = obs.get_qubit_count()
exp = 0
buf_state = QuantumState(n_qubits)
### check the coefficients for each term...
coef_list = np.array([abs(obs.get_term(i).get_coef())
for i in range(n_term)])
sum_coef = np.sum(coef_list)
### sort
sorted_indices = np.argsort(-coef_list)
coef_list.sort()
#sorted_coef_list = [coef_list[i] for i in sorted_indices]
### determine sampling wight
n_sample_total = n_sample*n_term
n_sample_list = n_sample_total*coef_list//sum_coef
n_count = np.sum(n_sample_list)
n_rest = n_sample_total - n_count
n_sample_list[sorted_indices[:n_rest]] += 1
j = 0
for i in range(n_term):
if n_sample_list[i] == 0:
continue
j += n_sample_list[i]
pauli_term = obs.get_term(i)
coef = pauli_term.get_coef()
pauli_id = pauli_term.get_pauli_id_list()
pauli_index = pauli_term.get_index_list()
if len(pauli_id) == 0: # means identity
exp += coef
continue
buf_state.load(state)
measurement_circuit = QuantumCircuit(n_qubits)
mask = "".join(["1" if n_qubits - 1 - k in pauli_index else "0"
for k in range(n_qubits)])
for single_pauli, index in zip(pauli_id, pauli_index):
if single_pauli == 1:
measurement_circuit.add_H_gate(index)
elif single_pauli == 2:
measurement_circuit.add_Sdag_gate(index)
measurement_circuit.add_H_gate(index)
measurement_circuit.update_quantum_state(buf_state)
samples = buf_state.sampling(n_sample_list[i])
mask = int(mask, 2)
exp += (coef
*sum(list(map(lambda x: (-1)**(bin(x & mask).count("1")),
samples)))
/n_sample_list[i])
return exp
def test_observable(state, obs, obsZ, n_sample):
"""Function
Args:
state (qulacs.QuantumState): This includes entangled ancilla
(n_qubits = n_qubit_system + 1)
obs (qulacs.Observable): This does not include ancilla Z
(n_qubit_system)
obsZ (qulacs.Observable): Single Pauli Z for ancilla (1)
poststate0 (qulacs.QuantumState): post-measurement state
when ancilla = 0 (n_qubit_system)
poststate1 (qulacs.QuantumState): post-measurement state
when ancilla = 1 (n_qubit_system)
n_sample (int): number of samples for each observable
Return:
:float: sampled expectation value of the observable
Author(s): Takashi Tsuchimochi
"""
n_term = obs.get_term_count()
n_qubits = obs.get_qubit_count()
p0 = state.get_zero_probability(n_qubits)
p1 = 1 - p0
opt = f"0{n_qubits}b"
expH = 0
exp = []
coef = []
buf_state = QuantumState(n_qubits)
for i in range(n_term):
pauli_term = obs.get_term(i)
coef.append(pauli_term.get_coef().real)
pauli_id = pauli_term.get_pauli_id_list()
pauli_index = pauli_term.get_index_list()
if len(pauli_id) == 0: # means identity
exp.extend(coef)
continue
buf_state.load(state)
measurement_circuit = QuantumCircuit(n_qubits)
mask = "".join(["1" if n_qubits - 1 - k in pauli_index else "0"
for k in range(n_qubits)])
measure_observable = QubitOperator((), 1)
for single_pauli, index in zip(pauli_id, pauli_index):
if single_pauli == 1:
### X
measurement_circuit.add_H_gate(index)
measure_observable *= QubitOperator(f"X{index}")
elif single_pauli == 2:
### Y
measurement_circuit.add_Sdag_gate(index)
measurement_circuit.add_H_gate(index)
measure_observable *= QubitOperator(f"Y{index}")
elif single_pauli == 3:
### Z
measure_observable *= QubitOperator(f"Z{index}")
qulacs_measure_observable \
= create_observable_from_openfermion_text(
str(measure_observable))
measurement_circuit.update_quantum_state(buf_state)
#exp.append(obsZ.get_expectation_value(buf_state).real)
samples = buf_state.sampling(n_sample)
#print(f"samples? {format(samples[0], opt)}")
#print(f"I = {i:5d} h_I = {coef[i]:10.5f} <P_I> = {exp[i]:10.5f}")
#mask = int(mask, 2)
#print(sum(list(map(lambda x: (-1)**(bin(x & mask).count('1')),
# samples))))
#print(coef*sum(list(map(lambda x: (-1)**(bin(x & mask).count('1')),
# samples))))
expH += coef[i]*exp[i]
samples = buf_state.sampling(n_sample)
mask = int(mask, 2)
prob = (sum(list(map(lambda x: (-1)**(bin(x & mask).count("1")),
samples)))
/n_sample)
measure_list = list(map(int, np.ones(n_qubits)*2))
for j in pauli_index:
measure_list[j] = 1
#print(qulacs_measure_observable.get_expectation_value(state))
expH += coef[i]*prob
#print(f"coef: {coef[i]:10.5f} prob: {prob:10.5f}")
return expH
