def test_H2_experiment_perfect(self):
print('\n')
#the RHF H2 energy at equilibrium bond length
E_hf = -1.1166843870661929
#the H2 qubit hamiltonian
circ_vec = [
Circuit(),
build_circuit('Z_0'),
build_circuit('Z_1'),
build_circuit('Z_2'),
build_circuit('Z_3'),
build_circuit('Z_0 Z_1'),
build_circuit('Y_0 X_1 X_2 Y_3'),
build_circuit('Y_0 Y_1 X_2 X_3'),
build_circuit('X_0 X_1 Y_2 Y_3'),
build_circuit('X_0 Y_1 Y_2 X_3'),
build_circuit('Z_0 Z_2'),
build_circuit('Z_0 Z_3'),
build_circuit('Z_1 Z_2'),
build_circuit('Z_1 Z_3'),
build_circuit('Z_2 Z_3')
]
coef_vec = [
-0.098863969784274, 0.1711977489805748, 0.1711977489805748,
-0.222785930242875, -0.222785930242875, 0.1686221915724993,
0.0453222020577776, -0.045322202057777, -0.045322202057777,
0.0453222020577776, 0.1205448220329002, 0.1658670240906778,
0.1658670240906778, 0.1205448220329002, 0.1743484418396386
]
H2_qubit_hamiltonian = QubitOperator()
for i in range(len(circ_vec)):
H2_qubit_hamiltonian.add(coef_vec[i], circ_vec[i])
# circuit for making HF state
circ = Circuit()
circ.add(gate('X', 0, 0))
circ.add(gate('X', 1, 1))
TestExperiment = Experiment(4, circ, H2_qubit_hamiltonian, 1000000)
params2 = []
avg_energy = TestExperiment.perfect_experimental_avg(params2)
print('Perfectly Measured H2 Experimental Avg. Energy')
print(avg_energy)
print('H2 RHF Energy')
print(E_hf)
experimental_error = abs(avg_energy - E_hf)
assert experimental_error == approx(0, abs=1.0e-14)
def test_op_exp_val_1(self):
# test direct expectation value measurement
trial_state = Computer(4)
trial_prep = [None] * 5
trial_prep[0] = gate('H', 0, 0)
trial_prep[1] = gate('H', 1, 1)
trial_prep[2] = gate('H', 2, 2)
trial_prep[3] = gate('H', 3, 3)
trial_prep[4] = gate('cX', 0, 1)
trial_circ = Circuit()
#prepare the circuit
for gate_ in trial_prep:
trial_circ.add(gate_)
# use circuit to prepare trial state
trial_state.apply_circuit(trial_circ)
# gates needed for [a1^ a2] operator
X1 = gate('X', 1, 1)
X2 = gate('X', 2, 2)
Y1 = gate('Y', 1, 1)
Y2 = gate('Y', 2, 2)
# initialize circuits to make operator
circ1 = Circuit()
circ1.add(X2)
circ1.add(Y1)
circ2 = Circuit()
circ2.add(Y2)
circ2.add(Y1)
circ3 = Circuit()
circ3.add(X2)
circ3.add(X1)
circ4 = Circuit()
circ4.add(Y2)
circ4.add(X1)
#build the quantum operator for [a1^ a2]
a1_dag_a2 = QubitOperator()
a1_dag_a2.add(0.0 - 0.25j, circ1)
a1_dag_a2.add(0.25, circ2)
a1_dag_a2.add(0.25, circ3)
a1_dag_a2.add(0.0 + 0.25j, circ4)
#get direct expectatoin value
exp = trial_state.direct_op_exp_val(a1_dag_a2)
assert exp == approx(0.25, abs=2.0e-16)
from pytest import approx
from qforte import Circuit, Computer, gate
import numpy as np
num_qubits = 5
prep_circ = Circuit()
ct_lst = [(4, 3), (4, 2), (4, 1), (4, 0), (3, 2), (3, 1), (3, 0), (2, 1),
(2, 0), (1, 0)]
for i in range(num_qubits):
prep_circ.add(gate('H', i, i))
for i in range(num_qubits):
prep_circ.add(gate('cR', i, i + 1, 1.116 / (i + 1.0)))
def generic_test_circ_vec_builder(qb_list, id):
circ_vec_tc = [Circuit() for i in range(len(qb_list))]
circ_vec_ct = [Circuit() for i in range(len(qb_list))]
for i, pair in enumerate(ct_lst):
t = pair[0]
c = pair[1]
if (id == 'cR'):
circ_vec_ct[i].add(gate(id, t, c, 3.17 * t * c))
circ_vec_tc[i].add(gate(id, c, t, 1.41 * t * c))
else:
circ_vec_ct[i].add(gate(id, t, c))
circ_vec_tc[i].add(gate(id, c, t))
return circ_vec_tc, circ_vec_ct
def test_circ_op_print(self):
# initialize empty circuit
circ1 = Circuit()
# add (Z1 H2 Y4 X4) Pauli string
# note: the rightmost gate is applied first
circ1.add(gate('X', 4))
circ1.add(gate('Y', 4))
circ1.add(gate('H', 2))
circ1.add(gate('Z', 1))
# test built-in print function
out = str(circ1)
assert out == '[Z1 H2 Y4 X4]'
# test smart_print function
with patch('sys.stdout', new=StringIO()) as fake_out:
smart_print(circ1)
assert fake_out.getvalue(
) == '\n Quantum circuit:\n(Z1 H2 Y4 X4) |Ψ>\n'
# initialize empty circuit
circ2 = Circuit()
# add (H1 Y2 S3 I4) Pauli string
# note: the rightmost gate is applied first
circ2.add(gate('I', 4))
circ2.add(gate('S', 3))
circ2.add(gate('Y', 2))
circ2.add(gate('H', 1))
# initialize empty circuit
circ3 = Circuit()
# add (X1 Y2 H3 Z4) Pauli string
# note: the rightmost gate is applied first
circ3.add(gate('Z', 4))
circ3.add(gate('H', 3))
circ3.add(gate('Y', 2))
circ3.add(gate('X', 1))
# initialize empty QubitOperator
q_op = QubitOperator()
# add u1*circ1 + u2*circ2 + u3*circ3
u1 = 0.5 + 0.1j
u2 = -0.5j
u3 = +0.3
q_op.add(u1, circ1)
q_op.add(u2, circ2)
q_op.add(u3, circ3)
# test built-in print function
out = str(q_op)
assert out == '+0.500000 +0.100000i[Z1 H2 Y4 X4]\n'\
'-0.500000j[H1 Y2 S3 I4]\n'\
'+0.300000[X1 Y2 H3 Z4]'
# test smart_print function
with patch('sys.stdout', new=StringIO()) as fake_out:
smart_print(q_op)
assert fake_out.getvalue() == '\n Quantum operator:\n(0.5+0.1j) (Z1 H2 Y4 X4) |Ψ>\n'\
'+ (-0-0.5j) (H1 Y2 S3 I4) |Ψ>\n'\
'+ (0.3+0j) (X1 Y2 H3 Z4) |Ψ>\n'
def test_circuit(self):
print('\n')
num_qubits = 10
qc1 = Computer(num_qubits)
qc2 = Computer(num_qubits)
prep_circ = Circuit()
circ = Circuit()
for i in range(num_qubits):
prep_circ.add(gate('H', i, i))
for i in range(num_qubits):
prep_circ.add(gate('cR', i, i + 1, 1.116 / (i + 1.0)))
for i in range(num_qubits - 1):
circ.add(gate('cX', i, i + 1))
circ.add(gate('cX', i + 1, i))
circ.add(gate('cY', i, i + 1))
circ.add(gate('cY', i + 1, i))
circ.add(gate('cZ', i, i + 1))
circ.add(gate('cZ', i + 1, i))
circ.add(gate('cR', i, i + 1, 3.14159 / (i + 1.0)))
circ.add(gate('cR', i + 1, i, 2.17284 / (i + 1.0)))
qc1.apply_circuit_safe(prep_circ)
qc2.apply_circuit_safe(prep_circ)
qc1.apply_circuit_safe(circ)
qc2.apply_circuit(circ)
C1 = qc1.get_coeff_vec()
C2 = qc2.get_coeff_vec()
diff_vec = [(C1[i] - C2[i]) * np.conj(C1[i] - C2[i])
for i in range(len(C1))]
diff_norm = np.sum(diff_vec)
print('\nNorm of diff vec |C - Csafe|')
print('-----------------------------')
print(' ', diff_norm)
assert diff_norm == approx(0, abs=1.0e-16)