def test_sampler_expectation_value() -> None:
c = Circuit(2)
c.H(0)
c.CX(0, 1)
op = QubitPauliOperator({
QubitPauliString({
Qubit(0): Pauli.Z,
Qubit(1): Pauli.Z
}):
1.0,
QubitPauliString({
Qubit(0): Pauli.X,
Qubit(1): Pauli.X
}):
0.3,
QubitPauliString({
Qubit(0): Pauli.Z,
Qubit(1): Pauli.Y
}):
0.8j,
QubitPauliString({Qubit(0): Pauli.Y}):
-0.4j,
})
b = MySampler()
b.compile_circuit(c)
expectation = get_operator_expectation_value(c,
op,
b,
n_shots=2000,
seed=0)
assert (np.real(expectation), np.imag(expectation)) == pytest.approx(
(1.3, 0.0), abs=0.1)
def test_expectation_value() -> None:
c = Circuit(2)
c.H(0)
c.CX(0, 1)
op = QubitPauliOperator({
QubitPauliString({
Qubit(0): Pauli.Z,
Qubit(1): Pauli.Z
}):
1.0,
QubitPauliString({
Qubit(0): Pauli.X,
Qubit(1): Pauli.X
}):
0.3,
QubitPauliString({
Qubit(0): Pauli.Z,
Qubit(1): Pauli.Y
}):
0.8j,
QubitPauliString({Qubit(0): Pauli.Y}):
-0.4j,
})
b = MyBackend()
b.compile_circuit(c)
assert get_operator_expectation_value(c, op, b) == pytest.approx(1.3)
def objective(params):
circ = ucc.copy()
sym_map = dict(zip(syms, params))
circ.symbol_substitution(sym_map)
return (get_operator_expectation_value(
circ, hamiltonian_op, backend, n_shots=4000) +
nuclear_repulsion_energy)
def objective(params):
circ = ucc(params)
PauliSimp().apply(circ)
FullPeepholeOptimise().apply(circ)
return (get_operator_expectation_value(
circ, hamiltonian_op, backend, n_shots=4000) +
nuclear_repulsion_energy)
def objective(params):
circ = ucc.copy()
sym_map = dict(zip(syms, params))
circ.symbol_substitution(sym_map)
return (get_operator_expectation_value(
circ,
operator,
backend,
n_shots=4000,
partition_strat=PauliPartitionStrat.CommutingSets,
) + nuclear_repulsion_energy)
def objective(params):
circ = ucc(params)
return (get_operator_expectation_value(
circ, hamiltonian_op, backend, n_shots=4000) +
nuclear_repulsion_energy)