def test_setting_no_in():
out_ops = _generate_random_paulis(n_qubits=4, n_terms=7)
for oop in out_ops:
expt = ExperimentSetting(zeros_state(oop.get_qubits()), oop)
expt2 = ExperimentSetting.from_str(str(expt))
assert expt == expt2
assert expt2.in_operator == functools.reduce(mul, [sZ(q) for q in oop.get_qubits()], sI())
assert expt2.out_operator == oop
def test_expt_settings_share_ntpb():
expts = [[
ExperimentSetting(zeros_state([0, 1]),
sX(0) * sI(1)),
ExperimentSetting(zeros_state([0, 1]),
sI(0) * sX(1))
],
[
ExperimentSetting(zeros_state([0, 1]),
sZ(0) * sI(1)),
ExperimentSetting(zeros_state([0, 1]),
sI(0) * sZ(1))
]]
for group in expts:
for e1, e2 in itertools.combinations(group, 2):
assert _max_weight_state([e1.in_state, e2.in_state]) is not None
assert _max_weight_operator([e1.out_operator,
e2.out_operator]) is not None
def test_R_operator_fixed_point_2_qubit():
# Check fixed point of operator. See Eq. 5 in Řeháček et al., PRA 75, 042108 (2007).
qubits = [0, 1]
id_setting = ExperimentSetting(in_state=zeros_state(qubits),
out_operator=sI(qubits[0]) * sI(qubits[1]))
zz_setting = ExperimentSetting(in_state=zeros_state(qubits),
out_operator=sZ(qubits[0]) * sI(qubits[1]))
id_result = ExperimentResult(setting=id_setting,
expectation=1,
total_counts=1)
zzplus_result = ExperimentResult(setting=zz_setting,
expectation=1,
total_counts=1)
zz_results = [id_result, zzplus_result]
# Z basis test
r = _R(P00, zz_results, qubits)
actual = r @ P00 @ r
np.testing.assert_allclose(actual, P00, atol=1e-12)
def _state_tomo_settings(qubits: Sequence[int]):
"""Yield settings over itertools.product(I, X, Y, Z).
Used as a helper function for generate_state_tomography_experiment
:param qubits: The qubits to tomographize.
"""
n_qubits = len(qubits)
for o_ops in itertools.product([sI, sX, sY, sZ], repeat=n_qubits):
o_op = functools.reduce(mul, (op(q) for op, q in zip(o_ops, qubits)), sI())
yield ExperimentSetting(
in_state=zeros_state(qubits),
out_operator=o_op,
)
def test_for_negative_probabilities():
# trivial program to do state tomography on
prog = Program(I(0))
# make TomographyExperiment
expt_settings = [ExperimentSetting(zeros_state([0]), pt) for pt in [sI(0), sX(0), sY(0), sZ(0)]]
experiment_1q = TomographyExperiment(settings=expt_settings, program=prog)
# make an abstract compiler
class DummyCompiler(AbstractCompiler):
def get_version_info(self):
return {}
def quil_to_native_quil(self, program: Program):
return program
def native_quil_to_executable(self, nq_program: Program):
return nq_program
# make a quantum computer object
device = NxDevice(nx.complete_graph(1))
qc_density = QuantumComputer(name='testy!',
qam=PyQVM(n_qubits=1,
quantum_simulator_type=ReferenceDensitySimulator),
device=device,
compiler=DummyCompiler())
# initialize with a pure state
initial_density = np.array([[1.0, 0.0], [0.0, 0.0]])
qc_density.qam.wf_simulator.density = initial_density
try:
list(measure_observables(qc=qc_density, tomo_experiment=experiment_1q, n_shots=3000))
except ValueError as e:
# the error is from np.random.choice by way of self.rs.choice in ReferenceDensitySimulator
assert str(e) != 'probabilities are not non-negative'
# initialize with a mixed state
initial_density = np.array([[0.9, 0.0], [0.0, 0.1]])
qc_density.qam.wf_simulator.density = initial_density
try:
list(measure_observables(qc=qc_density, tomo_experiment=experiment_1q, n_shots=3000))
except ValueError as e:
assert str(e) != 'probabilities are not non-negative'
from pyquil.paulis import sI, sZ, sX
from pyquil.quil import Program
from rpcq.messages import PyQuilExecutableResponse
from forest.benchmarking import distance_measures as dm
# Single qubit defs
Q0 = 0
PROJ_ZERO = np.array([[1, 0], [0, 0]])
PROJ_ONE = np.array([[0, 0], [0, 1]])
ID = PROJ_ZERO + PROJ_ONE
PLUS = np.array([[1], [1]]) / np.sqrt(2)
PROJ_PLUS = PLUS @ PLUS.T.conj()
PROJ_MINUS = ID - PROJ_PLUS
ID_SETTING = ExperimentSetting(in_state=zeros_state([Q0]), out_operator=sI(Q0))
Z_SETTING = ExperimentSetting(in_state=zeros_state([Q0]), out_operator=sZ(Q0))
X_SETTING = ExperimentSetting(in_state=zeros_state([Q0]), out_operator=sX(Q0))
# Two qubit defs
P00 = np.kron(PROJ_ZERO, PROJ_ZERO)
P01 = np.kron(PROJ_ZERO, PROJ_ONE)
P10 = np.kron(PROJ_ONE, PROJ_ZERO)
P11 = np.kron(PROJ_ONE, PROJ_ONE)
def test_generate_1q_state_tomography_experiment():
qubits = [0]
prog = Program(I(qubits[0]))
one_q_exp = generate_state_tomography_experiment(prog, qubits=qubits)
dimension = 2**len(qubits)