def output_state(dx,dy,dz):
I_f = np.array([[1, 0],
[0, 1]])
I = np.array([[1, 0],
[0, 1]])
X_f = np.array([[0, 1],
[1, 0]])
X = np.array([[0, 1],
[1, 0]])
for q in range(1):
I_f = np.kron(I_f, I)
X_f = np.kron(X_f, X)
J = Operator(1 / np.sqrt(2) * (I_f + 1j * X_f))
J_dg = J.adjoint()
circ = QuantumCircuit(2,2)
circ.append(J, range(2))
for q in range(2):
circ.append(RXGate(dx),[q])
circ.append(RYGate(dy),[q])
circ.append(RZGate(dz),[q])
circ.append(J_dg, range(2))
backend = Aer.get_backend('statevector_simulator')
job = backend.run(circ)
result = job.result()
outputstate = result.get_statevector(circ, decimals=5)
return outputstate
def crear_circuito(n, tipo):
I_f = np.array([[1, 0], [0, 1]])
I = np.array([[1, 0], [0, 1]])
X_f = np.array([[0, 1], [1, 0]])
X = np.array([[0, 1], [1, 0]])
for q in range(n - 1):
I_f = np.kron(I_f, I)
X_f = np.kron(X_f, X)
J = Operator(1 / np.sqrt(2) * (I_f + 1j * X_f))
J_dg = J.adjoint()
circ = QuantumCircuit(n, n)
circ.append(J, range(n))
if n == 1:
dx = np.pi
dy = 0
dz = 0
elif n == 2:
# barrido
dx = tipo[0]
dy = tipo[1]
dz = tipo[2]
for q in range(n):
circ.append(RXGate(dx), [q])
circ.append(RYGate(dy), [q])
circ.append(RZGate(dz), [q])
circ.append(J_dg, range(n))
circ.measure(range(n), range(n))
return circ
def _format_povms(povms: Sequence[any]) -> Tuple[Tuple[np.ndarray, ...], ...]:
"""Format sequence of basis POVMs"""
formatted_povms = []
# Convert from operator/channel to POVM effects
for povm in povms:
if isinstance(povm, (list, tuple)):
# POVM is already an effect
formatted_povms.append(povm)
continue
# Convert POVM to operator of quantum channel
try:
chan = Operator(povm)
except QiskitError:
chan = SuperOp(povm)
adjoint = chan.adjoint()
dims = adjoint.input_dims()
dim = np.prod(dims)
effects = tuple(DensityMatrix.from_int(i, dims).evolve(adjoint) for i in range(dim))
formatted_povms.append(effects)
# Format POVM effects to density matrix matrices
return tuple(tuple(DensityMatrix(effect).data for effect in povm) for povm in formatted_povms)
