def _instruction_states(instructions: List[Instruction]) -> List[np.ndarray]:
"""Construct preparation density matrices from instructions"""
states = []
num_qubits = instructions[0].num_qubits
init = DensityMatrix.from_int(0, 2**num_qubits)
for inst in instructions:
states.append(init.evolve(inst).data)
return states
def _instruction_povms(instructions: List[Instruction]) -> List[Dict[int, np.ndarray]]:
"""Construct measurement outcome POVMs from instructions"""
basis = []
for inst in instructions:
inst_inv = inst.inverse()
basis_dict = {
i: DensityMatrix.from_int(i, 2**inst.num_qubits).evolve(inst_inv).data
for i in range(2**inst.num_qubits)
}
basis.append(basis_dict)
return basis
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)