def _cp_condition(channel):
"""Return Choi-matrix eigenvalues for checking if channel is CP"""
if isinstance(channel, QuantumChannel):
if not isinstance(channel, Choi):
channel = Choi(channel)
return np.linalg.eigvalsh(channel.data)
unitary = Operator(channel).data
return np.tensordot(unitary, unitary.conj(), axes=([0, 1], [0, 1])).real
def _tp_condition(channel):
"""Return partial tr Choi-matrix eigenvalues for checking if channel is TP"""
if isinstance(channel, QuantumChannel):
if not isinstance(channel, Choi):
channel = Choi(channel)
choi = channel.data
dims = tuple(np.sqrt(choi.shape).astype(int))
shape = dims + dims
tr_choi = np.trace(np.reshape(choi, shape), axis1=1, axis2=3)
else:
unitary = Operator(channel).data
tr_choi = np.tensordot(unitary, unitary.conj(), axes=(0, 0))
return np.linalg.eigvalsh(tr_choi - np.eye(len(tr_choi)))
