def evolve(self, rho: Density) -> Density:
"""Apply the action of this channel upon a density"""
N = rho.qubit_nb
qubits = rho.qubits
indices = list([qubits.index(q) for q in self.qubits]) + \
list([qubits.index(q) + N for q in self.qubits])
tensor = bk.tensormul(self.tensor, rho.tensor, indices)
return Density(tensor, qubits, rho.memory)
def __matmul__(self, other: 'Gate') -> 'Gate':
"""Apply the action of this gate upon another gate
Note that gate1 must contain all the qubits of qate0
"""
if not isinstance(other, Gate):
raise NotImplementedError()
gate0 = self
gate1 = other
indices = [gate1.qubits.index(q) for q in gate0.qubits]
tensor = bk.tensormul(gate0.tensor, gate1.tensor, indices)
return Gate(tensor=tensor, qubits=gate1.qubits)
def __matmul__(self, other: 'Channel') -> 'Channel':
if not isinstance(other, Channel):
raise NotImplementedError()
chan0 = self
chan1 = other
N = chan1.qubit_nb
qubits = chan1.qubits
indices = list([chan1.qubits.index(q) for q in chan0.qubits]) + \
list([chan1.qubits.index(q) + N for q in chan0.qubits])
tensor = bk.tensormul(chan0.tensor, chan1.tensor, indices)
return Channel(tensor, qubits)
def run(self, ket: State) -> State:
"""Apply the action of this gate upon a state"""
qubits = self.qubits
indices = [ket.qubits.index(q) for q in qubits]
tensor = bk.tensormul(self.tensor, ket.tensor, indices)
return State(tensor, ket.qubits, ket.memory)
