Clifford Simulation

A special backend in qibo supports the simulation of Clifford circuits. This qibo.backends.clifford.CliffordBackend backend implements the phase-space formalism introduced in https://arxiv.org/abs/quant-ph/0406196 to efficiently simulate gate application and measurements sampling in the stabilizers state representation. The execution of a circuit through this backend creates a qibo.quantum_info.clifford.Clifford object that gives access to the final measured samples through the qibo.quantum_info.clifford.Clifford.samples() method, similarly to qibo.result.CircuitResult. The probabilities and frequencies are computed starting from the samples by the qibo.quantum_info.clifford.Clifford.frequencies() and qibo.quantum_info.clifford.Clifford.probabilities() methods.

It is also possible to recover the standard state representation with the qibo.quantum_info.clifford.Clifford.state() method. Note, however, that this process is inefficient as it involves the construction of all the stabilizers starting from the generators encoded inside the symplectic matrix.

As for the other backends, the Clifford backend can be set with

import qibo
qibo.set_backend("clifford", platform="numpy")

by specifying the engine used for calculation, if not provided the current backend is used

import qibo

# setting numpy as the global backend
qibo.set_backend("numpy")
# the clifford backend will use the numpy backend as engine
backend = qibo.backends.CliffordBackend()

Alternatively, a Clifford circuit can also be executed starting from the qibo.quantum_info.clifford.Clifford object

from qibo.quantum_info import Clifford, random_clifford

nqubits = 2
circuit = random_clifford(nqubits)
result = Clifford.from_circuit(circuit)