"""MBQC simulator
Simulates MBQC by executing the pattern.
"""
from graphix.sim.tensornet import TensorNetworkBackend
from graphix.sim.statevec import StatevectorBackend
[docs]class PatternSimulator:
"""MBQC simulator
Executes the measurement pattern.
"""
[docs] def __init__(self, pattern, backend="statevector", **kwargs):
"""
Parameters
-----------
pattern: :class:`graphix.pattern.Pattern` object
MBQC pattern to be simulated.
backend: str, 'statevector' or 'tensornetwork'
simulation backend (optional), default is 'statevector'.
kwargs: keyword args for specified backend.
.. seealso:: :class:`graphix.sim.statevec.StatevectorBackend`\
:class:`graphix.sim.tensornet.TensorNetworkBackend`
"""
# check that pattern has output nodes configured
assert len(pattern.output_nodes) > 0
if backend == "statevector":
self.backend = StatevectorBackend(pattern, **kwargs)
elif backend in {"tensornetwork", "mps"}:
self.backend = TensorNetworkBackend(pattern, **kwargs)
else:
raise ValueError("unknown backend")
self.pattern = pattern
self.results = self.backend.results
self.state = self.backend.state
self.node_index = []
[docs] def run(self):
"""Perform the simulation.
Returns
-------
state :
the output quantum state,
in the representation depending on the backend used.
"""
self.backend.add_nodes(self.pattern.input_nodes)
for cmd in self.pattern:
if cmd[0] == "N":
self.backend.add_nodes([cmd[1]])
elif cmd[0] == "E":
self.backend.entangle_nodes(cmd[1])
elif cmd[0] == "M":
self.backend.measure(cmd)
elif cmd[0] == "X":
self.backend.correct_byproduct(cmd)
elif cmd[0] == "Z":
self.backend.correct_byproduct(cmd)
elif cmd[0] == "C":
self.backend.apply_clifford(cmd)
else:
raise ValueError("invalid commands")
self.backend.finalize()
return self.backend.state