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effectreps.py
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effectreps.py
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"""
POVM effect representation classes for the `qibo` evolution type.
"""
#***************************************************************************************************
# Copyright 2015, 2019 National Technology & Engineering Solutions of Sandia, LLC (NTESS).
# Under the terms of Contract DE-NA0003525 with NTESS, the U.S. Government retains certain rights
# in this software.
# Licensed under the Apache License, Version 2.0 (the "License"); you may not use this file except
# in compliance with the License. You may obtain a copy of the License at
# http://www.apache.org/licenses/LICENSE-2.0 or in the LICENSE file in the root pyGSTi directory.
#***************************************************************************************************
import numpy as _np
from .. import basereps as _basereps
from pygsti.baseobjs.statespace import StateSpace as _StateSpace
from . import _get_densitymx_mode, _get_nshots
class EffectRep(_basereps.EffectRep):
def __init__(self, state_space):
self.state_space = _StateSpace.cast(state_space)
@property
def nqubits(self):
return self.state_space.num_qubits
class EffectRepComputational(EffectRep):
def __init__(self, zvals, basis, state_space):
self.zvals = zvals
self.basis = basis
super(EffectRepComputational, self).__init__(state_space)
class EffectRepConjugatedState(EffectRep):
def __init__(self, state_rep):
self.state_rep = state_rep
super(EffectRepConjugatedState, self).__init__(state_rep.state_space)
def probability(self, state):
# compute <s2|s1>
assert(_get_densitymx_mode() is True), "Can only use EffectRepConjugatedState when densitymx_mode == True!"
initial_state = state.qibo_state
effect_state = self.state_rep.qibo_state
if effect_state.ndim == 1: # b/c qibo_state can be either a vector or density mx
#Promote this state vector to a density matrix to use it as a POVM effect
effect_state = _np.kron(effect_state[:, None], effect_state.conjugate()[None, :])
assert(effect_state.ndim == 2) # density matrices
qibo_circuit = state.qibo_circuit
results = qibo_circuit(initial_state)
return _np.real_if_close(_np.dot(effect_state.flatten().conjugate(), results.state().flatten()))
def to_dense(self, on_space):
return self.state_rep.to_dense(on_space)
@property
def basis(self):
# (all qibo effect reps need to have a .basis property)
return self.state_rep.basis
class EffectRepComposed(EffectRep):
def __init__(self, op_rep, effect_rep, op_id, state_space):
self.op_rep = op_rep
self.effect_rep = effect_rep
self.op_id = op_id
self.state_space = _StateSpace.cast(state_space)
assert(self.state_space.is_compatible_with(effect_rep.state_space))
super(EffectRepComposed, self).__init__(effect_rep.state_space)
def probability(self, state):
return self.effect_rep.probability(self.op_rep.acton(state))