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slight fixes

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This commit is contained in:
Daniel Tsvetkov 2020-03-26 17:30:51 +01:00
parent beffc3ab2c
commit 26bc532a81
2 changed files with 42 additions and 16 deletions
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39
lib_q_computer_math.py
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@ -141,8 +141,9 @@ class State(Vector):
super().__init__(m, *args, **kwargs) super().__init__(m, *args, **kwargs)
self.name = name self.name = name
self.measurement_result = None self.measurement_result = None
if not self._is_normalized(): # TODO: SHOULD WE NORMALIZE?
raise TypeError("Not a normalized state vector") # if not self._is_normalized():
# raise TypeError("Not a normalized state vector")
def _is_normalized(self): def _is_normalized(self):
return np.isclose(np.sum(np.abs(self.m ** 2)), 1.0) return np.isclose(np.sum(np.abs(self.m ** 2)), 1.0)
@ -297,11 +298,12 @@ class State(Vector):
measurement_result = random.choices(choices_0, weights_0)[0][qubit_n - 1] measurement_result = random.choices(choices_0, weights_0)[0][qubit_n - 1]
# TODO: Verify if this is the correct collapse to lower dimension after partial measurement # TODO: Verify if this is the correct collapse to lower dimension after partial measurement
# https://www.youtube.com/watch?v=MG_9JWsrKtM&list=PL1826E60FD05B44E4&index=16 # https://www.youtube.com/watch?v=MG_9JWsrKtM&list=PL1826E60FD05B44E4&index=16
normalization_factor = np.sqrt(np.sum([self.m[i][0] for i in indexes_for_p_0])) normalization_factor = np.sqrt(np.sum(np.abs([self.m[i][0] for i in indexes_for_p_0])**2))
# TODO: This can be 0... # TODO: This can be 0...
self.m = [ post_measurement_state = [
[(self.m[i][0] ** 2) / normalization_factor] for i in indexes_for_p_0 [self.m[i][0] / normalization_factor] for i in indexes_for_p_0
] ]
self.m = s('|' + measurement_result + '>') * State(post_measurement_state)
return measurement_result return measurement_result
def pretty_print(self): def pretty_print(self):
@ -337,16 +339,16 @@ class State(Vector):
def test_measure_partial(): def test_measure_partial():
state = s("|010>") state = b_00
state.measure_partial(2) state.measure_partial(1)
def normalize_state(state_vector: ListOrNdarray): def normalize_state(vector: Vector):
"""Normalize a state by dividing by the square root of sum of the squares of states""" """Normalize a state by dividing by the square root of sum of the squares of states"""
norm_coef = np.sqrt(np.sum(np.array(state_vector) ** 2)) norm_coef = np.sqrt(np.sum(np.array(vector.m) ** 2))
if norm_coef == 0: if norm_coef == 0:
raise TypeError("zero-sum vector") raise TypeError("zero-sum vector")
return state_vector / norm_coef return State(vector.m / norm_coef)
def s(q, name=None): def s(q, name=None):
@ -530,7 +532,7 @@ class HermitianOperator(LinearTransformation, HermitianMatrix):
def operator_func(self, other): def operator_func(self, other):
"""This might not return a normalized state vector so don't wrap it in State""" """This might not return a normalized state vector so don't wrap it in State"""
return np.dot(self.m, other.m) return Vector(np.dot(self.m, other.m))
def __repr__(self): def __repr__(self):
if self.name: if self.name:
@ -1184,6 +1186,7 @@ def test_quantum_processor():
def test_light(): def test_light():
# http://alienryderflex.com/polarizer/
# TODO: Are these measurement operators the correct way to represent hor/ver/diag filter? # TODO: Are these measurement operators the correct way to represent hor/ver/diag filter?
# No, becuase they are not unitaries # No, becuase they are not unitaries
hor_filter = MeasurementOperator.create_from_prob(Matrix(_0.m), name='h') hor_filter = MeasurementOperator.create_from_prob(Matrix(_0.m), name='h')
@ -1191,17 +1194,21 @@ def test_light():
ver_filter = MeasurementOperator.create_from_prob(Matrix(_1.m), name='v') ver_filter = MeasurementOperator.create_from_prob(Matrix(_1.m), name='v')
# create random light/photon # create random light/photon
random_pol = [[np.random.uniform(0, 1)], [np.random.uniform(0, 1)]] random_pol = Vector([[np.random.uniform(0, 1)], [np.random.uniform(0, 1)]])
random_light = State(normalize_state(random_pol)) random_light = normalize_state(random_pol)
# TODO: Doesn't work...
qc = QuantumCircuit(1, initial_steps=[[random_light]]) qc = QuantumCircuit(1, initial_steps=[[random_light]])
qc.add_row([hor_filter, ver_filter])
qc.print()
qp = QuantumProcessor(qc)
qp.print_sample(qp.get_sample(100))
# add three filters as operators # add three filters as operators
# qc.add_row([hor_filter, ver_filter]) qc = QuantumCircuit(1, initial_steps=[[random_light]])
qc.add_row([hor_filter, diag_filter, ver_filter]) qc.add_row([hor_filter, diag_filter, ver_filter])
qc.print() qc.print()
qp = QuantumProcessor(qc) qp = QuantumProcessor(qc)
# TODO: This doesn't work - dealing with non-normalized state vectors
# - When measured in horizontal filter, the state vector has a positive |0> and 0 for |1>
qp.print_sample(qp.get_sample(100)) qp.print_sample(qp.get_sample(100))

19
play.py Normal file
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@ -0,0 +1,19 @@
import numpy as np
from lib_q_computer_math import Vector, Matrix, MeasurementOperator, _0, _1, _p, normalize_state
def main():
random_pol = Vector([[np.random.uniform(0, 1)], [np.random.uniform(0, 1)]])
random_light = normalize_state(random_pol)
hor_filter = MeasurementOperator.create_from_prob(Matrix(_0.m), name='h')
diag_filter = MeasurementOperator.create_from_prob(Matrix(_p.m), name='d')
ver_filter = MeasurementOperator.create_from_prob(Matrix(_1.m), name='v')
print(hor_filter.on(_0))
print(ver_filter.on(_0))
print(ver_filter.on(hor_filter.on(_0)))
print(ver_filter.on(diag_filter.on(hor_filter.on(_0))))
print()
if __name__ == "__main__":
main()