def post_measurement_state_update(dim, numA, numB, cmat_in, subP):
dim_list = np.arange(dim)
new_coef_mat = complex(1, 0) * np.zeros((dim**numA, dim**numB))
normK = 0
if subP == 'P1':
indA2 = 0
#Application of measurement condition
for indA1 in range(dim**numA): #fix row of updated state
for indB1 in range(dim**numB): #fix col of updated state
for indB2 in range(
dim**numB): #loop through other coefficients
row, col = index_convert(dim, numA, numB, indA1, indB1,
indA2, indB2)
new_coef_mat[indA1, indB1] += cmat_in[row, col]
normK += cmat_in[row, col] #calculate normK while updating
new_coef_mat = new_coef_mat / normK
elif subP == 'P2':
indB2 = 0
#Application of measurement condition
for indA1 in range(dim**numA): #fix row of updated state
for indB1 in range(dim**numB): #fix col of updated state
for indA2 in range(
dim**numA): #loop through other coefficients
row, col = index_convert(dim, numA, numB, indA1, indB1,
indA2, indB2)
new_coef_mat[indA1, indB1] += cmat_in[row, col]
normK += cmat_in[row, col] #calculate normK while updating
new_coef_mat = new_coef_mat / normK
return normK, new_coef_mat
def lowerA(dim, numA, numB, row, col, target_node, adj_mat, new_coef_mat,
current_coef):
cutAdjRow = adj_mat[target_node - 1, numA:(numA + numB)]
cutBasisVec = getbasisR(numA + numB)[target_node - 1][0:numA]
indA1, indA2, indB1, indB2 = get_two_state_indices(dim, numA, numB, row,
col)
labB2 = list(product(np.arange(dim), repeat=numB))[indB2]
labA2 = list(product(np.arange(dim), repeat=numA))[indA2]
labA1 = list(product(np.arange(dim), repeat=numA))[indA1]
for n in range(dim):
outLabB2 = (labB2 + n * cutAdjRow) % dim
indB2 = match_labB_to_indB(dim, outLabB2)
for m in range(0, dim):
outLabA1 = (labA1 + m * cutBasisVec) % dim
indA1 = match_labA_to_indA(dim, outLabA1)
cf = (1 / dim) * exp(
(2 * pi * complex(0, 1) / dim) * ((n * labA2[target_node - 1] +
(dim - m * n)) % dim))
new_row, new_col = index_convert(dim, numA, numB, indA1, indB1,
indA2, indB2)
new_coef_mat[new_row, new_col] += cf * current_coef
return new_coef_mat
def qudit_through_channel(dim, numA, numB, adj_mat, target_node, state_copy,
coef_mat, param):
input_coef_mat = np.copy(coef_mat)
new_coef_mat = (1 - param) * np.copy(coef_mat)
Alabels = list(product(np.arange(0, dim), repeat=numA))
Blabels = list(product(np.arange(0, dim), repeat=numB))
for x in range(dim**2):
error_label = list(product(np.arange(0, dim), repeat=2))[x]
for row in range(dim**(2 * numA)):
for col in range(dim**(2 * numB)):
indA1, indA2, indB1, indB2 = get_two_state_indices(
dim, numA, numB, row, col)
current_coef = input_coef_mat[row, col]
if state_copy == 'first':
if current_coef > 0:
labelIn = np.array(Alabels[indA1] + Blabels[indB1])
#create list of effected labels
altered = []
labelOut = label_update(dim, adj_mat, target_node,
labelIn, error_label)
if compare_labels(labelOut, labelIn):
altered.append(labelOut)
#determine which coefficients need to change and change them
try:
for entry in range(np.shape(altered)[0]):
#graphs state basis label of coefficient to be updated
focus = altered[entry]
#get matrix indices of label
id_indA1, id_indB1 = match_label_to_index(
dim, numA, numB, focus)
#convert back to row and col of new_coef_mat
id_row, id_col = index_convert(
dim, numA, numB, id_indA1, id_indB1, indA2,
indB2)
#update coeficient matrix
new_coef_mat[id_row, id_col] += current_coef * (
param / (dim**2 - 1))
except UnboundLocalError:
continue
elif state_copy == 'second':
if current_coef > 0:
labelIn = np.array(Alabels[indA2] + Blabels[indB2])
#create list of effected labels
altered = []
labelOut = label_update(dim, adj_mat, target_node,
labelIn, error_label)
if compare_labels(labelOut, labelIn):
altered.append(labelOut)
try:
#determine which coefficients need to change and change them
for entry in range(np.shape(altered)[0]):
#graphs state basis label of coefficient to be updated
focus = altered[entry]
#get matrix indices of label
id_indA2, id_indB2 = match_label_to_index(
dim, numA, numB, focus)
#convert back to row and col of new_coef_mat
id_row, id_col = index_convert(
dim, numA, numB, indA1, indB1, id_indA2,
id_indB2)
#update coeficient matrix
new_coef_mat[id_row, id_col] += current_coef * (
param / (dim**2 - 1))
except UnboundLocalError:
continue
return new_coef_mat