def signal_handler(sig, frame, exit=True):
print('You pressed Ctrl+C! Priting logs...')
model.load_weights(os.path.join(log_path, 'checkpoint'))
print(*model.variables, sep='\n')
# Write the summary to the log dir (so that we can reconstruct the model later on with the Variables
with open(os.path.join(log_path, 'summary.txt'), 'w') as f:
with redirect_stdout(f):
model.summary()
model.save(log_path)
model_matrix = model.model_matrix()
ndtotext_print(model_matrix)
# Sanity check: test the model against target
real_output = model.target_model(input)
model_output = model_matrix @ input
print('Sanity check loss:', loss(real_output, model_output).numpy())
std_loss = StdFidelity()
print('Sanity check loss std:',
std_loss(real_output, model_output).numpy())
# hs_norm = OperatorFidelity(model)
# print('Hilbert–Schmidt/Frobenius norm:', hs_norm())
# and check if it's the real inverse!
if exit:
sys.exit(0)
def on_epoch_end(self, epoch, logs=None):
print()
mm = model.model_matrix()
ndtotext_print(mm)
loss1 = loss(output, model(input))
loss2 = loss(output, mm @ input)
print('loss on call', loss1)
print('loss on mm', loss2)
def signal_handler(sig, frame, exit=True):
print('You pressed Ctrl+C! Priting logs...')
model.load_weights(os.path.join(log_path, 'checkpoint'))
print(*model.variables, sep='\n')
# Write the summary to the log dir (so that we can reconstruct the model later on with the Variables
with open(os.path.join(log_path, 'summary.txt'), 'w') as f:
with redirect_stdout(f):
model.summary()
model.save(log_path)
model_matrix = model.model_matrix()
ndtotext_print(model_matrix)
# Sanity check: test the QFT_U against QFT on all data
qft_layer = QFTLayer()
real_output = qft_layer(input)
model_output = model_matrix @ input
print('Sanity check loss:', loss(real_output, model_output).numpy())
std_loss = StdFidelity()
print('Sanity check loss std:',
std_loss(real_output, model_output).numpy())
hs_norm = OperatorFidelity(model)
print('Hilbert–Schmidt/Frobenius norm:', hs_norm())
# and check if it's the real inverse!
targets = None
if hasattr(model, 'targets'):
targets = model.targets
iqft_layer = IQFTLayer(targets)
iqft_layer(input)
eye = iqft_layer.matrix() @ model_matrix
print('Eye:')
ndtotext_print(eye)
print('Eye norm:')
ndtotext_print(np.abs(eye))
if exit:
sys.exit(0)
qubit_order=[C1,C2,T1,T2] # U00 qc.append(cirq.XX.on(C1, C2)) # -- qc.append(cirq.SWAP.on(T1, T2).controlled_by(C1, C2)) qc.append(cirq.Z.on(T2).controlled_by(C1, C2, T1)) qc.append(cirq.Z.on(T1).controlled_by(C1, C2)) qc.append(cirq.Z.on(T2).controlled_by(C1, C2)) qc.append(cirq.XX.on(C1, C2)) # -- # # U11 qc.append(cirq.SWAP.on(T1, T2).controlled_by(C1, C2)) qc.append(cirq.Z.on(T2).controlled_by(C1, C2, T1)) qc.append(cirq.Z.on(C2).controlled_by(C1)) XX_B(qc, C1, C2) # Up qc.append(cirq.XX.on(C1, C2)) # -- qc.append(cirq.Z.on(T1).controlled_by(C1, C2)) qc.append(cirq.Z.on(T2).controlled_by(C1, C2)) qc.append(cirq.Z.on(C2).controlled_by(C1)) # PHASE qc.append(cirq.XX.on(C1, C2)) # -- #Um # PHASE XX_B(qc, C1, C2) ndtotext_print(qc.unitary(qubit_order=qubit_order)) U_pi = np.array(U(pi).tolist()).astype(np.float64) ndtotext_print(U_pi) ndtotext_print(U_pi - qc.unitary(qubit_order=qubit_order))
import cirq from tfq_diamond import U import numpy as np from txtutils import ndtotext_print π = np.pi qubits = cirq.GridQubit.rect(2, 2) C1, C2, T1, T2 = qubits qc = cirq.Circuit() t = 1 qc.append(U(π).on(*qubits)) qc.append(cirq.XX.on(T1, T2)**t) qc.append(U(π).on(*qubits)) ndtotext_print(qc.unitary()) qc = cirq.Circuit() t = 1 qc.append(cirq.I.on(C1)) qc.append(cirq.I.on(C2)) qc.append(cirq.XX.on(T1, T2)**t) ndtotext_print(qc.unitary())
if __name__ == '__main__':
from tf_qc.utils import random_pure_states
from txtutils import ndtotext_print
data = random_pure_states((2, 2**2, 1))
l_u3 = U3Layer()
l_u3(data)
l_u3.variables[0].assign([0])
l_u3.variables[1].assign([0])
l_u3.variables[2].assign([0])
l_u3.variables[3].assign([0])
l_u3.variables[4].assign([π / 2])
l_u3.variables[5].assign([π])
print(*l_u3.variables, sep='\n')
ndtotext_print(l_u3.matrix)
data_data = lambda N: tf.keras.layers.Input(
(2**N, 1), batch_size=2, dtype=complex_type)
data = lambda N: random_pure_states((2, 2**N, 1))
l1 = ULayer()
l2 = ULayer([[0, 1, 2, 3], [4, 5, 6, 7]])
l1(data(8))
l2(data(8))
l1.thetas = l2.thetas
assert tf.reduce_all(l1.matrix() == l2.matrix())
l1 = ULayer()
l_I1 = ILayer()
l2 = ULayer([[0, 1, 2, 3], [4, 5, 6, 7]])
l1(data(8))
import itertools
π = np.pi
# t = sympy.Symbol('t', real=True)
t = 1
U_pi = U(π)
C1, C2, T1, T2 = cirq.GridQubit(0,0), cirq.GridQubit(1,1), cirq.GridQubit(1,0), cirq.GridQubit(0,1)
qubit_order=[C1,C2,T1,T2]
qc = cirq.Circuit()
qc.append(U_pi.on(C1,C2,T1,T2))
qc.append(cirq.ZPowGate(exponent=t/π).on(T2)) # Z(t)
qc.append(U_pi.on(C1,C2,T1,T2))
ndtotext_print(qc.unitary(qubit_order=qubit_order))
sim = cirq.Simulator()
seq = itertools.product([False, True], repeat=4)
for i,j,k,l in seq:
qc = cirq.Circuit() # Clear circuit
if i:
qc.append(cirq.X.on(C1))
else:
qc.append(cirq.I.on(C1))
if j:
qc.append(cirq.X.on(C2))
else:
qc.append(cirq.I.on(C2))
CNS(qc, B[2], B[3], A[2], A[1])
qc.append(Rn_dag(4).on(A[2]))
CNS(qc, B[2], B[3], A[1], A[2])
# CNS(qc, B[0], B[1], A[1], A[0]) ##
qc.append(Rn(5).on(A[1]))
qc.append(Rn(5).on(A[3]))
# CNS(qc, B[0], B[1], A[0], A[1]) ##
CNS(qc, B[0], B[1], A[1], A[2]) ##
CNS(qc, B[4], B[5], A[3], A[2])
qc.append(Rn_dag(5).on(A[3]))
CNS(qc, B[4], B[5], A[2], A[3])
CNS(qc, B[0], B[1], A[2], A[1]) ##
CNS(qc, B[0], B[1], A[1], A[0]) ##
matrix = qc.unitary(qubit_order=B+A)[:2**n_qft,:2**n_qft]
ndtotext_print(matrix) # Picked out for all B=0
qc_true = cirq.Circuit()
qc_true.append(cirq.H(A[0]))
qc_true.append(Rn(2).on(A[0]).controlled_by(A[1]))
qc_true.append(Rn(3).on(A[0]).controlled_by(A[2]))
qc_true.append(Rn(4).on(A[0]).controlled_by(A[3]))
matrix_true = qc_true.unitary(qubit_order=A)
ndtotext_print(matrix_true)
print('diff')
ndtotext_print(matrix_true - matrix)
# --- Reduced circuit ---
qc_reduced = cirq.Circuit()
qc_reduced.append(cirq.H(A[0]))
import cirq
from txtutils import ndtotext_print
import numpy as np
import sympy
from tfq_diamond import U
π = np.pi
U_pi = U(π)
iswap_1 = cirq.riswap(3 * π / 2) # Apposite sign to sympy!!!
iswap_2 = cirq.riswap(π / 2)
print('iSWAP(π/2) [NOT THE ONE WE USE, BUT MIGHT WORK ANYWAY!]')
ndtotext_print(iswap_1._unitary_())
print('iSWAP(3π/2)')
ndtotext_print(iswap_2._unitary_())
def Rn(n):
return cirq.ZPowGate()**(2**(1 - n))
qc_test = cirq.Circuit()
q = cirq.GridQubit(1, 1)
qc_test.append(Rn(5).on(q))
print(qc_test)
print(qc_test.unitary())
print('Should be:', np.exp(2 * π * 1j / 2**5))
assert np.isclose(qc_test.unitary()[1, 1], np.exp(2 * π * 1j / 2**5))
n_qft = 2
import cirq
from txtutils import ndtotext_print
import numpy as np
import sympy
from tfq_diamond import U
from typing import *
π = np.pi
U_pi = U(π)
iswap_1 = cirq.riswap(3 * π / 2) # Apposite sign to sympy!!!
iswap_2 = cirq.riswap(π / 2)
print('iSWAP(π/2) [NOT THE ONE WE USE, BUT MIGHT WORK ANYWAY!]')
ndtotext_print(iswap_1._unitary_())
print('iSWAP(3π/2)')
ndtotext_print(iswap_2._unitary_())
def Rn(n):
return cirq.ZPowGate()**(2**(1 - n))
qc_test = cirq.Circuit()
q = cirq.GridQubit(1, 1)
qc_test.append(Rn(5).on(q))
print(qc_test)
print(qc_test.unitary())
print('Should be:', np.exp(2 * π * 1j / 2**5))
assert np.isclose(qc_test.unitary()[1, 1], np.exp(2 * π * 1j / 2**5))
import cirq
from txtutils import ndtotext_print
import numpy as np
import sympy
π = np.pi
print('iSWAP(π/2) [NOT THE ONE WE USE, BUT MIGHT WORK ANYWAY!]')
ndtotext_print(cirq.riswap(π / 2)._unitary_())
print('iSWAP(π/2) @ iSWAP(3π/2)')
ndtotext_print(
cirq.riswap(π / 2)._unitary_() @ cirq.riswap(3 * π / 2)._unitary_())
n_qft = 5
A = [cirq.GridQubit(0, i) for i in range(n_qft)]
B = [cirq.GridQubit(1, i) for i in range(n_qft)]
'''
A1 - B1
| |
A2 - B2
| |
A3 - B3
.
.
.
'''
qc = cirq.Circuit()
# Input data
input_values = [1, 1, 1]
for i, value in enumerate(input_values):
from typing import *
π = np.pi
# ---- GOOD -----
qc = cirq.Circuit()
C1, C2, T1, T2 = cirq.GridQubit(0, 0), cirq.GridQubit(1, 1), cirq.GridQubit(
1, 0), cirq.GridQubit(0, 1)
qc.append(cirq.SWAP.on(T1, T2))
qc.append(cirq.H.on(T1))
qc.append(cirq.Z.on(T1))
qc.append(cirq.Z.on(T2))
qc.append(U(π).on(C1, C2, T1, T2))
qc.append(cirq.H.on(T2))
ndtotext_print(qc.unitary(qubit_order=[C1, C2, T1, T2]))
# ---- BAD -----
qc2 = cirq.Circuit()
qc2.append(cirq.XX.on(C1, C2))
qc2.append(cirq.H.on(T2))
qc2.append(U(π).on(C1, C2, T1, T2))
qc2.append(cirq.H.on(T1))
qc2.append(cirq.XX.on(C1, C2))
qc2.append(U(π).on(C1, C2, T1, T2))
ndtotext_print(qc2.unitary(qubit_order=[C1, C2, T1, T2]))
