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circuits_IC.py
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circuits_IC.py
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from qibo.models import Circuit
from qibo import gates
import numpy as np
from qibo.hamiltonians import TFIM
'''
File to construct circuits for PQCs and QRU models with different architectures.
The first class test_circuit is commented, and is the parent to all other classes, inheriting the role of each element as well.
'''
class test_circuit:
def __init__(self, nqubits, nlayers) -> None:
'''
Initial class for circuits. Only placeholder functions.
'''
self.nqubits = nqubits # Size of the circuit
self.nlayers = nlayers # Number of layers in the circuitasured the quantum circuit with
def create_PQC(self):
'''
This function creates data-independent circuits, including architectures and parameters.
The concrete circuits are specified in subsequent classes in this file
'''
self.PQC = Circuit(self.nqubits)
def create_QML(self):
'''
This function creates data-dependent circuits, including architectures and parameters.
The concrete circuits are specified in subsequent classes in this file
'''
self.QML = Circuit(self.nqubits)
def mapper_QML(self, parameters, x):
'''circuit
Auxiliary function to map data x into parameters of the quantum circuit consistently.
The data is passed to the gates repeated times
'''
pass
def energy(self, parameters):
'''
Computation of energy of the output of a PQC
'''
self.PQC.set_parameters(parameters)
return self.ham.expectation(self.PQC.execute().state())
def function(self, parameters, x):
'''
Computation of the hypothesis function for
'''
hyp_fun = np.zeros(len(x))
for i, data in enumerate(x):
self.mapper_QML(parameters, data)
hyp_fun[i] = self.ham.expectation(self.QML.execute().state())
return hyp_fun
class single_qubit_and_entangling(test_circuit):
def __init__(self, nqubits, nlayers):
super().__init__(nqubits, nlayers)
def create_PQC(self):
super().create_PQC()
for l in range(self.nlayers):
for q in range(self.nqubits):
self.PQC.add(gates.RX(q, theta = 0))
self.PQC.add(gates.RZ(q, theta = 0))
self.PQC.add(gates.RX(q, theta = 0))
if l % 2 == 0:
for q in range(0, self.nqubits, 2):
self.PQC.add(gates.CNOT(q, (q+1) % (self.nqubits)))
elif l % 2 != 0:
for q in range(1, self.nqubits, 2):
self.PQC.add(gates.CNOT(q, (q+1) % (self.nqubits)))
for q in range(self.nqubits):
self.PQC.add(gates.RX(q, theta = 0))
self.PQC.add(gates.RZ(q, theta = 0))
self.PQC.add(gates.RX(q, theta = 0))
def create_QML(self):
super().create_QML()
for l in range(self.nlayers):
for q in range(self.nqubits):
self.QML.add(gates.RX(q, theta = 0))
self.QML.add(gates.RZ(q, theta = 0))
self.QML.add(gates.RX(q, theta = 0))
if l % 2 == 0:
for q in range(0, self.nqubits, 2):
self.QML.add(gates.GPI((q + 1) % (self.nqubits), phi = 0).controlled_by(q))
elif l % 2 != 0:
for q in range(1, self.nqubits, 2):
self.QML.add(gates.GPI((q + 1) % self.nqubits, phi = 0).controlled_by(q))
for q in range(self.nqubits):
self.QML.add(gates.RX(q, theta = 0))
self.QML.add(gates.RZ(q, theta = 0))
self.QML.add(gates.RX(q, theta = 0))
def mapper_QML(self, parameters, data):
assert len(parameters) == len(self.PQC.get_parameters())
self.PQC.set_parameters(parameters)
data_parameters = np.zeros(len(self.QML.get_parameters()))
index = 0
for l in range(self.nlayers):
data_parameters[index : index + 3 * self.nqubits] = \
parameters[l * 3 * self.nqubits : (1 + l) * 3 * self.nqubits]
index += 3 * self.nqubits
if l % 2 == 0: size = len(list(range(0, self.nqubits, 2)))
if l % 2 == 1: size = len(list(range(1, self.nqubits, 2)))
data_parameters[index : index + size] = [data] * size
index += size
data_parameters[index : index + 3 * self.nqubits] = \
parameters[self.nlayers * 3 * self.nqubits:]
self.QML.set_parameters(data_parameters)
return data_parameters
class single_qubit(test_circuit):
def __init__(self, nqubits, nlayers):
super().__init__(nqubits, nlayers)
def create_PQC(self):
super().create_PQC()
for l in range(self.nlayers):
for q in range(self.nqubits):
self.PQC.add(gates.RX(q, theta = 0))
self.PQC.add(gates.RZ(q, theta = 0))
self.PQC.add(gates.RX(q, theta = 0))
for q in range(self.nqubits):
self.PQC.add(gates.RX(q, theta = 0))
self.PQC.add(gates.RZ(q, theta = 0))
self.PQC.add(gates.RX(q, theta = 0))
def create_QML(self):
super().create_QML()
for l in range(self.nlayers):
for q in range(self.nqubits):
self.QML.add(gates.RX(q, theta = 0))
self.QML.add(gates.RZ(q, theta = 0))
self.QML.add(gates.RX(q, theta = 0))
if l % 2 == 0:
for q in range(0, self.nqubits, 2):
self.QML.add(gates.GPI((q + 1) % (self.nqubits), phi = 0).controlled_by(q))
elif l % 2 != 0:
for q in range(1, self.nqubits, 2):
self.QML.add(gates.GPI((q + 1) % self.nqubits, phi = 0).controlled_by(q))
for q in range(self.nqubits):
self.QML.add(gates.RX(q, theta = 0))
self.QML.add(gates.RZ(q, theta = 0))
self.QML.add(gates.RX(q, theta = 0))
def mapper_QML(self, parameters, data):
assert len(parameters) == len(self.PQC.get_parameters())
self.PQC.set_parameters(parameters)
data_parameters = np.zeros(len(self.QML.get_parameters()))
index = 0
for l in range(self.nlayers):
data_parameters[index : index + 3 * self.nqubits] = \
parameters[l * 3 * self.nqubits : (1 + l) * 3 * self.nqubits]
index += 3 * self.nqubits
if l % 2 == 0: size = len(list(range(0, self.nqubits, 2)))
if l % 2 == 1: size = len(list(range(1, self.nqubits, 2)))
data_parameters[index : index + size] = [data] * size
index += size
data_parameters[index : index + 3 * self.nqubits] = \
parameters[self.nlayers * 3 * self.nqubits:]
self.QML.set_parameters(data_parameters)
return data_parameters
class permutation_simple(test_circuit):
def __init__(self, nqubits, nlayers):
super().__init__(nqubits, nlayers)
def create_PQC(self):
super().create_PQC()
for l in range(self.nlayers):
for q in range(self.nqubits):
self.PQC.add(gates.RX(q, theta = 0))
def energy(self, parameters):
self.mapper_QML(parameters, 0)
return self.ham.expectation(self.PQC.execute().state())
def create_QML(self):
super().create_QML()
for l in range(self.nlayers):
for q in range(self.nqubits):
self.QML.add(gates.RX(q, theta = 0))
for q in range(0, self.nqubits, 2):
self.QML.add(gates.CNOT(q, (q + 1) % (self.nqubits)))
self.QML.add(gates.RZ((q + 1) % (self.nqubits), theta = 0))
self.QML.add(gates.CNOT(q, (q + 1) % (self.nqubits)))
for q in range(1, self.nqubits, 2):
self.QML.add(gates.CNOT(q, (q + 1) % (self.nqubits)))
self.QML.add(gates.RZ((q + 1) % (self.nqubits), theta = 0))
self.QML.add(gates.CNOT(q, (q + 1) % (self.nqubits)))
def mapper_QML(self, parameters, data):
assert len(parameters) == self.nlayers
pqc_parameters = np.zeros(len(self.PQC.get_parameters()))
qml_parameters = np.zeros(len(self.QML.get_parameters()))
index = 0
for l in range(self.nlayers):
pqc_parameters[l * self.nqubits : (l + 1) * self.nqubits] = [parameters[l]] * self.nqubits
qml_parameters[index : index + self.nqubits] = [parameters[l]] * self.nqubits
index += self.nqubits
qml_parameters[index : index + self.nqubits] = [data] * self.nqubits
index += self.nqubits
self.PQC.set_parameters(pqc_parameters)
self.QML.set_parameters(qml_parameters)
return pqc_parameters, qml_parameters
class permutation_double(test_circuit):
def __init__(self, nqubits, nlayers):
super().__init__(nqubits, nlayers)
def create_PQC(self):
super().create_PQC()
for l in range(self.nlayers):
for q in range(self.nqubits):
self.PQC.add(gates.RX(q, theta = 0))
for q in range(0, self.nqubits, 2):
self.PQC.add(gates.CNOT(q, (q + 1) % (self.nqubits)))
self.PQC.add(gates.RZ((q + 1) % (self.nqubits), theta = 0))
self.PQC.add(gates.CNOT(q, (q + 1) % (self.nqubits)))
for q in range(1, self.nqubits, 2):
self.PQC.add(gates.CNOT(q, (q + 1) % (self.nqubits)))
self.PQC.add(gates.RZ((q + 1) % (self.nqubits), theta = 0))
self.PQC.add(gates.CNOT(q, (q + 1) % (self.nqubits)))
def create_QML(self):
super().create_QML()
for l in range(self.nlayers):
for q in range(self.nqubits):
self.QML.add(gates.RX(q, theta = 0))
for q in range(self.nqubits):
self.QML.add(gates.RX(q, theta = 0))
for q in range(0, self.nqubits, 2):
self.QML.add(gates.CNOT(q, (q + 1) % (self.nqubits)))
self.QML.add(gates.RZ((q + 1) % (self.nqubits), theta = 0))
self.QML.add(gates.CNOT(q, (q + 1) % (self.nqubits)))
for q in range(1, self.nqubits, 2):
self.QML.add(gates.CNOT(q, (q + 1) % (self.nqubits)))
self.QML.add(gates.RZ((q + 1) % (self.nqubits), theta = 0))
self.QML.add(gates.CNOT(q, (q + 1) % (self.nqubits)))
def mapper_QML(self, parameters, data):
assert len(parameters) == 2 * self.nlayers
pqc_parameters = np.zeros(len(self.PQC.get_parameters()))
qml_parameters = np.zeros(len(self.QML.get_parameters()))
index_pqc = 0
index_qml = 0
for i, p in enumerate(parameters):
if i % 2 == 0:
qml_parameters[index_qml : index_qml + self.nqubits] = [data] * self.nqubits
index_qml += self.nqubits
pqc_parameters[index_pqc : index_pqc + self.nqubits] = [p] * self.nqubits
index_pqc += self.nqubits
qml_parameters[index_qml : index_qml + self.nqubits] = [p] * self.nqubits
index_qml += self.nqubits
self.PQC.set_parameters(pqc_parameters)
self.QML.set_parameters(qml_parameters)
return pqc_parameters, qml_parameters
def energy(self, parameters):
self.mapper_QML(parameters, 0)
return self.ham.expectation(self.PQC.execute().state())
class permutation_composed(test_circuit):
def __init__(self, nqubits, nlayers):
super().__init__(nqubits, nlayers)
def create_PQC(self):
super().create_PQC()
for l in range(self.nlayers):
for q in range(self.nqubits):
self.PQC.add(gates.RX(q, theta = 0))
for q in range(0, self.nqubits, 2):
self.PQC.add(gates.CNOT(q, (q + 1) % (self.nqubits)))
self.PQC.add(gates.RZ((q + 1) % (self.nqubits), theta = 0))
self.PQC.add(gates.CNOT(q, (q + 1) % (self.nqubits)))
for q in range(1, self.nqubits, 2):
self.PQC.add(gates.CNOT(q, (q + 1) % (self.nqubits)))
self.PQC.add(gates.RZ((q + 1) % (self.nqubits), theta = 0))
self.PQC.add(gates.CNOT(q, (q + 1) % (self.nqubits)))
def create_QML(self):
super().create_QML()
for l in range(self.nlayers):
for q in range(self.nqubits):
self.QML.add(gates.RY(q, theta = 0))
for q in range(self.nqubits):
self.QML.add(gates.RX(q, theta = 0))
for q in range(0, self.nqubits, 2):
self.QML.add(gates.CNOT(q, (q + 1) % (self.nqubits)))
self.QML.add(gates.RZ((q + 1) % (self.nqubits), theta = 0))
self.QML.add(gates.CNOT(q, (q + 1) % (self.nqubits)))
for q in range(1, self.nqubits, 2):
self.QML.add(gates.CNOT(q, (q + 1) % (self.nqubits)))
self.QML.add(gates.RZ((q + 1) % (self.nqubits), theta = 0))
self.QML.add(gates.CNOT(q, (q + 1) % (self.nqubits)))
def mapper_QML(self, parameters, data):
assert len(parameters) == 2 * self.nlayers
pqc_parameters = np.zeros(len(self.PQC.get_parameters()))
qml_parameters = np.zeros(len(self.QML.get_parameters()))
index_pqc = 0
index_qml = 0
for i, p in enumerate(parameters):
if i % 2 == 0:
qml_parameters[index_qml : index_qml + self.nqubits] = [data] * self.nqubits
index_qml += self.nqubits
pqc_parameters[index_pqc : index_pqc + self.nqubits] = [p] * self.nqubits
index_pqc += self.nqubits
qml_parameters[index_qml : index_qml + self.nqubits] = [p] * self.nqubits
index_qml += self.nqubits
self.PQC.set_parameters(pqc_parameters)
self.QML.set_parameters(qml_parameters)
return pqc_parameters, qml_parameters
def energy(self, parameters):
self.mapper_QML(parameters, 0)
return self.ham.expectation(self.PQC.execute().state())