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import numpy as np
from qutip.qip.gates import globalphase
[docs]class CircuitProcessor(object):
"""
Base class for representation of the physical implementation of a quantum
program/algorithm on a specified qubit system.
"""
def __init__(self, N, correct_global_phase):
"""
Parameters
----------
N: Integer
The number of qubits in the system.
correct_global_phase: Boolean
Check if the global phases should be included in the final result.
"""
self.N = N
self.correct_global_phase = correct_global_phase
[docs] def optimize_circuit(self, qc):
"""
Function to take a quantum circuit/algorithm and convert it into the
optimal form/basis for the desired physical system.
Parameters
----------
qc: QubitCircuit
Takes the quantum circuit to be implemented.
Returns
--------
qc: QubitCircuit
The optimal circuit representation.
"""
raise NotImplementedError("Use the function in the sub-class")
[docs] def adjacent_gates(self, qc, setup):
"""
Function to take a quantum circuit/algorithm and convert it into the
optimal form/basis for the desired physical system.
Parameters
----------
qc: QubitCircuit
Takes the quantum circuit to be implemented.
setup: String
Takes the nature of the spin chain; linear or circular.
Returns
--------
qc: QubitCircuit
The resolved circuit representation.
"""
raise NotImplementedError("Use the function in the sub-class")
[docs] def load_circuit(self, qc):
"""
Translates an abstract quantum circuit to its corresponding Hamiltonian
for a specific model.
Parameters
----------
qc: QubitCircuit
Takes the quantum circuit to be implemented.
"""
raise NotImplementedError("Use the function in the sub-class")
[docs] def get_ops_and_u(self):
"""
Returns the Hamiltonian operators and corresponding values by stacking
them together.
"""
raise NotImplementedError("Use the function in the sub-class")
[docs] def get_ops_labels(self):
"""
Returns the Hamiltonian operators and corresponding labels by stacking
them together.
"""
pass
def eliminate_auxillary_modes(self, U):
return U
[docs] def run(self, qc=None):
"""
Generates the propagator matrix by running the Hamiltonian for the
appropriate time duration for the desired physical system.
Parameters
----------
qc: QubitCircuit
Takes the quantum circuit to be implemented.
Returns
--------
U_list: list
The propagator matrix obtained from the physical implementation.
"""
if qc:
self.load_circuit(qc)
U_list = []
H_ops, H_u = self.get_ops_and_u()
for n in range(len(self.T_list)):
H = sum([H_u[n, m] * H_ops[m] for m in range(len(H_ops))])
U = (-1j * H * self.T_list[n]).expm()
U = self.eliminate_auxillary_modes(U)
U_list.append(U)
if self.correct_global_phase and self.global_phase != 0:
U_list.append(globalphase(self.global_phase, N=self.N))
return U_list
[docs] def run_state(self, qc=None, states=None):
"""
Generates the propagator matrix by running the Hamiltonian for the
appropriate time duration for the desired physical system with the
given initial state of the qubit register.
Parameters
----------
qc: QubitCircuit
Takes the quantum circuit to be implemented.
states: Qobj
Initial state of the qubits in the register.
Returns
--------
U_list: list
The propagator matrix obtained from the physical implementation.
"""
if states is None:
raise NotImplementedError("Qubit state not defined.")
if qc:
self.load_circuit(qc)
U_list = [states]
H_ops, H_u = self.get_ops_and_u()
for n in range(len(self.T_list)):
H = sum([H_u[n, m] * H_ops[m] for m in range(len(H_ops))])
U = (-1j * H * self.T_list[n]).expm()
U = self.eliminate_auxillary_modes(U)
U_list.append(U)
if self.correct_global_phase and self.global_phase != 0:
U_list.append(globalphase(self.global_phase, N=self.N))
return U_list
[docs] def pulse_matrix(self):
"""
Generates the pulse matrix for the desired physical system.
Returns
--------
t, u, labels:
Returns the total time and label for every operation.
"""
dt = 0.01
H_ops, H_u = self.get_ops_and_u()
t_tot = sum(self.T_list)
n_t = int(np.ceil(t_tot / dt))
n_ops = len(H_ops)
t = np.linspace(0, t_tot, n_t)
u = np.zeros((n_ops, n_t))
t_start = 0
for n in range(len(self.T_list)):
t_idx_len = int(np.floor(self.T_list[n] / dt))
mm = 0
for m in range(len(H_ops)):
u[mm, t_start:(t_start + t_idx_len)] = (np.ones(t_idx_len) *
H_u[n, m])
mm += 1
t_start += t_idx_len
return t, u, self.get_ops_labels()
[docs] def plot_pulses(self):
"""
Maps the physical interaction between the circuit components for the
desired physical system.
Returns
--------
fig, ax: Figure
Maps the physical interaction between the circuit components.
"""
import matplotlib.pyplot as plt
t, u, u_labels = self.pulse_matrix()
fig, ax = plt.subplots(1, 1, figsize=(12, 6))
for n, uu in enumerate(u):
ax.plot(t, u[n], label=u_labels[n])
ax.axis('tight')
ax.set_ylim(-1.5 * 2 * np.pi, 1.5 * 2 * np.pi)
ax.legend(loc='center left',
bbox_to_anchor=(1, 0.5), ncol=(1 + len(u) // 16))
fig.tight_layout()
return fig, ax