"""
import os
import numpy as np
import numpy.matlib as mat
from numpy.matlib import kron
from scipy.sparse import csr_matrix
import matplotlib.pyplot as plt
import datetime
from scipy.optimize import check_grad
from numpy.testing import (
assert_, assert_almost_equal, run_module_suite, assert_equal)
#QuTiP
from qutip import Qobj, identity, sigmax, sigmay, sigmaz, tensor
import qutip.logging_utils as logging
logger = logging.get_logger()
#QuTiP control modules
import qutip.control.pulseoptim as cpo
import qutip.control.pulsegen as pulsegen
from qutip.qip.algorithms import qft
example_name = 'QFT-dump'
log_level=logging.INFO
# ****************************************************************
# Define the physics of the problem
Sx = sigmax()
Sy = sigmay()
Sz = sigmaz()
Si = 0.5*identity(2)
# Drift Hamiltonian
# NumPy/SciPy
import numpy as np
import scipy.sparse as sp
# Conditionally import CVXPY
try:
import cvxpy
except ImportError:
cvxpy = None
Complex = namedtuple('Complex', ['re', 'im'])
from qutip.tensor import tensor_swap
from qutip.operators import qeye
from qutip.logging_utils import get_logger
logger = get_logger()
def complex_var(rows=1, cols=1, name=None):
return Complex(re=cvxpy.Variable((rows, cols),
name=(name + "_re") if name else None),
im=cvxpy.Variable((rows, cols),
name=(name + "_im") if name else None))
def herm(*Xs):
return sum([[X.re == X.re.T, X.im == -X.im.T] for X in Xs], [])
def pos_noherm(*Xs):
constraints = [cvxpy.bmat([[X.re, -X.im], [X.im, X.re]]) >> 0 for X in Xs]
#!/usr/bin/env python3
# -*- coding: utf-8 -*-
"""
Created on Thu Jan 31 13:14:40 2019
@author: fred
"""
import datetime
import matplotlib.pyplot as plt
import numpy as np
from qutip import cnot, sigmax, sigmay, identity, sigmaz, tensor
#from qutip.control import *
import qutip.logging_utils as logging
logger = logging.get_logger()
log_level = logging.INFO
import qutip.control.pulseoptim as cpo
import qutip.control.pulsegen as pulsegen
example_name = 'CNOT'
## MODEL
Sx = sigmax()
Sy = sigmay()
Sz = sigmaz()
Si = 0.5 * identity(2)
H_d = 0.5 * (tensor(Sx, Sx) + tensor(Sy, Sy) + tensor(Sz, Sz)
) # Drift Hamiltonian
H_c = [tensor(Sx, Si),
tensor(Sy, Si),
tensor(Si, Sx),
tensor(Si, Sy)] # The (four) control Hamiltonians
import numpy as np
# Conditionally import CVXPY
try:
import cvxpy
except:
cvxpy = None
Complex = namedtuple('Complex', ['re', 'im'])
from qutip.qip.gates import swap
from qutip.tensor import tensor_swap
from qutip.operators import qeye
from qutip.logging_utils import get_logger
logger = get_logger()
def complex_var(rows=1, cols=1, name=None):
return Complex(
re=cvxpy.Variable(rows, cols, name=(name + "_re") if name else None),
im=cvxpy.Variable(rows, cols, name=(name + "_im") if name else None)
)
def herm(*Xs):
return sum([
[X.re == X.re.T, X.im == -X.im.T]
for X in Xs
], [])
