def integrate(self, type='NLS'):
r = ode(getattr(self, '_func_' + type))
opt = Odeoptions()
opt.atol = 1e-12
opt.rtol = 1e-10
opt.max_step = self.dz
r.set_integrator('zvode',
method=opt.method,
order=opt.order,
atol=opt.atol,
rtol=opt.rtol,
nsteps=opt.nsteps,
first_step=opt.first_step,
min_step=opt.min_step,
max_step=opt.max_step)
r.set_initial_value(self.a0, 0)
self.Y = [r.y]
for i in trange(1, len(self.z)):
self.Y.append(r.integrate(self.z[i]))
self.Y = np.array(self.Y)
def integrate(self):
r = ode(self.__func_LS_cyc)
opt = Odeoptions()
opt.atol = 1e-10
opt.rtol = 1e-8
opt.max_step = .005
r.set_integrator('zvode',
method=opt.method,
order=opt.order,
atol=opt.atol,
rtol=opt.rtol,
nsteps=opt.nsteps,
first_step=opt.first_step,
min_step=opt.min_step,
max_step=opt.max_step)
r.set_initial_value(self.a0, 0)
self.Y = [r.y]
for i in trange(1, len(self.z)):
self.Y.append(r.integrate(self.z[i]))
self.Y = np.array(self.Y)
def __init__(self, number_spins, alpha, B_field, opts=Odeoptions()):
self.opts = opts
calc = ising_calculator_FM(number_spins, alpha)
H0, Ht = calc.get_H()
#time dependent hamiltonian with exponential ramping of Ht
# self.H = [H0, [Ht, 'Bstop + (Bstart - Bstop) * exp(-t / ramp_time)']]
self.H = H0 + Ht * B_field
from qutip import mesolve, Qobj, tensor, qsave, qload, Odeoptions, qeye, sigmax, sigmay, sigmaz, expect, ket2dm, basis
from integrator import time_dependent_simulator
import numpy as np
from matplotlib import pyplot
number_spins = 2
alpha = 1.
Bstart = 50.0 #units of J0
Bstop = 0.01 #units of J0
ramp_time = 1. #units of 1/J0
t_list = np.linspace(0, 12 * ramp_time, 2000)
#set up integrator options
opts = Odeoptions()
opts.nsteps = 10000000
def all_spins_up_y():
up_y = Qobj([[1], [1.j]]).unit()
state = tensor([up_y] * number_spins)
return state
def plot_magnetization(states, b_fields):
from scripts.theory.time_independent.state_quantifier import state_quantifier
quant = state_quantifier(number_spins)
ms = [quant.absolute_magnetization_x(state) for state in states]
pyplot.xscale('log')
pyplot.plot(b_fields, ms)
pyplot.ylim([-0.05, 1.05])
pyplot.xlim([0.05, 50.05])
from qutip import mesolve, Qobj, tensor, qsave, qload, Odeoptions, qeye, sigmax, sigmay, sigmaz, expect, ket2dm, basis
from integrator import time_dependent_simulator
import numpy as np
from matplotlib import pyplot
number_spins = 2
alpha = 1.
Bstart = 50.0 #units of J0
Bstop = 0.01 #units of J0
ramp_time = 1. #units of 1/J0
t_list = np.linspace(0, 12 * ramp_time , 2000)
#set up integrator options
opts = Odeoptions()
opts.nsteps = 10000000
def all_spins_up_y():
up_y = Qobj([[1],[1.j]]).unit()
state = tensor([up_y] * number_spins)
return state
def plot_magnetization(states, b_fields):
from scripts.theory.time_independent.state_quantifier import state_quantifier
quant = state_quantifier(number_spins)
ms = [quant.absolute_magnetization_x(state) for state in states]
pyplot.xscale('log')
pyplot.plot(b_fields, ms)
pyplot.ylim([-0.05,1.05])
pyplot.xlim([0.05, 50.05])
pyplot.xlabel('B/J0')
pyplot.ylabel('Magnetization')