parmsi['t'+str(i)+'[Time]'] = ','.join([mathematica(J[i]) for J in Jt])
# parmsi['t'+str(i)+'[Time]'] = ','.join([mathematica(JW(W)[i]) for W in ramp(W_i, W_f, xi, tau, dt)])
for i in range(L):
parmsi['U'+str(i)+'[Time]'] = ','.join([mathematica(U[i]) for U in Ut])
# parmsi['U'+str(i)+'[Time]'] = ','.join([mathematica(UW(W)[i]) for W in ramp(W_i, W_f, xi, tau, dt)])
parmslist.append(parmsi)
input_file = pyalps.writeInputFiles(basename+'.dynamic',parmslist)
res = pyalps.runApplication('mps_evolve',input_file,writexml=True)
end = datetime.datetime.now()
## simulation results
# data = pyalps.loadIterationMeasurements(pyalps.getResultFiles(prefix=basename+'.dynamic'), what=['Overlap', 'Local density', 'Local density squared', 'One body density matrix', 'Density density'])
data = pyalps.loadIterationMeasurements(pyalps.getResultFiles(prefix=basename+'.dynamic'), what=['Overlap', 'Energy'])
coords = []
for d1 in data:
for s1 in d1:
for d in s1:
for s in d:
if(s.props['observable'] == 'One body density matrix'):
coords = (s.x[:,0], s.x[:,1])
XY = pyalps.collectXY(data, x='Time', y='Overlap', foreach=['tau'])
p = [[[(x + 1)*dt, 1-abs(y**2)] for (x, y) in zip(xy.x, xy.y)] for xy in XY]
XY = pyalps.collectXY(data, x='Time', y='Energy', foreach=['tau'])
E = [[[(x + 1)*dt, y] for (x, y) in zip(xy.x, xy.y)] for xy in XY]
p['TIMESTEPS'] = nsteps
p['tau'] = tau # not used in the simulation, but useful in the evaluation below
p['Jz'] = z
p['ALWAYS_MEASURE'] = 'Local Magnetization'
p['chkp_each'] = nsteps
p['measure_each'] = 5
p['COMPLEX'] = 1
parms.append(p)
## write input files and run application
input_file = pyalps.writeInputFiles(basename, parms)
res = pyalps.runApplication('mps_evolve', input_file)
## simulation results
data = pyalps.loadIterationMeasurements(pyalps.getResultFiles(prefix=basename),
what=['Local Magnetization'])
for q in pyalps.flatten(data):
L = q.props['L']
#Compute the integrated flow of magnetization through the center \Delta M=\sum_{n>L/2}^{L} (<S_n^z(t)>+1/2)
#\Delta M= L/4
loc = 0.5 * (L / 2)
#\Delta M-=<S_n^z(t)> from n=L/2 to L
q.y = np.array([0.5 * (L / 2) - sum(q.y[0][L / 2:L])])
#Plot the Error in the magnetization one site to the right of the chain center
Mag = pyalps.collectXY(data, x='Time', y='Local Magnetization', foreach=['Jz'])
for d in Mag:
d.x = (d.x + 1) * d.props['DT']
plt.figure()
# parmsi['TIMESTEPS'] = int(2*tau / dt)
# for i in range(L-1):
# parmsi['t'+str(i)+'[Time]'] = ','.join([mathematica(JW(W)[i]) for W in quench(W_i, W_f, xi, 2*tau, dt)])
# for i in range(L):
# parmsi['U'+str(i)+'[Time]'] = ','.join([mathematica(UW(W)[i]) for W in quench(W_i, W_f, xi, 2*tau, dt)])
# parmslist.append(parmsi)
input_file = pyalps.writeInputFiles(basename + ".dynamic", parmslist)
res = pyalps.runApplication("mps_evolve", input_file, writexml=True)
end = datetime.datetime.now()
## simulation results
data = pyalps.loadIterationMeasurements(
pyalps.getResultFiles(prefix=basename + ".dynamic"),
what=["Energy", "Local density", "Local density squared", "One body density matrix", "Density density"],
)
coords = []
for d1 in data:
for s1 in d1:
for d in s1:
for s in d:
if s.props["observable"] == "One body density matrix":
coords = (s.x[:, 0], s.x[:, 1])
XY = pyalps.collectXY(data, x="Time", y="Energy", foreach=["tau"])
E = [[[(x + 1) * dt, y] for (x, y) in zip(xy.x, xy.y)] for xy in XY][0]
# XY = pyalps.collectXY(data, x='Time', y='Overlap', foreach=['tau'])
# p = [[[(x + 1)*dt, 1-abs(y**2)] for (x, y) in zip(xy.x, xy.y)] for xy in XY]
parms['t'+str(i)+'[Time]'] = ','.join([mathematica(JW(W)[i]) for W in quench(W_i, W_f, xi, tf, dt)])
for i in range(L):
parms['U'+str(i)+'[Time]'] = ','.join([mathematica(UW(W)[i]) for W in quench(W_i, W_f, xi, tf, dt)])
parmslist = [parms]
# print mathematica([JW(W)[0] for W in quench(W_i, W_f, xi, tf, dt)])
# print mathematica([UW(W)[0] for W in quench(W_i, W_f, xi, tf, dt)])
# quit()
input_file = pyalps.writeInputFiles(basename+'.dynamic',parmslist)
res = pyalps.runApplication('mps_evolve',input_file,writexml=True)
end = datetime.datetime.now()
## simulation results
data = pyalps.loadIterationMeasurements(pyalps.getResultFiles(prefix=basename+'.dynamic'), what=['Energy', 'Local density', 'Local density squared', 'One body density matrix', 'Density density'])
coords = []
for d1 in data:
for s1 in d1:
for d in s1:
for s in d:
if(s.props['observable'] == 'One body density matrix'):
coords = (s.x[:,0], s.x[:,1])
XY = pyalps.collectXY(data, x='Time', y='Energy', foreach=['tau'])
E = [[[(x + 1)*dt, y] for (x, y) in zip(xy.x, xy.y)] for xy in XY][0]
XY = pyalps.collectXY(data, x='Time', y='Local density', foreach=['tau'])
n = [[[(x + 1)*dt, y] for (x, y) in zip(xy.x, xy.y)] for xy in XY][0]
#write the input file and run the simulation
input_file = pyalps.writeInputFiles('parm_spin_one', parms)
res = pyalps.runApplication('mps_optim', input_file, writexml=True)
#load all measurements for all states
data = pyalps.loadEigenstateMeasurements(
pyalps.getResultFiles(prefix='parm_spin_one'))
# print properties of the eigenvector:
for s in data[0]:
print(s.props['observable'], ' : ', s.y[0])
# load and plot iteration history
iterations = pyalps.loadIterationMeasurements(
pyalps.getResultFiles(prefix='parm_spin_one'),
what=['Energy', 'TruncatedWeight'])
energy_iteration = pyalps.collectXY(pyalps.flatten(iterations), 'iteration',
'Energy')
for d in energy_iteration:
d.x = range(0, len(d.y))
truncation_iteration = pyalps.collectXY(pyalps.flatten(iterations),
'iteration', 'TruncatedWeight')
for d in truncation_iteration:
d.x = range(0, len(d.y))
plt.figure()
pyalps.plot.plot(energy_iteration)
plt.title('Iteration history of ground state energy (S=1)')
plt.ylabel('$E_0$')
plt.xlabel('iteration')
pass
basename = 'SingleSite/ss.'
parms['N_total'] = 14
# parms['initial_local_N'] = '3,2,2,2,2,2,2,2,2,2'#'1,1,1,1,1,1,1,1,0,0'#'2,2,1,1,1,1,1,1,1,1'
input_file = pyalps.writeInputFiles(basename + str(resi), [parms])
pyalps.runApplication('mps_optim', input_file, writexml=True)
#load all measurements for all states
data = pyalps.loadEigenstateMeasurements(pyalps.getResultFiles(prefix=basename))
for d in data:
for s in d:
if(s.props['observable'] == 'Energy'):
print s.y[0]
if(s.props['observable'] == 'Local density'):
print s.y[0]
iters = pyalps.loadIterationMeasurements(pyalps.getResultFiles(prefix=basename), what=['Energy'])
# print iters
en_vs_iter = pyalps.collectXY(iters, x='iteration', y='Energy')
# print en_vs_iter
Es = np.array([Ei for (i, Ei) in sorted(zip([int(xi) for xi in en_vs_iter[0].x[0:-1:20]], en_vs_iter[0].y[0:-1:20]))[-40:-1]])
Es2 = Es[1:-1] - Es[0:-2]
print Es2
plt.figure()
# pyalps.plot.plot(en_vs_iter)
plt.plot(Es)
# plt.yscale('log')
plt.show()
p['MEASURE_OVERLAP[Overlap]'] = initstate
p['ALWAYS_MEASURE'] = 'Overlap'
p['chkp_each'] = ns
p['measure_each'] = 10
p['update_each'] = 1
p['COMPLEX'] = 1
parms.append(p)
## write input files and run application
input_file = pyalps.writeInputFiles(basename + '.dynamic', parms)
res = pyalps.runApplication('mps_evolve', input_file)
## simulation results
data = pyalps.loadIterationMeasurements(pyalps.getResultFiles(prefix=basename +
'.dynamic'),
what=['Overlap'])
LE = pyalps.collectXY(data, x='Time', y='Overlap', foreach=['tau'])
for d in pyalps.flatten(LE):
d.x = (d.x + 1.) * d.props['dt'] # convert time index to real time
d.y = abs(
d.y)**2 # Loschmidt Echo defined as the module squared of the overlap
d.props['label'] = r'$\tau={0}$'.format(d.props['tau'])
plt.figure()
pyalps.plot.plot(LE)
plt.xlabel('Time $t$')
plt.ylabel('Loschmidt Echo $|< \psi(0)|\psi(t) > |^2$')
plt.title('Loschmidt Echo vs. Time')
plt.legend(loc='lower right')