def test_energy_calc_heis(self):
from cyclopeps.tools.peps_tools import PEPS
from cyclopeps.ops.heis import return_op
from cyclopeps.algs.tebd import run_tebd
mpiprint(
0, '\n' + '=' * 50 + '\nPeps Full Update Heisenberg test\n' +
'-' * 50)
# Create PEPS
Nx = 4
Ny = 4
d = 2
D = 3
Zn = None
backend = 'numpy'
chi = 50
# Get mpo
ham = return_op(Nx, Ny, sym=None, backend=backend)
# Run TEBD
Ef, _ = run_tebd(Nx,
Ny,
d,
ham,
D=D,
Zn=Zn,
chi=chi,
backend=backend,
n_step=100,
su_step_size=0.1,
su_conv_tol=1e-5,
su_n_step=1)
print('Final E = {}'.format(Ef))
mpiprint(0, 'Passed\n' + '=' * 50)
def test_energy_calc_heis_Z2_not_reduced(self):
from cyclopeps.tools.peps_tools import PEPS
from cyclopeps.ops.heis import return_op
from cyclopeps.algs.tebd import run_tebd
mpiprint(
0, '\n' + '=' * 50 +
'\nPeps Full Update Z2 (not reduced) Heisenberg test\n' + '-' * 50)
# Create PEPS
Nx = 4
Ny = 4
d = 2
D = 2
Zn = 2
backend = 'numpy'
chi = 50
# Get mpo
ham = return_op(Nx, Ny, sym='Z2', backend=backend)
# Run TEBD
Ef, _ = run_tebd(Nx,
Ny,
d,
ham,
D=D,
Zn=Zn,
chi=chi,
backend=backend,
n_step=1,
su_step_size=[0.5, 0.1],
su_conv_tol=1e-5,
reduced=False,
su_n_step=1)
print('Final E = {}'.format(Ef))
mpiprint(0, 'Passed\n' + '=' * 50)
# Bias sweeps
sVec = linspace(-0.5, 0.5, 30)
# TEBD Parameters
step_sizes = [0.1, 0.05, 0.01]
n_step = [50, 50, 50]
chi = [10, 20, 50]
# ---------------------------------------------------------
E = []
peps = None
for i, s in enumerate(sVec):
# Create the Suzuki trotter decomposed operator
params = (c, s)
ops = return_op(Nx, Ny, params, hermitian=False)
# Run TEBD
Ef, peps = run_tebd(Nx,
Ny,
d,
ops,
peps=peps,
D=D,
chi=chi,
n_step=n_step,
step_size=step_sizes)
E.append(Ef)
for s2 in range(len(E)):
print('{}\t{}'.format(sVec[s2], E[s2]))
dens_ops_bot = return_dens_op(Nx, Ny, top=False)
# Run TEBD
peps = PEPS(Nx, Ny, d, D[0], chi[0], fname=fnamer, fdir=savedir)
pepsl = PEPS(Nx, Ny, d, D[0], chi[0], fname=fnamel, fdir=savedir)
# Loop over all optimizaton parameters
for ind in range(len(D)):
# --------------------------------------------------------------------
# Calculate right eigenstate
Ef, peps = run_tebd(Nx,
Ny,
d,
ops,
peps=peps,
D=D[ind],
chi=chi[ind],
n_step=n_step[ind],
step_size=dt[ind],
conv_tol=conv[ind])
# --------------------------------------------------------------------
# Calculate left eigenstate
Efl, pepsl = run_tebd(Nx,
Ny,
d,
ops,
peps=pepsl,
D=D[ind],
chi=chi[ind],
n_step=n_step[ind],
norm_bs_upper=3.,
norm_bs_lower=0.)
# Loop over all optimizaton parameters
for ind in range(len(D)):
# Update PEPS Parameters
pepsl.D = D[ind]
pepsl.chi = chi[ind]
pepsl.fname = prepend + "Nx{}_Ny{}_sx{}_sy{}_D{}_chi{}_run_left".format(
Nx, Ny, sxind, syind, D[ind], chi[ind])
# --------------------------------------------------------------------
# Calculate left eigenstate
for i in range(5):
try:
Efl, pepsl = run_tebd(Nx,
Ny,
d,
opsl,
peps=pepsl,
D=D[ind],
chi=chi[ind],
n_step=n_step[ind],
step_size=dt[ind],
conv_tol=conv[ind])
break
except Exception as e:
print('Failed Left TEBD:\n{}'.format(e))
print('Restarting ({}/{} restarts)'.format(i, 5))
pepsl.load_tensors(pepsl.fdir + pepsl.fname)
curr_ops = return_curr_op(Nx,Ny,params)
dens_ops_top = return_dens_op(Nx,Ny,top=True)
dens_ops_bot = return_dens_op(Nx,Ny,top=False)
# Run TEBD
peps = PEPS(Nx,Ny,d,D[0],chi[0])
pepsl = PEPS(Nx,Ny,d,D[0],chi[0])
for ind in range(len(D)):
print('Right Vector' + '-'*50)
# Calculate right state
try:
Ef,peps = run_tebd(Nx,
Ny,
d,
ops,
peps=peps,
D=D[ind],
chi=chi[ind],
n_step=ns[ind],
step_size=dt[ind])
except Exception as e:
print('Error in using previous peps, starting with random')
print(e)
try:
peps = PEPS(Nx,Ny,d,D[ind],chi[ind])
Ef,peps = run_tebd(Nx,
Ny,
d,
ops,
peps=peps,
D=D[ind],
jr = 0.9
jl = 0.1
ju = 0.5
jd = 0.5
cr = 0.5
cl = 0.5
cu = 0.5
cd = 0.5
dr = 0.5
dl = 0.5
du = 0.5
dd = 0.5
sx = -0.5
sy = 0.
params = (jr, jl, ju, jd, cr, cl, cu, cd, dr, dl, du, dd, sx, sy)
# Create the Suzuki trotter decomposed operator
ops = return_op(peps.Nx, peps.Ny, params)
# Run TEBD
Ef, _ = run_tebd(peps.Nx,
peps.Ny,
peps.d,
ops,
peps=peps,
D=D[start:],
chi=chi[start:],
n_step=n_step[start:],
conv_tol=1e-8,
step_size=step_sizes[start:])
ju = 0.5
jd = 0.5
cr = 0.5
cl = 0.5
cu = 0.5
cd = 0.5
dr = 0.5
dl = 0.5
du = 0.5
dd = 0.5
sx = -0.2
sy = 0.
params = (jr, jl, ju, jd, cr, cl, cu, cd, dr, dl, du, dd, sx, sy)
# Create the Suzuki trotter decomposed operator
ops = return_op(Nx, Ny, params)
# Run TEBD
Ef, _ = run_tebd(Nx,
Ny,
d,
ops,
D=D,
su_step_size=[0.5, 0.1, 0.05],
su_n_step=[50, 50, 50],
su_conv_tol=1e-5,
su_chi=20,
chi=chi,
n_step=n_step,
step_size=step_sizes)
