My codes:
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import numpy as np
import tenpy
import time
from tenpy.networks.mps import MPS
from tenpy.models.xxz_chain import XXZChain
from tenpy.algorithms import dmrg
import matplotlib.pyplot as plt
def example_DMRG_heisenberg_infinite_S_xi_scaling(Jz):
model_params = dict(L=20, Jxx=1., Jz=Jz, hz=0, bc_MPS='infinite', conserve='best')
M = XXZChain(model_params)
product_state = ["up"] * M.lat.N_sites
psi = MPS.from_product_state(M.lat.mps_sites(), product_state, bc=M.lat.bc_MPS)
dmrg_params = {
'start_env': 10,
'mixer': False,
# 'mixer_params': {'amplitude': 1.e-3, 'decay': 5., 'disable_after': 50},
'trunc_params': {
'chi_max': 30,
#Dimension of the system
'svd_min': 1.e-10
},
'max_E_err': 1.e-9,
'max_S_err': 1.e-6,
'update_env': 0,
}
chi_list = np.arange(7, 31, 2)
s_list = []
xi_list = []
E_list=[]
eng = dmrg.TwoSiteDMRGEngine(psi, M, dmrg_params)
a=0
for chi in chi_list:
t0 = time.time()
eng.reset_stats(
) # necessary if you for example have a fixed numer of sweeps, if you don't set this you option your simulation stops after initial number of sweeps!
eng.trunc_params['chi_max'] = chi
## DMRG Calculation ##
print("Start IDMRG CALCULATION")
result=eng.run()
eng.options['mixer'] = None
psi.canonical_form()
## Calculating bond entropy and correlation length ##
a+=1
if a==len(chi_list):
print("cnm")
s_list=psi.entanglement_entropy()
# the bond 0 is between MPS unit cells and hence sensible even for 2D lattices.
#xi_list.append(psi.correlation_length())
#print(result)
E_list.append(result[0])
print(chi,
time.time() - t0,
#np.mean(psi.expectation_value(M.H_bond)),
#s_list[-1],
#xi_list[-1],
flush=True)
tenpy.tools.optimization.optimize(3) # quite some speedup for small chi
print("SETTING NEW BOND DIMENSION")
return s_list, xi_list, E_list
if __name__ == "__main__":
import logging
logging.basicConfig(level=logging.INFO)
s_list, xi_list,E_list = example_DMRG_heisenberg_infinite_S_xi_scaling(Jz=1)
length=[i for i in range(0,len(E_list))]
plt.plot(length,E_list)
plt.show()
