def compute(n):
spins = [2 for i in range(n)]
sc = spinchain.Spin_Hamiltonian(spins) # create the chain
sc.clean()
sc = spinchain.Spin_Hamiltonian(spins) # create the chain
def fj(i, j):
if 0.9 < abs(i - j) < 1.1: return 1.0
return 0.0
sc.set_exchange(fj) # set exchange couplings
#sc.set_fields(lambda x: [0.2,0.2,0.2]) # set exchange couplings
sc.maxm = 10
sc.nsweeps = 2
sc.get_gs()
i = 0
j = 1
t0 = time.time()
sc.fit_td = True
# (x,y) = sc.evolution(nt=100,dt=0.03,name="ZZ",i=i,j=j)
(x2, y2) = sc.get_dynamical_correlator(es=es, use_kpm=False, dt=0.1)
t1 = time.time()
print("Time", t1 - t0)
return t1 - t0
import sys
import os
import numpy as np
sys.path.append(os.environ["DMRGROOT"]) # root for dmrg
import spinchain
n = 30
spins = [2 for i in range(n)] # spin 1/2 heisenberg chain
sc = spinchain.Spin_Hamiltonian(spins) # create the spin chain
# dimerized coupling
def fj(i,j):
if abs(i-j)==1:
ij = (i+j)%4
dj = -0.2
if ij==1: return 1.0 + dj
else: return 1.0 - dj
return 0.0
sc.set_exchange(fj) # set those exchange couplings
#sc.kpmmaxm = 10 # KPM max m
sc.kpmscale = 10.0
import time
import matplotlib.pyplot as plt
fo = open("DCF.OUT","w") # dynamical correlation function
for i in range(n): # loop over sites
(xs,ys) = sc.get_spismj(n=1000,mode="DMRG",i=i,j=0)