Dear ALPS,
I'm having some troubling getting a sensible result using DMRG with ALPS 2.3.0 on a simple transverse Ising model (i.e. using the "spin" model with Jz != 0, Gamma != 0). Other methods seem to get the correct result with the same parameters. It seems to be the Gamma term which causes the trouble. I've pasted a script below which demonstrates the problem. The script gives me the following output, with the second number being the ground state energy found by each method:
Model fulldiag: {10.0: -5.3178022046739857} Model sparsediag: {10.0: -5.3178022046739937} Model mps_optim: {10.0: -5.3178022046739919} Model dmrg: {10.0: -213.49032836522568}
Adjusting the various DMRG parameters produces similar results of E0 ~= -210. I assume I am doing something wrong, or perhaps the Gamma term isn't supported by DMRG? I have searched the mailing list archive without success. Ultimately, I want to use DMRG on a more complex model which includes a term similar to the Gamma / Sx term in the spin model.
Thank you for your great work, Alex Henry
The script:
########################## import pyalps import numpy as np import matplotlib.pyplot as plt import copy import math
models = ['fulldiag', 'sparsediag', 'mps_optim', 'dmrg'] parms = [{ 'LATTICE' : "chain lattice", 'MODEL' : "spin", 'local_S' : 0.5, 'Jxy' : 0, 'Jz' : 1, 'Gamma' : 1, 'h' : 0, 'NUMBER_EIGENVALUES' : 1, 'L' : 10, }]
def process(prefix, prog): input_file = pyalps.writeInputFiles(prefix, parms) res = pyalps.runApplication(prog, input_file) data = pyalps.loadEigenstateMeasurements(pyalps.getResultFiles(prefix=prefix)) return data
def get_results(d): E0 = {} for Lsets in d: L = pyalps.flatten(Lsets)[0].props['L'] allE = [] for q in pyalps.flatten(Lsets): allE += list(q.y) allE = np.sort(allE) E0[L] = allE[0] return E0
results = {} for model in models: name = "ising_" + model data = process(name, model) results[model] = (get_results(data))
for model in models: print "Model " + model + ": " + str(results[model]) #############################