parms.append({
'LATTICE': "chain lattice",
'MODEL': "spin",
'local_S': 0.5,
'J': 1,
'L': l,
'CONSERVED_QUANTUMNUMBERS': 'Sz',
'Sz_total': sz
})
#write the input file and run the simulation
input_file = pyalps.writeInputFiles('parm2b', parms)
res = pyalps.runApplication('sparsediag', input_file)
#load all measurements for all states
data = pyalps.loadSpectra(pyalps.getResultFiles(prefix='parm2b'))
lengths = []
min_energies = {}
# extract the ground state energies over all momenta for every simulation
for sim in data:
l = int(sim[0].props['L'])
if l not in lengths: lengths.append(l)
sz = int(sim[0].props['Sz_total'])
all_energies = []
for sec in sim:
all_energies += list(sec.y)
min_energies[(l, sz)] = np.min(all_energies)
# make a plot of the triplet gap as function of system size
# THE SOFTWARE IS PROVIDED "AS IS", WITHOUT WARRANTY OF ANY KIND, EXPRESS OR
# IMPLIED, INCLUDING BUT NOT LIMITED TO THE WARRANTIES OF MERCHANTABILITY,
# FITNESS FOR A PARTICULAR PURPOSE, TITLE AND NON-INFRINGEMENT. IN NO EVENT
# SHALL THE COPYRIGHT HOLDERS OR ANYONE DISTRIBUTING THE SOFTWARE BE LIABLE
# FOR ANY DAMAGES OR OTHER LIABILITY, WHETHER IN CONTRACT, TORT OR OTHERWISE,
# ARISING FROM, OUT OF OR IN CONNECTION WITH THE SOFTWARE OR THE USE OR OTHER
# DEALINGS IN THE SOFTWARE.
#
# ****************************************************************************
import pyalps
import numpy as np
import matplotlib.pyplot as plt
import pyalps.plot
data = pyalps.loadSpectra(pyalps.getResultFiles(prefix='ed02a'))
data += pyalps.loadSpectra(pyalps.getResultFiles(prefix='ed02b'))
lengths = []
min_energies = {}
# extract the ground state energies over all momenta for every simulation
for sim in data:
l = int(sim[0].props['L'])
if l not in lengths: lengths.append(l)
sz = int(sim[0].props['Sz_total'])
s = float(sim[0].props['local_S'])
all_energies = []
for sec in sim:
all_energies += list(sec.y)
min_energies[(l, s, sz)] = np.min(all_energies)
'LATTICE': "ladder",
'MODEL': "spin",
'local_S': 0.5,
'J0': 0,
'J1': 1,
'L': l,
'CONSERVED_QUANTUMNUMBERS': 'Sz',
'Sz_total': 0
})
#write the input file and run the simulation
input_file = pyalps.writeInputFiles('ed03c', parms)
res = pyalps.runApplication('sparsediag', input_file)
#load all measurements for all states
data = pyalps.loadSpectra(pyalps.getResultFiles(prefix='ed03c'))
# collect spectra over all momenta for every simulation
spectra = {}
for sim in data:
l = int(sim[0].props['L'])
all_energies = []
spectrum = pyalps.DataSet()
for sec in sim:
all_energies += list(sec.y)
spectrum.x = np.concatenate(
(spectrum.x,
np.array([sec.props['TOTAL_MOMENTUM']
for i in range(len(sec.y))])))
spectrum.y = np.concatenate((spectrum.y, sec.y))
spectrum.y -= np.min(all_energies)