def new_spin(name, base_ks, uploaded):
"""
Return new spin
"""
spin = Spin(name=name, baseks=base_ks, uploaded=uploaded)
spin.save()
return spin
def new_spin(name, base_ks):
"""
Return new spin
"""
spin = Spin(name=name, baseks=base_ks)
spin.save()
return spin
def new_spin(name, base_ks):
"""
Return new spin
"""
spin = Spin(name=name, baseks=base_ks)
spin.save()
return spin
from core import Contractor as ct
from core import MPO
from core import MPS
from models import Boson as Bs
from models import Spin as Sp
L = 10
D = 20
Jx = 1.
Jy = 1.
Jz = 1.
g = -1.05
h = 0.5
offset = 0
Nmax = 4
IsingModel = Sp.Ising(L, Jz, g, h, offset)
HeisenbergModel = Sp.Heisenberg(L, Jx, Jy, Jz, g, h, offset)
BoseHubbardModel = Bs.BoseHubbard(L,
Nmax,
t=1.,
U=0.1,
mu=1.,
V=0.5,
Vint=0.2,
offset=0)
# Test of DMRG & fitApplyMPO & entanglement entropy & total spin projector
#H = IsingModel.hamil
H = HeisenbergModel.hamil
gs = MPS.MPS(L, D, 2)
# gs.setProductState(Sp.Up)
def __init__(s, H_PARAMS):
#======================================================================
# Initiate the Hamiltonian features
#======================================================================
Hamiltonian.__init__(s)
#======================================================================
# Define the lattice
# for key in lattice.keys: printa(key)
#======================================================================
from lattices import Chain
lattice = Chain()
keys = lattice.keys
s.LATTICE_UNIT_CELL_SIZE = lattice.LATTICE_UNIT_CELL_SIZE
#======================================================================
# Define the model
# for key in model.opts: printa(key)
#======================================================================
from models import Spin
model = Spin(1)
s.d = model.d
s.model_operators = model.opts
#======================================================================
# Initiate the Hamiltonian features
#======================================================================
Hamiltonian.__init__(s, model, lattice, H_PARAMS)
#======================================================================
# Define the Hamiltonian and its operators
#======================================================================
g = H_PARAMS['g']
# Spin-Spin
s.make_two_sites_operators(keys['nearest_n'], 1,
s.model_operators['Sx'],
s.model_operators['Sx'])
s.make_two_sites_operators(keys['nearest_n'], 1,
s.model_operators['Sy'],
s.model_operators['Sy'])
s.make_two_sites_operators(keys['nearest_n'], 1,
s.model_operators['Sz'],
s.model_operators['Sz'])
# Spin-squared
s.make_two_sites_operators(
keys['nearest_n'], g,
dot(s.model_operators['Sx'], s.model_operators['Sx']),
dot(s.model_operators['Sx'], s.model_operators['Sx']))
s.make_two_sites_operators(
keys['nearest_n'], g,
dot(s.model_operators['Sy'], s.model_operators['Sy']),
dot(s.model_operators['Sy'], s.model_operators['Sy']))
s.make_two_sites_operators(
keys['nearest_n'], g,
dot(s.model_operators['Sz'], s.model_operators['Sz']),
dot(s.model_operators['Sz'], s.model_operators['Sz']))
s.make_two_sites_operators(
keys['nearest_n'], g,
dot(s.model_operators['Sx'], s.model_operators['Sy']),
dot(s.model_operators['Sx'], s.model_operators['Sy']))
s.make_two_sites_operators(
keys['nearest_n'], g,
dot(s.model_operators['Sy'], s.model_operators['Sx']),
dot(s.model_operators['Sy'], s.model_operators['Sx']))
s.make_two_sites_operators(
keys['nearest_n'], g,
dot(s.model_operators['Sx'], s.model_operators['Sz']),
dot(s.model_operators['Sx'], s.model_operators['Sz']))
s.make_two_sites_operators(
keys['nearest_n'], g,
dot(s.model_operators['Sz'], s.model_operators['Sx']),
dot(s.model_operators['Sz'], s.model_operators['Sx']))
s.make_two_sites_operators(
keys['nearest_n'], g,
dot(s.model_operators['Sz'], s.model_operators['Sy']),
dot(s.model_operators['Sz'], s.model_operators['Sy']))
s.make_two_sites_operators(
keys['nearest_n'], g,
dot(s.model_operators['Sy'], s.model_operators['Sz']),
dot(s.model_operators['Sy'], s.model_operators['Sz']))