'size': 26
})
## for Palatino and other serif fonts use:
#rc('font',**{'family':'serif','serif':['Palatino']})
rc('text', usetex=True)
# matplotlib.rcParams['figure.dpi'] = 400
import numpy as np
import scipy as sp
import math
from Calculations import plot_adjacency_graph
N = 12
pxp = unlocking_System([0], "periodic", 2, N)
pxp.gen_basis()
pxp_syms = model_sym_data(pxp, [translational(pxp)])
H = Hamiltonian(pxp, pxp_syms)
H.site_ops[1] = np.array([[0, 0], [1, 0]])
H.site_ops[2] = np.array([[0, 1], [0, 0]])
H.model = np.array([[0, 1, 2, 0], [0, 2, 1, 0]])
H.model_coef = np.array([1, 1])
k = [0]
H.gen(k)
# H.gen()
# H0=spin_Hamiltonian(pxp,"x",pxp_syms)
# H0.gen(k)
# # H = H_operations.add(H0,H,np.array([1,1/2]))
# H = H_operations.add(H0,H,np.array([1,1]))
from matplotlib import rc
rc('font', **{
'family': 'sans-serif',
'sans-serif': ['Computer Modern'],
'size': 26
})
## for Palatino and other serif fonts use:
#rc('font',**{'family':'serif','serif':['Palatino']})
rc('text', usetex=True)
# matplotlib.rcParams['figure.dpi'] = 400
N = 18
pxp = unlocking_System([0], "periodic", 2, N)
pxp.gen_basis()
pxp_syms = model_sym_data(pxp, [parity(pxp), translational(pxp)])
H = spin_Hamiltonian(pxp, "x", pxp_syms)
k = [0, 0]
H.gen(k)
H.sector.find_eig(k)
e = H.sector.eigvalues(k)
to_del = []
for n in range(0, np.size(e, axis=0)):
if np.abs(e[n]) < 1e-10:
to_del = np.append(to_del, n)
for n in range(np.size(to_del, axis=0) - 1, -1, -1):
e = np.delete(e, to_del[n])
#rectangular billiards
# n_max = 200
return psi / np.power(np.vdot(psi, psi), 0.5)
def exp(Q, psi):
return np.vdot(psi, np.dot(Q, psi))
def var(Q, psi):
Q2 = np.dot(Q, Q)
return exp(Q2, psi) - exp(Q, psi)**2
N = 12
pxp = unlocking_System([0], "periodic", 2, N)
pxp.gen_basis()
pxp_syms = model_sym_data(pxp, [translational_general(pxp, order=4), PT(pxp)])
H = Hamiltonian(pxp, pxp_syms)
H.site_ops[1] = np.array([[0, 1], [1, 0]])
H.model = np.array([[0, 1, 0], [0, 1, 1, 1, 0], [0, 1, 1, 1, 0]])
H.model_coef = np.array([1, -1, -1])
H.uc_size = np.array([1, 4, 4])
H.uc_pos = np.array([0, 3, 1])
H.gen()
H.sector.find_eig()
z = zm_state(4, 1, pxp)
eig_overlap(z, H).plot()
plt.show()
fidelity(z, H).plot(np.arange(0, 20, 0.01), z)
import matplotlib.pyplot as plt
from progressbar import ProgressBar
from scipy.sparse import linalg as sparse_linalg
from Hamiltonian_Classes import Hamiltonian, H_table, clock_Hamiltonian, spin_Hamiltonian
from System_Classes import unlocking_System
from Symmetry_Classes import translational, parity, model_sym_data, charge_conjugation
from Construction_functions import bin_to_int_base_m, int_to_bin_base_m, cycle_bits_state
from Search_functions import find_index_bisection
from State_Classes import zm_state, sym_state, prod_state
from rw_functions import save_obj, load_obj
pxp = unlocking_System([0], "periodic", 3, 8)
pxp.gen_basis()
pxp_syms = model_sym_data(pxp, [
translational(pxp),
parity(pxp),
])
# pxp_syms = model_sym_data(pxp,[translational(pxp)])
H1 = clock_Hamiltonian(pxp, pxp_syms)
H2 = spin_Hamiltonian(pxp, "x", pxp_syms)
e_clock, u_clock = np.linalg.eigh(H1.site_ops[1])
e_spin, u_spin = np.linalg.eigh(H2.site_ops[1])
spin2clock_u = np.dot(u_spin, np.conj(np.transpose(u_clock)))
clock2spin_u = np.dot(u_clock, np.conj(np.transpose(u_spin)))
root6 = np.power(6, 0.5)
root23 = np.power(2 / 3, 0.5)
clock2spin_u = np.array([[1 / root6, root23, -1 / root6],
[1 / root6 - 1j / 2, -1 / root6, -1 / root6 - 1j / 2],
[1 / root6 + 1j / 2, -1 / root6,
from matplotlib import rc
rc('font', **{
'family': 'sans-serif',
'sans-serif': ['Computer Modern'],
'size': 26
})
## for Palatino and other serif fonts use:
#rc('font',**{'family':'serif','serif':['Palatino']})
rc('text', usetex=True)
# matplotlib.rcParams['figure.dpi'] = 400
N = 8
base = 3
pxp = unlocking_System([0], "periodic", base, N)
pxp.gen_basis()
pxp_syms = model_sym_data(pxp, [translational(pxp)])
H = clock_Hamiltonian(pxp, pxp_syms)
# H = spin_Hamiltonian(pxp,"x",pxp_syms)
# H = clock_Hamiltonian(pxp,pxp_syms)
H.gen()
H.sector.find_eig()
z = zm_state(2, 1, pxp)
krylov_dim = 2 * pxp.N
def gen_krylov_basis(H, dim, init_state, system, orth=False):
krylov_basis = init_state.prod_basis()
current_state = krylov_basis
for n in range(0, dim):
'sans-serif': ['Computer Modern'],
'size': 26
})
## for Palatino and other serif fonts use:
#rc('font',**{'family':'serif','serif':['Palatino']})
rc('text', usetex=True)
# matplotlib.rcParams['figure.dpi'] = 400
N = 10
J = 1
hx = 1
hz = 1
#init system
system = unlocking_System([0, 1], "periodic", 2, N)
system.gen_basis()
system_syms = model_sym_data(system, [translational(system)])
#create Hamiltonian
H = Hamiltonian(system, system_syms)
H.site_ops[1] = np.array([[0, 1], [1, 0]])
H.site_ops[2] = np.array([[-1, 0], [0, 1]])
H.model = np.array([[1, 1], [2], [1]])
H.model_coef = np.array([J, hz, hx])
#dynamics following quench from |00000>
psi = ref_state(0, system)
k = system_syms.find_k_ref(psi.ref)
for n in range(0, np.size(k, axis=0)):
H.gen(k[n])
H.sector.find_eig(k[n])
print(H.sector.eigvalues(k[n]))
system = unlocking_System([0, 1], "periodic", 2, 4)
n = 2 #no singlets to add
sites = np.arange(0, system.N)
#combinatrocs, all possible site indexes to modify 2n spins, to insert n singlets
singlet_sites = np.array((list(itertools.combinations(sites, 2 * n))))
#of these sites, form all possible pairs (all possible singlet couplings)
no_pairs = int(np.size(singlet_sites, axis=1) / 2)
#For each pair, two ways to insert a singlet. either the first index has spin
#up, second down or vice versa. Label as 0,1; find all poss ways unique up to inversion
pair_basis_system = unlocking_System([0, 1], "periodic", 2, no_pairs)
if no_pairs > 1:
pair_sym = model_sym_data(pair_basis_system,
[inversion(pair_basis_system)])
unique_pair_refs = pair_sym.find_block_refs([0])
unique_pair_bits = np.zeros((np.size(unique_pair_refs), no_pairs),
dtype=int)
for n in range(0, np.size(unique_pair_refs, axis=0)):
unique_pair_bits[n] = pair_basis_system.basis[pair_basis_system.keys[
unique_pair_refs[n]]]
else:
unique_pair_bits = np.array([[0]])
# print(unique_pair_bits)
ref_pairs = np.zeros(2)
from combinatorics import all_pairs
for i in range(0, np.size(singlet_sites, axis=0)):
# print(" ")
for pair in all_pairs(list(singlet_sites[i])):
return Hp
class su2LW_data:
def __init__(self, raisingKey, lw, casimir_Eig, Hz_Eig):
self.raisingKey = raisingKey
self.lw = lw
self.casimir_Eig = casimir_Eig
self.Hz_Eig = Hz_Eig
#init system
N = 18
pxp = unlocking_System([0], "periodic", 2, N)
pxp.gen_basis()
pxp_syms = model_sym_data(pxp, [translational(pxp), parity(pxp)])
uc_size = 2
decompBasis = unlocking_System([0, 1], "periodic", 2, uc_size)
decompBasis.gen_basis()
decompSym = model_sym_data(decompBasis, [inversion(decompBasis)])
block_refs = decompSym.find_block_refs([0])
block_refs = np.delete(block_refs, 0, axis=0)
block_basis = np.zeros((np.size(block_refs), uc_size))
for n in range(0, np.size(block_refs, axis=0)):
block_basis[n] = decompBasis.basis[decompBasis.keys[block_refs[n]]]
from Diagnostics import print_wf
su2RootData = dict()
count = 0
pbar = ProgressBar()
