def TransverseIsing(nspin, R, J, h):
H = []
for i in range(nspin):
j = (i + 1) % nspin
active = [
k for k in range(nspin)
if dpbc(i, k, nspin) < R or dpbc(j, k, nspin) < R
]
active = np.asarray(active)
print(active)
nact = len(active)
h_alpha = np.zeros(4**nact)
ii = np.where(active == i)[0][0]
jj = np.where(active == j)[0][0]
idx = [0] * nact
idx[ii] = 1
h_alpha[Bas2Int(idx, 4)] = h
idx = [0] * nact
idx[ii] = 3
idx[jj] = 3
if np.abs(i - j) == 1 and j != 0:
h_alpha[Bas2Int(idx, 4)] = J
imap, gmap = pauli_action(active, nspin)
H.append((active, h_alpha, imap, gmap))
Hm = Hmat(H)
print()
print_Hamiltonian(H)
return H
def Ising(nspin,R,psi): H = [] for i in range(nspin): j = (i+1)%nspin # ----- active = [k for k in range(nspin) if dpbc(i,k,nspin)<R or dpbc(j,k,nspin)<R] active = np.asarray(active) nact = len(active) # ----- h_alpha = np.zeros(4**nact) ii = np.where(active==i)[0][0] jj = np.where(active==j)[0][0] idx = [0]*nact idx[ii] = 3 h_alpha[Bas2Int(idx,4)] = np.sin(psi)/2.0 idx = [0]*nact idx[jj] = 3 h_alpha[Bas2Int(idx,4)] = np.sin(psi)/2.0 idx = [0]*nact idx[ii] = 1 idx[jj] = 1 h_alpha[Bas2Int(idx,4)] = np.cos(psi) # ----- imap,gmap = pauli_action(active,nspin) H.append((active,h_alpha,imap,gmap)) return H
def MaxCut(graph, R):
VV, EE = graph
nbit = len(VV)
H = []
for (i, j) in EE:
# -----
active = [
k for k in range(nbit)
if dgr(graph, i, k) < R or dgr(graph, j, k) < R
]
active = np.asarray(active)
nact = len(active)
# -----
h_alpha = np.zeros(4**nact)
ii = np.where(active == i)[0][0]
jj = np.where(active == j)[0][0]
idx = [0] * nact
h_alpha[Bas2Int(idx, 4)] = -0.5
idx[ii] = 3
idx[jj] = 3
h_alpha[Bas2Int(idx, 4)] = 0.5
# -----
imap, gmap = pauli_action(active, nbit)
H.append((active, h_alpha, imap, gmap))
return H
def single_qubit_field(psi):
H = []
nspin = 1
active = [0]
nact = len(active)
h_alpha = np.zeros(4**nact)
h_alpha[Bas2Int([1], 4)] = np.sin(psi)
h_alpha[Bas2Int([3], 4)] = np.cos(psi)
imap, gmap = pauli_action(active, nspin)
H.append((active, h_alpha, imap, gmap))
return H
def Heisenberg_LR(nspin, R):
H = []
for i in range(nspin):
for j in range(i + 1, nspin):
print(i, j)
# -----
active = [
k for k in range(nspin)
if dobc(i, k, nspin) < R or dobc(j, k, nspin) < R
]
active = np.asarray(active)
nact = len(active)
print(active)
# -----
h_alpha = np.zeros(4**nact)
ii = np.where(active == i)[0][0]
jj = np.where(active == j)[0][0]
for alpha in range(1, 4):
idx = [0] * nact
idx[ii] = alpha
idx[jj] = alpha
h_alpha[Bas2Int(idx, 4)] = 1.0 / (dobc(i, j, nspin) + 1.0)
# -----
#print h_alpha
imap, gmap = pauli_action(active, nspin)
H.append((active, h_alpha, imap, gmap))
return H
def Heisenberg_SR(nspin, R):
H = []
imax = nspin
if (nspin == 2): imax = nspin - 1
for i in range(imax):
j = (i + 1) % nspin
active = [
k for k in range(nspin)
if dpbc(i, k, nspin) < R or dpbc(j, k, nspin) < R
]
active = np.asarray(active)
nact = len(active)
# -----
h_alpha = np.zeros(4**nact)
ii = np.where(active == i)[0][0]
jj = np.where(active == j)[0][0]
for alpha in range(1, 4):
idx = [0] * nact
idx[ii] = alpha
idx[jj] = alpha
h_alpha[Bas2Int(idx, 4)] = 1.0
# -----
imap, gmap = pauli_action(active, nspin)
H.append((active, h_alpha, imap, gmap))
return H
def lie_algebra(mu, nu, n):
# Return coefficients and index for sigma mu,sigma nu
index = ''
coeff = 1
for i in range(n):
tmpA, tmpB = PPmunu(mu[i] + nu[i])
index += tmpA
coeff *= tmpB
return coeff, Bas2Int(Str2Opp(index), 4)
def H_molecule(line):
# from O'Malley et al, https://arxiv.org/pdf/1512.06860.pdf
# H = \sum_i h[S_i] -> h_\alpha
nspin = 2
V = np.loadtxt('../../code_v4/h2.dat').T
V = V[:, line]
print(V)
H = []
active = [0, 1]
active = np.asarray(active)
nact = len(active)
# -----
h_alpha = np.zeros(4**nact)
h_alpha[Bas2Int([0, 0], 4)] = V[1]
h_alpha[Bas2Int([3, 0], 4)] = V[2]
h_alpha[Bas2Int([0, 3], 4)] = V[3]
h_alpha[Bas2Int([3, 3], 4)] = V[4]
h_alpha[Bas2Int([1, 1], 4)] = V[5]
h_alpha[Bas2Int([2, 2], 4)] = V[6]
# -----
imap, gmap = pauli_action(active, nspin)
H.append((active, h_alpha, imap, gmap))
# print(H)
return H
import numpy as np
import sys
sys.path.append('../../../../../code_v4/')
from hamiltonian import Heisenberg_LR, print_Hamiltonian
from mf import hom_mf_solution, hom_mf_state, hom_mf_energy, mf_solution, mf_state, mf_energy
from ite import ITE_FCI
from qite import QITE
from binary_functions import Bas2Int
nspin = 2
R = 0.50
db = 0.01
bmax = 4.00
H = Heisenberg_LR(nspin, R)
print_Hamiltonian(H)
# AFM initial guess
psi_0 = np.zeros(2**nspin, dtype=complex)
xvec = [0, 1] * (nspin / 2)
xind = Bas2Int(xvec, 2)
psi_0[xind] = 1.0
ITE_FCI(H, db, bmax, psi0=psi_0)
QITE(H, db, bmax, lanczos=False, psi0=psi_0, ncheck=10)
def Hubbard(norb, R, U):
H = []
nspin = 2 * norb
# ----- encoding:
# 0u 0d 1u 1d 2u 2d 3u 3d ... (n-1)u (n-1)d
# 0 1 2 3 4 5 6 7 ... 2n-2 2n-1
# ----- formulas:
# n0 => (1-Zp)/2
# (a*_p a_q + a*_q a_p) = (1/2) X_p X_q (prod_{k=q+1}^{p-1} Z_k ) (1- Z_p Z_q) with p>q
# ----- potential energy:
# n_iu n_id = (1-Z_{2i}) (1-Z_{2i+1})/4 for i = 0 ... n-1
# ----- kinetic energy (open boundary conditions):
# a*_{iu} a_{i+1u} + hc => (a*_p a_q + a*_q a_p) with p=2i q=2i+2, i=0 ... n-2
# a*_{id} a_{i+1d} + hc => (a*_p a_q + a*_q a_p) with p=2i+1 q=2i+3, i=1 ... n-2
# ----- potential energy
for i in range(norb - 1):
print(">>>>>>> sites ", i, i + 1)
print("neighborhood")
dij = np.asarray(
[min(np.abs(i - j), np.abs(i + 1 - j)) for j in range(norb)])
idx = np.where(dij < R)[0]
print(idx)
pmin = 2 * min(idx)
pmax = 2 * max(idx) + 1
act = range(pmin, pmax + 1)
nact = len(act)
print(act)
print("-----")
h_alpha = np.zeros(4**nact)
for k in (i, i + 1):
pk = 2 * k - pmin
print("interaction on site ", k)
wk = 0.5
#idx = [0]*nact
#h_alpha[Bas2Int(idx,4)] += U*wk/4.0+(U/2)*wk/2.0
if (k == 0 or k == norb - 1): wk = 1.0
print("indices", pk, pk + 1, nact, wk)
# -----
idx = [0] * nact
idx[pk] = 3
print(idx)
h_alpha[Bas2Int(
idx, 4
)] = -U * wk / 4.0 + (U / 2) * wk / 2.0 # half-filling Hubbard
# -----
idx = [0] * nact
idx[pk + 1] = 3
print(idx)
h_alpha[Bas2Int(
idx, 4
)] = -U * wk / 4.0 + (U / 2) * wk / 2.0 # half-filling Hubbard
# -----
idx = [0] * nact
idx[pk] = 3
idx[pk + 1] = 3
print(idx)
h_alpha[Bas2Int(idx, 4)] = U * wk / 4.0
# -----
print("kinetic")
for sigma in (0, 1):
print("spin ", sigma)
p = (2 * i + sigma) - pmin
q = p + 2
# -----
idx = [0] * nact
idx[p] = 1
idx[p + 1] = 3
idx[q] = 1
print(idx)
h_alpha[Bas2Int(idx, 4)] = -0.5
# -----
idx = [0] * nact
idx[p] = 2
idx[p + 1] = 3
idx[q] = 2
print(idx)
h_alpha[Bas2Int(idx, 4)] = -0.5
imap, gmap = pauli_action(act, nspin)
H.append((act, h_alpha, imap, gmap))
print("remember to add the constant correction ",
U * norb / 4.0 - (U / 2) * 2 * norb / 2.0)
return H
# First populate the Lie algebra rules
index = np.zeros([4**2, 4**2], dtype=int)
coeff = np.zeros([4**2, 4**2], dtype=complex)
row = 0
for i in range(4**2):
column = 0
for j in range(4**2):
Pnu = Opp2Str(Int2Bas(column, 4, 2))
Pmu = Opp2Str(Int2Bas(row, 4, 2))
A = Pmu[0] + Pnu[0]
B = Pmu[1] + Pnu[1]
A, intA = PPmunu(A)
B, intB = PPmunu(B)
index[i, j] = Bas2Int(Str2Opp(A + B), 4)
coeff[i, j] = intA * intB
column += 1
row += 1
#
phi = psi
# Store the energy for initial wavefunction
e = np.matmul(Hamiltonian, phi)
e = np.real(np.matmul(np.transpose(np.conj(phi)), e))
energy_qite_list.append(e)
alist = []
print('We start QITE now')
for i in range(0, N):
# First construct Pmu_expectation matrices
