def pauli_action(active_, nbit_, verbose=False):
nact = len(active_)
N = 2**nbit_
M = 4**nact
dot = [2**(nbit_ - 1 - i) for i in range(nbit_)]
ind_sx = np.zeros((M, N), dtype=int)
gmm_sx = np.zeros((M, N), dtype=complex) + 1
svec = np.zeros((M, nbit_), dtype=int)
for mu in range(M):
svec[mu, active_] = Int2Bas(mu, 4, nact)
sxyvec = d12f(svec)
nyvec = d2f(svec)
syzvec = d23f(svec)
nyvec = np.einsum('ab->a', nyvec)
xvec = np.zeros((N, nbit_), dtype=int)
for xi in range(N):
xvec[xi, :] = np.asarray(Int2Bas(xi, 2, nbit_))
gmm_sx = np.einsum('am,bm->ba', xvec, syzvec) + 0j
gmm_sx[:, :] = (-1)**gmm_sx[:, :]
for mu in range(M):
gmm_sx[mu, :] *= 1j**nyvec[mu]
yvec = (xvec[:, :] + sxyvec[mu, :]) % 2
ind_sx[mu, :] = np.einsum('a,ba->b', dot, yvec)
return ind_sx, gmm_sx
def RTE(H_, dT, Tmax, lanczos=False, psi0=None):
# --- diagonalization ---
N = H_[0][2].shape[1]
nbit = int(np.log2(N))
hdiag = np.zeros(N, dtype=complex)
ei = np.zeros(N, dtype=complex)
for i in range(N):
xi = Int2Bas(i, 2, nbit)
for (A, h, imp, gmp) in H_:
nact = len(A)
for m in np.where(np.abs(h) > 1e-8)[0]:
sm = Int2Bas(m, 4, nact)
#print A,sm,[xi[A[i]] for i in range(nact)]
smx = [
sigma_matrices[xi[A[w]], xi[A[w]], sm[w]]
for w in range(nact)
]
hdiag[i] += h[m] * np.prod(smx)
if (i % 1000 == 0): print i, N, hdiag[i]
precond = lambda x, e, *args: x / (hdiag - e + 1e-4)
def hop(c_):
return Hpsi(H_, c_)
epsm0, Um0 = davidson(hop, psi0, precond)
fout = open('RTE_davidson.out', 'w')
fout.write("gs energy %.6f \n" % epsm0)
# --- initial state ---
if (psi0 is None):
i0 = np.argmin(hdiag)
psi0 = np.zeros(N, dtype=complex)
psi0[i0] = 1.0
# --- real-time evolution ---
bra_RTE = psi0[:]
braH_RTE = Hpsi(H_, psi0[:])[:]
ket_RTE = psi0[:]
nbeta = int(Tmax / dT) + 1
hvect_LANZ = np.zeros(nbeta + 1, dtype=complex)
svect_LANZ = np.zeros(nbeta + 1, dtype=complex)
fout.write("ITE\n")
for ib in range(nbeta):
hvect_LANZ[ib] = np.einsum('a,a', np.conj(braH_RTE), ket_RTE)
svect_LANZ[ib] = np.einsum('a,a', np.conj(bra_RTE), ket_RTE)
ket_RTE = ExpitH(H_, ket_RTE, dT)[0]
print ib, hvect_LANZ[ib]
dump_lanz_rte(hvect_LANZ[:nbeta], svect_LANZ[:nbeta], 'qlanz.vecs')
fout.close()
def Hii(H_,i): N = H_[0][2].shape[1] nbit = int(np.log2(N)) hii = 0.0 xi = Int2Bas(i,2,nbit) for (A,h,imp,gmp) in H_: nact = len(A) for m in np.where(np.abs(h)>1e-8)[0]: sm = Int2Bas(m,4,nact) smx = [ sigma_matrices[xi[A[w]],xi[A[w]],sm[w]] for w in range(nact)] hii += np.real(h[m]*np.prod(smx)) return hii
def print_state(psi_, nbit, outf):
for i in range(psi_.shape[0]):
if (np.abs(psi_[i]) > 1e-4):
for x in Int2Bas(i, 2, nbit):
outf.write(str(x))
outf.write(" %.12f %.12f I \n" %
(np.real(psi_[i]), np.imag(psi_[i])))
def hom_mf_state(theta_, nbit_):
chi = np.zeros(2)
chi[0] = np.cos(theta_)
chi[1] = np.sin(theta_)
N = 2**nbit_
phi = np.zeros(N, dtype=complex)
for i in range(N):
x = Int2Bas(i, 2, nbit_)
phi[i] = np.prod([chi[x[k]] for k in range(nbit_)])
return phi
def print_Hamiltonian(H_): mu = 0 for (A,h,imp,gmp) in H_: nact = len(A) print "term ",mu print "active qubits ",A print "operators: " for m in np.where(np.abs(h)>1e-8)[0]: print Opp2Str(Int2Bas(m,4,nact)),h[m] mu += 1
def print_Hamiltonian(H_):
mu = 0
for (A, h, imp, gmp) in H_:
#print('A: ',A)
nact = len(A)
print("active qubits ", A)
print("operators: ")
for m in np.where(np.abs(h) > 1e-8)[0]:
print(Opp2Str(Int2Bas(m, 4, nact)), h[m])
mu += 1
def hom_mf_energy(theta, nbit, H_):
chi = np.zeros(2)
chi[0] = np.cos(theta)
chi[1] = np.sin(theta)
xjm = np.einsum('a,abc,b->c', chi, sigma_matrices, chi)
xjm = np.real(xjm)
ea = 0.0
for (A, h, imp, gmp) in H_:
nact = len(A)
for m in np.where(np.abs(h) > 1e-8)[0]:
xm = Int2Bas(m, 4, nact)
ea += h[m] * np.prod([xjm[xm[k]] for k in range(nact)])
return ea
def mf_state(theta_):
nbit = theta_.shape[0]
chi = np.zeros((nbit, 2))
for i in range(nbit):
chi[i, 0] = np.cos(theta_[i])
chi[i, 1] = np.sin(theta_[i])
# -----
N = 2**nbit
phi = np.zeros(N, dtype=complex)
for i in range(N):
x = Int2Bas(i, 2, nbit)
phi[i] = np.prod([chi[k, x[k]] for k in range(nbit)])
# -----
return phi
def mf_energy(theta_, H_):
nbit = theta_.shape[0]
chi = np.zeros((nbit, 2))
for i in range(nbit):
chi[i, 0] = np.cos(theta_[i])
chi[i, 1] = np.sin(theta_[i])
# -----
xjm = np.einsum('ja,abc,jb->jc', chi, sigma_matrices, chi)
xjm = np.real(xjm)
ea = 0.0
for (A, h, imp, gmp) in H_:
nact = len(A)
for m in np.where(np.abs(h) > 1e-8)[0]:
xm = Int2Bas(m, 4, nact)
ea += h[m] * np.prod([xjm[A[k], xm[k]] for k in range(nact)])
return ea
def pauli_basis(nbit_):
M = 4**nbit_
for i in range(M):
print(i, Opp2Str(Int2Bas(i, 4, nbit_)))
def computational_basis(nbit_):
N = 2**nbit_
for i in range(N):
print(i, Psi2Str(Int2Bas(i, 2, nbit_)))
elif Oppstr == "ZX":
return "Y", 1j
elif Oppstr == "ZY":
return "X", -1j
elif Oppstr == "ZZ":
return "I", 1
else:
raise ValueError
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)
if __name__ == '__main__':
n = 2
index = np.zeros([4**n, 4**n], dtype=int)
coeff = np.zeros([4**n, 4**n], dtype=complex)
for i in range(4**n):
for j in range(4**n):
coeff[i, j], index[i, j] = lie_algebra(Opp2Str(Int2Bas(i, 4, n)),
Opp2Str(Int2Bas(j, 4, n)),
n)
print(i, j, index[i, j])
e = np.matmul(Hamiltonian, phi)
e = np.real(np.matmul(np.transpose(np.conj(phi)), e))
energy_classical_list.append(e)
print('Final energy at beta', beta, 'is ', e)
# Qite approximation
# 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))
