update_error_list.append(1. - fidelity_reached)
current_energy = np.sum(mps_func.expectation_values(
A_list, H_list))
E_list.append(current_energy)
Sz_array[idx, :] = mps_func.expectation_values_1_site(
A_list, Sz_list)
ent_array[idx, :] = mps_func.get_entanglement(A_list)
t_list.append(t_list[-1] + dt)
print("T=", t_list[-1], " E=", E_list[-1], " Sz=",
Sz_array[idx, L // 2])
# N_iter = 10
continue
if order == '2nd':
Ap_list = qTEBD.apply_U(A_list, U_half_list, 0)
Ap_list = qTEBD.apply_U(Ap_list, U_list, 1)
Ap_list = qTEBD.apply_U(Ap_list, U_half_list, 0)
else:
Ap_list = qTEBD.apply_U(A_list, U_list, 0)
Ap_list = qTEBD.apply_U(Ap_list, U_list, 1)
# Ap_list = e^(-i dt H) | A_list >
# print("Norm new mps = ", mps_func.overlap(Ap_list, Ap_list), "new state aimed E = ",
# np.sum(mps_func.expectation_values(Ap_list, H_list, check_norm=False))/mps_func.overlap(Ap_list, Ap_list)
# )
### POLAR DECOMPOSITION UPDATE ###
Ap_norm_sq = mps_func.overlap(Ap_list, Ap_list)
fidelity_before = np.abs(mps_func.overlap(Ap_list,
A_list))**2 / Ap_norm_sq
running_idx = len(t_list)
try:
tuple_loaded = misc.load_circuit(dir_path, depth, N_iter, order)
running_idx, my_circuit, E_list, t_list, update_error_list, Sz_array, ent_array, num_iter_array = tuple_loaded
print(" old result loaded ")
mps_of_layer = qTEBD.circuit_2_mps(my_circuit, product_state)
mps_of_last_layer = [A.copy() for A in mps_of_layer[current_depth]]
except Exception as e:
print(e)
stop_crit = 1e-1
for idx in range(running_idx, int(total_t // dt) + 1):
# [TODO] remove the assertion below
assert np.isclose(mps_func.overlap(mps_of_last_layer, mps_of_last_layer), 1.)
if order == '2nd':
target_mps = qTEBD.apply_U(mps_of_last_layer, U_half_list, 0)
target_mps = qTEBD.apply_U(target_mps, U_list, 1)
target_mps = qTEBD.apply_U(target_mps, U_half_list, 0)
else:
# target_mps = [A.copy() for A in mps_of_last_layer]
# target_mps, _ = mps_func.right_canonicalize(target_mps, no_trunc=True)
# target_mps, trunc_error = qTEBD.apply_U_all(target_mps, U_list, False, no_trunc=True)
target_mps = qTEBD.apply_U(mps_of_last_layer, U_list, 0)
target_mps = qTEBD.apply_U(target_mps, U_list, 1)
mps_func.right_canonicalize(target_mps, no_trunc=True)
mps_func.left_canonicalize(target_mps, no_trunc=False)
# target_mps is the e(-H)|psi0> which is not normalizaed.
target_mps_norm_sq = mps_func.overlap(target_mps, target_mps)
product_state = [np.array([1., 0.]).reshape([2, 1, 1]) for i in range(L)]
mps_of_layer = qTEBD.circuit_2_mps(my_circuit, product_state)
E_list.append(np.sum(mps_func.expectation_values(mps_of_layer[-1],
H_list)))
for dt in [0.05, 0.01, 0.001]:
U_list = qTEBD.make_U(H_list, dt)
U_half_list = qTEBD.make_U(H_list, dt / 2.)
for i in range(int(40 // dt**(0.75))):
mps_of_layer = qTEBD.circuit_2_mps(my_circuit, product_state)
mps_of_last_layer = [A.copy() for A in mps_of_layer[current_depth]]
# [TODO] remove the assertion below
assert np.isclose(
mps_func.overlap(mps_of_last_layer, mps_of_last_layer), 1.)
if order == '2nd':
new_mps = qTEBD.apply_U(mps_of_last_layer, U_half_list, 0)
new_mps = qTEBD.apply_U(new_mps, U_list, 1)
new_mps = qTEBD.apply_U(new_mps, U_half_list, 0)
else:
new_mps = qTEBD.apply_U(mps_of_last_layer, U_list, 0)
new_mps = qTEBD.apply_U(new_mps, U_list, 1)
print(
"Norm new mps = ", mps_func.overlap(new_mps, new_mps),
"new state aimed E = ",
np.sum(
mps_func.expectation_values(
new_mps, H_list, check_norm=False)) /
mps_func.overlap(new_mps, new_mps))
# new_mps is the e(-H)|psi0> which is not normalizaed.