mps_of_last_layer = [A.copy() for A in mps_of_layer[current_depth]]
except Exception as e:
print(e)
stop_crit = 1e-1
assert np.isclose(mps_func.overlap(target_mps, target_mps), 1.)
for idx in range(running_idx, N_iter):
#################################
#### variational optimzation ####
#################################
try:
mps_of_last_layer, my_circuit = qTEBD.var_circuit(
target_mps, mps_of_last_layer, my_circuit, product_state)
except:
mps_of_last_layer, my_circuit = qTEBD.var_circuit2(
target_mps, product_state, my_circuit)
#################
#### Measure ####
#################
assert np.isclose(
mps_func.overlap(mps_of_last_layer, mps_of_last_layer), 1.)
current_energy = np.sum(
mps_func.expectation_values(mps_of_last_layer, H_list))
E_list.append(current_energy)
Sz_array[idx, :] = mps_func.expectation_values_1_site(
mps_of_last_layer, Sz_list)
ent_array[idx, :] = mps_func.get_entanglement(mps_of_last_layer)
fidelity_reached = np.abs(
mps_func.overlap(target_mps, mps_of_last_layer))**2
print("iter=", idx, " E=", E_list[-1], " Sz=", Sz_array[idx, L // 2])
assert np.isclose(mps_func.overlap(target_mps, target_mps), 1.)
for idx in range(running_idx, N_iter):
#################################
#### variational optimzation ####
#################################
try:
mps_of_last_layer, my_circuit = qTEBD.var_circuit(
target_mps,
mps_of_last_layer,
my_circuit,
product_state,
brickwall=True)
except:
mps_of_last_layer, my_circuit = qTEBD.var_circuit2(target_mps,
product_state,
my_circuit,
brickwall=True)
#################
#### Measure ####
#################
assert np.isclose(
mps_func.overlap(mps_of_last_layer, mps_of_last_layer), 1.)
current_energy = np.sum(
mps_func.expectation_values(mps_of_last_layer, H_list))
E_list.append(current_energy)
Sz_array[idx, :] = mps_func.expectation_values_1_site(
mps_of_last_layer, Sz_list)
ent_array[idx, :] = mps_func.get_entanglement(mps_of_last_layer)
fidelity_reached = np.abs(
mps_func.overlap(target_mps, mps_of_last_layer))**2
