def energy_along_flat(a, b):
ansatz_state = qnnops.alternating_layer_ansatz(origin + a * dx + b * dy,
n_qubits=cfg.n_qubits,
block_size=cfg.n_qubits,
n_layers=cfg.n_layers,
rot_axis=cfg.rot_axis)
return qnnops.energy(ham_matrix, ansatz_state) - eigval[0]
def loss(_params):
ansatz_state = qnnops.alternating_layer_ansatz(_params, n_qubits,
block_size, n_layers,
rot_axis)
return qnnops.energy(ham_matrix, ansatz_state)
def loss_fn(params):
ansatz_state = qnnops.alternating_layer_ansatz(params, n_qubits,
n_qubits, n_layers,
args.rot_axis)
return qnnops.energy(ham_matrix, ansatz_state)
def circuit(params):
return qnnops.alternating_layer_ansatz(
params, n_qubits=n_qubits, block_size=block_size, n_layers=n_layers, rot_axis=rot_axis)
def loss_fn(params):
ansatz_state = qnnops.alternating_layer_ansatz(
params, config.n_qubits, config.n_qubits, config.n_layers, config.rot_axis)
return qnnops.energy(ham_matrix, ansatz_state) - ground_energy