def vqe_run(self,
ansatz,
init_guess_parameters=None,
init_state_qasm=None,
excited_state=0,
cache=None):
assert len(ansatz) > 0
if init_guess_parameters is None:
var_parameters = numpy.zeros(
sum([element.n_var_parameters for element in ansatz]))
else:
assert len(init_guess_parameters) == sum(
[element.n_var_parameters for element in ansatz])
var_parameters = init_guess_parameters
LogUtils.vqe_info(self.q_system, self.backend, self.optimizer, ansatz)
self.iteration = 1
self.time_previous_iter = time.time()
# functions to be called by the optimizer
get_energy = partial(self.get_energy,
ansatz=ansatz,
backend=self.backend,
init_state_qasm=init_state_qasm,
excited_state=excited_state,
cache=cache)
get_gradient = partial(self.backend.ansatz_gradient,
ansatz=ansatz,
q_system=self.q_system,
init_state_qasm=init_state_qasm,
cache=cache,
excited_state=excited_state)
if self.use_ansatz_gradient:
result = scipy.optimize.minimize(get_energy,
var_parameters,
jac=get_gradient,
method=self.optimizer,
options=self.optimizer_options,
tol=config.optimizer_tol,
bounds=config.optimizer_bounds)
else:
result = scipy.optimize.minimize(get_energy,
var_parameters,
method=self.optimizer,
options=self.optimizer_options,
tol=config.optimizer_tol,
bounds=config.optimizer_bounds)
result['n_iters'] = self.iteration # cheating
return result
optimizer_options={'gtol': 1e-08},
use_ansatz_gradient=use_energy_vector_gradient)
# create a vqe_runner for excited states, where the minimum may be away from the zero, which will make gradient
# descent optimizers useless
# vqe_runner_2 = VQERunner(molecule, backend=QiskitSim, optimizer='BFGS', optimizer_options={'gtol': 1e-08},
# use_ansatz_gradient=use_grad)
vqe_runner_2 = VQERunner(molecule,
backend=backend,
optimizer='Nelder-Mead',
optimizer_options=None)
# <<<<<<<<<<<<<<<<<<<<<<<<<<<<<<<<<<<<<<<<<<<<<<<<<>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>
LogUtils.log_config()
logging.info('{}, r={} ,{}'.format(molecule.name, r, ansatz_element_type))
time_stamp = datetime.datetime.now().strftime("%d-%b-%Y (%H:%M:%S.%f)")
# create the pool of ansatz elements
if spin_complement:
ansatz_element_pool = SpinCompGSDExcitations(
molecule.n_orbitals,
molecule.n_electrons,
element_type=ansatz_element_type).get_excitations()
else:
ansatz_element_pool = GSDExcitations(
molecule.n_orbitals,
molecule.n_electrons,
ansatz_element_type=ansatz_element_type).get_excitations()
