def get_optimal_vector(self):
if 'opt_params' not in self._ret:
raise AquaError("Cannot find optimal vector before running the algorithm to find optimal params.")
qc = self.get_optimal_circuit()
if self._quantum_instance.is_statevector:
ret = self._quantum_instance.execute(qc)
self._ret['min_vector'] = ret.get_statevector(qc, decimals=16)
else:
c = ClassicalRegister(qc.width(), name='c')
q = find_regs_by_name(qc, 'q')
qc.add_register(c)
qc.barrier(q)
qc.measure(q, c)
ret = self._quantum_instance.execute(qc)
self._ret['min_vector'] = ret.get_counts(qc)
return self._ret['min_vector']
def _solve(self):
opt_params, opt_val = self.find_minimum_eigenvalue()
self._ret['eigvals'] = np.asarray([opt_val])
self._ret['opt_params'] = opt_params
qc = self._var_form.construct_circuit(self._ret['opt_params'])
if self._quantum_instance.is_statevector:
ret = self._quantum_instance.execute(qc)
self._ret['eigvecs'] = np.asarray([ret.get_statevector(qc)])
else:
c = ClassicalRegister(self._operator.num_qubits, name='c')
q = find_regs_by_name(qc, 'q')
qc.add_register(c)
qc.barrier(q)
qc.measure(q, c)
ret = self._quantum_instance.execute(qc)
self._ret['eigvecs'] = np.asarray([ret.get_counts(qc)])
