e9b118563c4089f6cd997e79abe3449617acfd7c,qiskit_aqua/algorithms/single_sample/qpe/qpe.py,QPE,init_params,#QPE#Any#Any#,112

Before Change

        iqft_params = params.get(QuantumAlgorithm.SECTION_KEY_IQFT)
        iqft_params["num_qubits"] = num_ancillae
        iqft = get_pluggable_class(PluggableType.IQFT,iqft_params["name"])
        iqft = iqft()
        iqft.init_params(iqft_params)

        self.init_args(
            operator, init_state, iqft, num_time_slices, num_ancillae,
            paulis_grouping=paulis_grouping, expansion_mode=expansion_mode,
            expansion_order=expansion_order)

    def init_args(
            self, operator, state_in, iqft, num_time_slices, num_ancillae,
            paulis_grouping="random", expansion_mode="trotter", expansion_order=1,

After Change

        // Set up initial state, we need to add computed num qubits to params
        init_state_params = params.get(QuantumAlgorithm.SECTION_KEY_INITIAL_STATE)
        init_state_params["num_qubits"] = operator.num_qubits
        init_state = get_pluggable_class(PluggableType.INITIAL_STATE,
                                         init_state_params["name"]).init_params(init_state_params)

        // Set up iqft, we need to add num qubits to params which is our num_ancillae bits here
        iqft_params = params.get(QuantumAlgorithm.SECTION_KEY_IQFT)
        iqft_params["num_qubits"] = num_ancillae
        iqft = get_pluggable_class(PluggableType.IQFT, iqft_params["name"]).init_params(iqft_params)

        return cls(operator, init_state, iqft, num_time_slices, num_ancillae,
                   paulis_grouping=paulis_grouping, expansion_mode=expansion_mode,
                   expansion_order=expansion_order)

    def _construct_qpe_evolution(self):
        Implement the Quantum Phase Estimation algorithm

Instances