Source code for mindquantum.nn.evolution

# Copyright 2021 Huawei Technologies Co., Ltd
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# Licensed under the Apache License, Version 2.0 (the "License");
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# http://www.apache.org/licenses/LICENSE-2.0
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"""Mindspore quantum simulator evolution operator."""

from projectq.ops import QubitOperator
from mindspore.ops.primitive import PrimitiveWithInfer
from mindspore.ops.primitive import prim_attr_register
from mindspore._checkparam import Validator as validator
from mindspore.common import dtype as mstype
from mindquantum.circuit import Circuit
from mindquantum.gate import Hamiltonian
from ._check_qnn_input import _check_circuit
from ._check_qnn_input import _check_type_or_iterable_type
from ._check_qnn_input import _check_parameters_of_circuit


class Evolution(PrimitiveWithInfer):
    r"""
    Inputs of this operation is generated by MindQuantum framework.

    Inputs:
        - **n_qubits** (int) - The qubit number of quantum simulator.
        - **param_names** (list[str]) - The parameters names.
        - **gate_names** (list[str]) - The name of each gate.
        - **gate_matrix** (list[list[list[list[float]]]]) - Real part and image part of the matrix of quantum gate.
        - **gate_obj_qubits** (list[list[int]]) - Object qubits of each gate.
        - **gate_ctrl_qubits** (list[list[int]]) - Control qubits of each gate.
        - **gate_params_names** (list[list[str]]) - Parameter names of each gate.
        - **gate_coeff** (list[list[float]]) - Coefficient of eqch parameter of each gate.
        - **gate_requires_grad** (list[list[bool]]) - Whether to calculate gradient of parameters of gates.
        - **hams_pauli_coeff** (list[list[float]]) - Coefficient of pauli words.
        - **hams_pauli_word** (list[list[list[str]]]) - Pauli words.
        - **hams_pauli_qubit** (list[list[list[int]]]) - The qubit that pauli matrix act on.

    Outputs:
        - **Quantum state** (Tensor) - The quantum state after evolution.

    Supported Platforms:
        ``CPU``
    """
    @prim_attr_register
    def __init__(self, n_qubits, param_names, gate_names, gate_matrix,
                 gate_obj_qubits, gate_ctrl_qubits, gate_params_names,
                 gate_coeff, gate_requires_grad, hams_pauli_coeff,
                 hams_pauli_word, hams_pauli_qubit):
        """Initialize Evolutino"""
        self.init_prim_io_names(inputs=['param_data'], outputs=['state'])
        self.n_qubits = n_qubits

    def check_shape_size(self, param_data):
        if len(param_data) != 1:
            raise ValueError("PQC input param_data should have dimension size \
equal to 1, but got {}.".format(len(param_data)))

    def infer_shape(self, param_data):
        self.check_shape_size(param_data)
        return [1 << self.n_qubits, 2]

    def infer_dtype(self, param_data):
        args = {'param_data': param_data}
        validator.check_tensors_dtypes_same_and_valid(args, mstype.float_type,
                                                      self.name)
        return param_data


[docs]def generate_evolution_operator(param_names, circuit: Circuit, hams=None): """ A method to generate a parameterized quantum circuit simulation operator. Args: param_names (list[str]): The list of parameter names. circuit (Circuit): The whole circuit combined with encoder circuit and ansatz circuit. hams (Union[Hamiltonian, list[Hamiltonian]]): The measurement hamiltonian. Returns: Evolution, A parameterized quantum circuit simulator operator supported by mindspore framework. Examples: >>> import numpy as np >>> from mindspore import Tensor >>> import mindquantum.gate as G >>> from mindquantum import Circuit >>> circ = Circuit(G.RX('a').on(0)) >>> evol = generate_evolution_operator(['a'], circ) >>> state = evol(Tensor(np.array([0.5]).astype(np.float32))) >>> state = state.asnumpy() >>> state = state[:, 0] + 1j * state[:, 1] array([0.9689124+0.j , 0. -0.24740396j], dtype=complex64) >>> G.RX(0.5).matrix()[:, 0] array([0.96891242+0.j , 0. -0.24740396j]) """ _check_circuit(circuit, 'circuit') _check_parameters_of_circuit([], param_names, circuit) if hams is not None: _check_type_or_iterable_type(hams, Hamiltonian, 'Hamiltonian') if circuit.n_qubits == -1: circuit.summary(False) if isinstance(hams, Hamiltonian): hams = [hams] if hams is None: ham_ms_data = Hamiltonian(QubitOperator()).mindspore_data() else: ham_ms_data = {} for ham in hams: for k, v in ham.mindspore_data().items(): if k not in ham_ms_data: ham_ms_data[k] = [v] else: ham_ms_data[k].append(v) return Evolution(circuit.n_qubits, param_names=param_names, **circuit.mindspore_data(), **ham_ms_data)