qiskit/providers/basicaer/basicaertools.py
def einsum_matmul_index(gate_indices, number_of_qubits):
    """Return the index string for Numpy.eignsum matrix-matrix multiplication.

    The returned indices are to perform a matrix multiplication A.B where
    the matrix A is an M-qubit matrix, matrix B is an N-qubit matrix, and
    M <= N, and identity matrices are implied on the subsystems where A has no
    support on B.

    Args:
        gate_indices (list[int]): the indices of the right matrix subsystems
                                   to contract with the left matrix.
        number_of_qubits (int): the total number of qubits for the right matrix.

    Returns:
        str: An indices string for the Numpy.einsum function.
    """

    mat_l, mat_r, tens_lin, tens_lout = _einsum_matmul_index_helper(gate_indices,
                                                                    number_of_qubits)

    # Right indices for the N-qubit input and output tensor
    tens_r = ascii_uppercase[:number_of_qubits]

    # Combine indices into matrix multiplication string format
    # for numpy.einsum function
    return "{mat_l}{mat_r}, ".format(mat_l=mat_l, mat_r=mat_r) + \
           "{tens_lin}{tens_r}->{tens_lout}{tens_r}".format(tens_lin=tens_lin,
                                                            tens_lout=tens_lout,
                                                            tens_r=tens_r)
def einsum_matmul_index(gate_indices, number_of_qubits):
    mat_l, mat_r, tens_lin, tens_lout = _einsum_matmul_index_helper(gate_indices,
                                                                    number_of_qubits)

    # Right indices for the N-qubit input and output tensor
    tens_r = ascii_uppercase[:number_of_qubits]

    # Combine indices into matrix multiplication string format
    # for numpy.einsum function
    return "{mat_l}{mat_r}, ".format(mat_l=mat_l, mat_r=mat_r) + \
           "{tens_lin}{tens_r}->{tens_lout}{tens_r}".format(tens_lin=tens_lin,
                                                            tens_lout=tens_lout,
                                                            tens_r=tens_r)
def einsum_matmul_index ( gate_indices , number_of_qubits ) : mat_l , mat_r , tens_lin , tens_lout = _einsum_matmul_index_helper ( gate_indices , number_of_qubits ) # Right indices for the N-qubit input and output tensor tens_r = ascii_uppercase [ : number_of_qubits ] # Combine indices into matrix multiplication string format # for numpy.einsum function return "{mat_l}{mat_r}, " . format ( mat_l = mat_l , mat_r = mat_r ) + "{tens_lin}{tens_r}->{tens_lout}{tens_r}" . format ( tens_lin = tens_lin , tens_lout = tens_lout , tens_r = tens_r )
Return the index string for Numpy.eignsum matrix-matrix multiplication.

    The returned indices are to perform a matrix multiplication A.B where
    the matrix A is an M-qubit matrix, matrix B is an N-qubit matrix, and
    M <= N, and identity matrices are implied on the subsystems where A has no
    support on B.

    Args:
        gate_indices (list[int]): the indices of the right matrix subsystems
                                   to contract with the left matrix.
        number_of_qubits (int): the total number of qubits for the right matrix.

    Returns:
        str: An indices string for the Numpy.einsum function.
Return the index string for Numpy . eignsum matrix - matrix multiplication .