def METHOD_NAME(state, section_size=2):
    """
    Synthesize linear reversible circuits for all-to-all architecture
    using Patel, Markov and Hayes method.
    This function is an implementation of the Patel, Markov and Hayes algorithm from [1]
    for optimal synthesis of linear reversible circuits for all-to-all architecture,
    as specified by an n x n matrix.
    Args:
        state (list[list] or ndarray): n x n boolean invertible matrix, describing the state
            of the input circuit
        section_size (int): the size of each section, used in the
            Patel–Markov–Hayes algorithm [1]. section_size must be a factor of num_qubits.
    Returns:
        QuantumCircuit: a CX-only circuit implementing the linear transformation.
    Raises:
        QiskitError: when variable "state" isn't of type numpy.ndarray
    References:
        1. Patel, Ketan N., Igor L. Markov, and John P. Hayes,
           *Optimal synthesis of linear reversible circuits*,
           Quantum Information & Computation 8.3 (2008): 282-294.
           `arXiv:quant-ph/0302002 [quant-ph] <https://arxiv.org/abs/quant-ph/0302002>`_
    """
    return synth_cnot_count_full_pmh(state, section_size=section_size)