_sparse_tools.py 文件源码

def get_gap(sparse_operator):
    """Compute gap between lowest eigenvalue and first excited state.

    Returns: A real float giving eigenvalue gap.
    """
    if not is_hermitian(sparse_operator):
        raise ValueError('sparse_operator must be Hermitian.')

    values, _ = scipy.sparse.linalg.eigsh(
        sparse_operator, 2, which='SA', maxiter=1e7)

    gap = abs(values[1] - values[0])
    return gap