vector_1d.py

import torch

import meent


def run():
    rcwa_options = dict(backend=2, thickness=[205, 100000], period=[300, 300],
                        fto=[3, 0],
                        n_top=1, n_bot=1,
                        wavelength=900,
                        pol=0.5,
                        )

    # si = 3.638751670074983-0.007498295841854125j
    si = 3.638751670074983
    sio2 = 1.4518-0j
    si3n4 = 2.0056-0j

    ucell = [
        # layer 1
        [si3n4,
            [
                # obj 1
                ['rectangle', 50, 150, 31, 300, si, 0, 0, 0],
                # obj 2
                ['rectangle', 200, 150, 49.5, 300, si, 0, 0, 0],
            ],
        ],
        # layer 2
        [si,
         []
        ],
    ]

    mee = meent.call_mee(**rcwa_options)
    mee.ucell = ucell

    result = mee.conv_solve()

    result_given_pol = result.res
    result_te_incidence = result.res_te_inc
    result_tm_incidence = result.res_tm_inc

    de_ri, de_ti = result_given_pol.de_ri, result_given_pol.de_ti
    de_ri1, de_ti1 = result_te_incidence.de_ri, result_te_incidence.de_ti
    de_ri2, de_ti2 = result_tm_incidence.de_ri, result_tm_incidence.de_ti

    print(de_ri.sum(), de_ti.sum())
    print(de_ri1.sum(), de_ti1.sum())
    print(de_ri2.sum(), de_ti2.sum())

    return


if __name__ == '__main__':

    run()

    print(0)