91 lines
2.4 KiB
Python
91 lines
2.4 KiB
Python
import importlib
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import numpy
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from numpy.linalg import norm
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from meanas import vec, unvec
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from meanas.fdfd import waveguide_mode, functional, scpml
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from meanas.fdfd.solvers import generic as generic_solver
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import gridlock
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from matplotlib import pyplot
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__author__ = 'Jan Petykiewicz'
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def test1(solver=generic_solver):
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dx = 20 # discretization (nm/cell)
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pml_thickness = 10 # (number of cells)
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wl = 1550 # Excitation wavelength
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omega = 2 * numpy.pi / wl
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# Device design parameters
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w = 800
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th = 220
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center = [0, 0, 0]
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r0 = 8e3
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# refractive indices
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n_wg = numpy.sqrt(12.6) # ~Si
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n_air = 1.0 # air
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# Half-dimensions of the simulation grid
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y_max = 1200
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z_max = 900
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xyz_max = numpy.array([800, y_max, z_max]) + (pml_thickness + 2) * dx
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# Coordinates of the edges of the cells.
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half_edge_coords = [numpy.arange(dx/2, m + dx/2, step=dx) for m in xyz_max]
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edge_coords = [numpy.hstack((-h[::-1], h)) for h in half_edge_coords]
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edge_coords[0] = numpy.array([-dx, dx])
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# #### Create the grid and draw the device ####
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grid = gridlock.Grid(edge_coords, initial=n_air**2, num_grids=3)
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grid.draw_cuboid(center=center, dimensions=[8e3, w, th], eps=n_wg**2)
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dxes = [grid.dxyz, grid.autoshifted_dxyz()]
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for a in (1, 2):
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for p in (-1, 1):
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dxes = scmpl.stretch_with_scpml(dxes, omega=omega, axis=a, polarity=p,
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thickness=pml_thickness)
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wg_args = {
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'omega': omega,
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'dxes': [(d[1], d[2]) for d in dxes],
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'epsilon': vec(g.transpose([1, 2, 0]) for g in grid.grids),
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'r0': r0,
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}
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wg_results = waveguide_mode.solve_waveguide_mode_cylindrical(mode_number=0, **wg_args)
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E = wg_results['E']
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n_eff = wl / (2 * numpy.pi / wg_results['wavenumber'])
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print('n =', n_eff)
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print('alpha (um^-1) =', -4 * numpy.pi * numpy.imag(n_eff) / (wl * 1e-3))
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'''
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Plot results
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'''
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def pcolor(v):
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vmax = numpy.max(numpy.abs(v))
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pyplot.pcolor(v.T, cmap='seismic', vmin=-vmax, vmax=vmax)
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pyplot.axis('equal')
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pyplot.colorbar()
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pyplot.figure()
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pyplot.subplot(2, 2, 1)
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pcolor(numpy.real(E[0][:, :]))
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pyplot.subplot(2, 2, 2)
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pcolor(numpy.real(E[1][:, :]))
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pyplot.subplot(2, 2, 3)
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pcolor(numpy.real(E[2][:, :]))
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pyplot.subplot(2, 2, 4)
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pyplot.show()
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if __name__ == '__main__':
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test1()
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