edoardo 5b18e7bce7 after the first tests, I increase the number of iterations per epoch

2026-05-29 14:29:30 +02:00

misc

modified version of metapeg, using epigraph and linewidth/spacing constraints

2026-05-24 17:47:07 +02:00

hdf5_vis.py

another parameter test

2026-05-25 16:44:50 +02:00

metapeg_v2.py

after the first tests, I increase the number of iterations per epoch

2026-05-29 14:29:30 +02:00

metapeg.ipynb

modified version of metapeg, using epigraph and linewidth/spacing constraints

2026-05-24 17:47:07 +02:00

metapeg.py

modified version of metapeg, using epigraph and linewidth/spacing constraints

2026-05-24 17:47:07 +02:00

mode_converter.ipynb

first debug on metapeg. At the moment there is only one frequency being optimized. Although we are not using the epigraph yet, it would still be convenient to still consider a small range around the central frequency and optimize the average objective between them. This would still be better than considering only one frequency, but for the moment I need to understand if this model can work or not. Before running a full batch, more debugging is required to better understand how everything works. In this release, the code has not been tested in the results part, but the main optimization function run a couple of rounds without throwing errors. We still need to assure the normalization we make on the far fields is reasonable or not. The next step is to run a dummy simulation until the end and observe the results generation works, then the true test would be to let it run a true optimization with the right resolution.

2026-05-13 22:43:54 +02:00

mode_converter.py

fixed observed far-field component

2026-05-13 10:43:51 +02:00

sim_opt_design.py

1) minor changes to metapeg_v2, but we no longer modify the chunk property and leave it to the default value (=True). Setting it to False causes segmentation errors in the adjoint loop, but works for direct simulations (for example in the normalization run) 2) added sim_opt_design, which is used to simulate an optimized design given the values of an optimized MaterialGrid after and outside the main optimization algorithm

2026-05-27 14:55:09 +02:00

S

Description

An inversly designed mode converter based on a custom ASM propagator. FDTD simulations (meep) are used to design the unit-cell and verify the full design.

45 MiB

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Python 9.2%