{"id":360116,"date":"2024-04-02T18:28:28","date_gmt":"2024-04-02T18:28:28","guid":{"rendered":"\/forum\/forums\/reply\/360116\/"},"modified":"2024-04-02T18:28:28","modified_gmt":"2024-04-02T18:28:28","slug":"360116","status":"publish","type":"reply","link":"https:\/\/innovationspace.ansys.com\/forum\/forums\/reply\/360116\/","title":{"rendered":"Reply To: Grating Coupler Double Etch Optimization using Gradient Based Inverse Design"},"content":{"rendered":"

<p>Regarding your suggestions, I still have a few questions about the number of parameters you can optimize in one run. If I were to optimize both etch depth and tooth position at the same time, do I add two parameters representing etch depth and tooth position respectively or do I expand the current parameter in the code to a 2 by 2*n_grates matrix? For example, params = matrix(i,j); params(i,1) = tooth position, params(i,2) = etch depth.<\/p><p>When you say locations are random, does it mean that the simulation will not follow a gradient-based optimization, which means it would be hard to know if the simulation has reached a local maximum in FOM? If that is the case, I would think it makes more sense to first optimize the position of the tooth and etch depth (without constraint in the latter) and then binarize the depths. Is the lumopt package capable of doing binarization only, or do I need to use a separate package?<\/p><p>Finally, the last idea is by optimizing the two etch steps separately, by running the optimization once using the half etch height and once again using the full etch height and then somehow combine the two. Do you think it is worth going down this path? Thanks again.<\/p><\/p>\n","protected":false},"template":"","class_list":["post-360116","reply","type-reply","status-publish","hentry"],"aioseo_notices":[],"aioseo_head":"\n\t\t\n\t\n\t\n\t\n\t\n\t\t\n\t\t\n\t\t\n\t\t\n\t\t\n\t\t\n\t\t\n\t\t\n\t\t\n\t\t\n\t\t\n\t\t