Dusandinho/PreFab
Prediction of fabrication variations in integrated photonic devices using deep learning
This project helps integrated photonics designers understand how their device designs will be affected by real-world manufacturing imperfections. You input your proposed photonic device layout, and it outputs a predicted, altered design reflecting common fabrication variations. Photonics engineers and researchers can then quickly adjust their designs before committing to expensive physical fabrication.
No commits in the last 6 months.
Use this if you need to quickly simulate and correct for manufacturing variations like corner rounding or feature filling in your integrated photonic device designs.
Not ideal if you are looking for a general-purpose simulation tool for photonic devices that does not focus specifically on fabrication variation prediction.
Stars
30
Forks
9
Language
Python
License
GPL-3.0
Category
Last pushed
Mar 02, 2023
Commits (30d)
0
Get this data via API
curl "https://pt-edge.onrender.com/api/v1/quality/ml-frameworks/Dusandinho/PreFab"
Open to everyone — 100 requests/day, no key needed. Get a free key for 1,000/day.
Higher-rated alternatives
kaanaksit/odak
Scientific computing library for optics, computer graphics and visual perception.
NVIDIA/torch-harmonics
Differentiable signal processing on the sphere for PyTorch
PreFab-Photonics/PreFab
Artificial nanofabrication of integrated photonic circuits using deep learning
MatthewFilipovich/torchoptics
Differentiable wave optics simulation library built on PyTorch
artificial-scientist-lab/XLuminA
XLuminA, a highly-efficient, auto-differentiating discovery framework for super-resolution microscopy.