PreFab is a virtual nanofabrication environment that leverages deep learning and computer vision to predict and correct for structural variations in integrated photonic devices during nanofabrication.
PreFab predicts process-induced structural variations, including corner rounding, loss of small lines and islands, filling of narrow holes and channels, sidewall angle deviations, and stochastic effects. This allows designers to rapidly prototype and evaluate expected performance pre-fabrication.
PreFab corrects device designs to ensure that the fabricated outcome closely matches the intended specifications. This minimizes structural variations and reduces performance discrepancies between simulations and actual experiments.
Each photonic nanofabrication process requires unique models, which are regularly updated with the latest data. The current models include (see the full list in docs/models.md
):
Foundry | Process | Latest Version | Latest Dataset | Model Name |
---|---|---|---|---|
ANT | NanoSOI | ANF1 (May 6 2024) | d10 (Jun 8 2024) | ANT_NanoSOI_ANF1_d10 |
ANT | SiN | ANF1 (May 6 2024) | d1 (Jan 31 2024) | ANT_SiN_ANF1_d1 |
Generic | DUV-SOI | ANF1 (May 6 2024) | d0 (Jul 30 2024) | generic_DUV_SOI_ANF1_d0 |
New models are to be regularly added. Usage may change. For additional foundry and process models, feel free to contact us or raise an issue.
Install PreFab via pip:
pip install prefab
Or clone the repository and install in development mode:
git clone https://github.com/PreFab-Photonics/PreFab.git
cd PreFab
pip install -e .
Before you can make PreFab requests, you will need to create an account.
To link your account, you will need an token. You can do this by running the following command in your terminal. This will open a browser window where you can log in and authenticate your token.
python3 -m prefab setup
Visit /docs/examples
or our docs to get started with your first predictions.
PreFab models are hosted on a serverless cloud platform. Please keep in mind:
- 🐢 Default CPU inference may be slower.
- 🥶 The first prediction using optional GPU inference may take longer due to cold start server loading. Subsequent predictions will be faster.
- 😊 Please be considerate of usage. Start with small tasks and limit usage during the initial stages. Thank you!
This project is licensed under the LGPL-2.1 license. © 2024 PreFab Photonics.