Fabrication-aware inverse design with shape optimization for photonic integrated circuits
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
Inverse design (ID) is a computational method that systematically explores a design space to find optimal device geometries based on specific performance criteria. In silicon photonics, ID often generates design features that degrade significantly due to the fabrication process, limiting the applicability of these devices in scalable fabrication. We demonstrate a solution to this performance degradation through fabrication-aware inverse design (FAID), integrating lithography models for deep-ultraviolet (DUV) lithography and electron-beam lithography (EBL) into the shape optimization approach of ID. A Y-branch and a subwavelength grating (SWG)-to-strip converter were generated and fabricated with this new, to the best of our knowledge, approach. Simulation and measurement results verify that FAID yields devices with up to 0.7 dB lower insertion loss per device. The modified workflow enables designers to use ID to generate devices that adjust for process bias predicted by lithography models.
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Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it