Topological inverse design of nanophotonic devices with energy constraint
Why this work is in the frame
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Bibliographic record
Abstract
In this paper, we introduce an energy constraint to improve topology-based inverse design. Current methods typically place the constraints solely on the device geometry and require many optimization iterations to converge to a manufacturable solution. In our approach the energy constraint directs the optimization process to solutions that best contain the optical field inside the waveguide core medium, leading to more robust designs with relatively larger minimum feature size. To validate our method, we optimize two components: a mode converter (MC) and a wavelength demultiplexer. In the MC, the energy constraint leads to nearly binarized structures without applying independent binarization stage. In the demultiplexer, it also reduces the appearance of small features. Furthermore, the proposed constraint improves the robustness to fabrication imperfections as shown in demultiplexer design. With energy constraint optimization, the corresponding spectrum shifts under ±10 nm dimensional variations are reduced by 17% to 30%. The proposed constraint is unique in simultaneously taking both geometry and electric field into account, opening the door to new ideas and insights to further improve the computationally intensive topology-based optimization process of nanophotonic devices.
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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) | 0.001 | 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