Experimental demonstration of robust nanophotonic devices optimized by topological inverse design with energy constraint
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Bibliographic record
Abstract
In this paper, we present the experimental results for integrated photonic devices optimized with an energy-constrained inverse design method. When this constraint is applied, optimizations are directed to solutions that contain the optical field inside the waveguide core medium, leading to more robust designs with relatively larger minimum feature size. We optimize three components: a mode converter (MC), a 1310 nm/1550 nm wavelength duplexer, and a three-channel C-band wavelength demultiplexer for coarse wavelength division multiplexing (CWDM) application with 50 nm channel spacing. The energy constraint leads to nearly binarized structures without applying independent binarization stage. It also reduces the appearance of small features. In the MC, well-binarized design, improved insertion loss, and cross talk are obtained as a result. Furthermore, the proposed constraint improves the robustness to fabrication imperfections as shown in the duplexer design. With energy constraint optimization, the corresponding spectrum shifts for the duplexer under <mml:math xmlns:mml="http://www.w3.org/1998/Math/MathML" display="inline" id="m1"> <mml:mrow> <mml:mo form="prefix">±</mml:mo> <mml:mn>10</mml:mn> <mml:mtext> </mml:mtext> <mml:mi>nm</mml:mi> </mml:mrow> </mml:math> dimensional variations are reduced from 105 nm to 55 nm and from 72 nm to 60 nm for the 1310 nm and 1550 nm channel, respectively. In the CWDM demultiplexer, robustness toward <mml:math xmlns:mml="http://www.w3.org/1998/Math/MathML" display="inline" id="m2"> <mml:mrow> <mml:mo form="prefix">±</mml:mo> <mml:mn>10</mml:mn> <mml:mtext> </mml:mtext> <mml:mi>nm</mml:mi> </mml:mrow> </mml:math> fabrication error is improved by a factor of 2. The introduction of the energy constraint into topological optimization demonstrates computational gain with better-performing designs.
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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 | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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