Inverse design of broadband and lossless topological photonic crystal waveguide modes
Bibliographic record
Abstract
Photonic crystal slab (PCS) waveguides can be engineered to control the propagation of light, finding a variety of applications in optical sensing, nonlinear optics and quantum optics. However, traditional PCS waveguides suffer from disorder-induced backscattering which is especially severe in the slow-light regime. Topological PCS waveguides can support propagating edge-state modes which are possibly more robust against some defects. Here we apply inverse design techniques to modify a state-of-the-art topological PCS waveguide, to obtain a significant (more than 100%) improvement to the operational bandwidth of a lossless waveguide mode. We then optimize the new design's group velocity curve, obtaining two new designs, one with a group index of 28 over a bandwidth ▵<i>ω/ω</i>=1:5% and in the other a maximum group index greater than 200 away from the mode edge. We use an efficient, semi-analytic, computation method, the guided mode expansion method, to calculate photonic band structures and automatic differentiation to calculate objective function gradients. Combining this with a physically intuitive shape parameterization, the method, while initially constraining the optimization to solutions resembling the initial design, is efficient and flexible. This method can be applied to quickly optimize PCS devices towards a large variety of target figures of merit.
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How this classification was reachedexpand
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 itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".