Robust Programmable Photonic Circuits Based on a Floquet-Lieb Topological Waveguide Lattice
Bibliographic record
Abstract
We propose a robust programmable photonic integrated circuit platform based on a 2D Floquet-Lieb topological lattice. Reconfigurable topological photonic lattices typically require creating topologically distinct domains to guide interface modes, which requires a large number of coupling elements to be tuned and severely constraints the realizable circuit configurations. Here by taking advantage of the natural hopping sequence of light in the Floquet-Lieb microring lattice, we show that line defect modes and flat-band resonance modes can be excited by tuning only selective coupling elements, thus enabling efficient light steering and localization in the lattice interior. We show how basic circuit elements such as waveguide bends, splitters, combiners, and resonators, can be formed in the lattice, which can be used to construct general photonic integrated circuits. Compared to conventional topologically-trivial waveguide meshes, our topological photonic lattice requires fewer tuning elements while offering better tolerance to defects and random variations due to topological protection. The proposed topological lattice can thus provide an efficient and robust platform for implementing classical and quantum integrated photonic circuits.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| 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 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 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 source (direct Gemma or distilled Codex), 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".