Chiral quantum optics in broken-symmetry and topological photonic crystal waveguides
Bibliographic record
Abstract
On-chip chiral quantum light-matter interfaces, which support directional interactions, provide a promising platform for efficient spin-photon coupling, nonreciprocal photonic elements, and quantum logic architectures. We present full-wave three-dimensional calculations to quantify the performance of conventional and topological photonic crystal waveguides as chiral emitter-photon interfaces. Specifically, the ability of these structures to support and enhance directional interactions while suppressing subsequent backscattering losses is quantified. Broken symmetry waveguides, such as the nontopological glide-plane waveguide and topological bearded interface waveguide are found to act as efficient chiral interfaces, with the topological waveguide modes allowing for operation at significantly higher Purcell enhancement factors. Finally, although all structures suffer from backscattering losses due to fabrication imperfections, these are found to be smaller at high enhancement factors for the topological waveguide. These reduced losses occur because the optical mode is pushed away from the air-dielectric interfaces where scattering occurs, and not because of any topological protection. These results are important to the understanding of light-matter interactions in topological photonic crystal and design of efficient, on-chip chiral quantum devices.
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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 | 0.001 |
| 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 | 0.000 | 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 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".