Optimizing the chiral Purcell factor for unidirectional single-photon emitters in topological photonic crystal waveguides using inverse design
Bibliographic record
Abstract
We present an inverse-design approach to significantly improve the figures of merit for chiral photonics with quantum emitters in topological photonic crystal slab waveguides. Beginning with a topological waveguide mode with a group index of approximately 10 and a maximum forward or backward Purcell factor at a chiral point of less than 0.5, we perform optimizations of the directional Purcell factor. We use a fully three-dimensional guided-mode expansion method to efficiently calculate waveguide band-dispersion properties and modes, while automatic differentiation is employed to calculate the gradient of objective functions. We present two example improved designs: (i) a topological mode with an accessible group index of approximately 30 and a maximum unidirectional Purcell factor at a chiral point greater than 4.5, representing a nearly 10-fold improvement to the Purcell factor, and (ii) a slow-light mode well away from the Brillouin-zone edge with a group index greater than 350 and a maximum unidirectional Purcell factor at a chiral point greater than 45.
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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 | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.000 | 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".