An Analytical Method for Evaluating the Robustness of Photonic Integrated Circuits
Bibliographic record
Abstract
We propose an efficient analytical method to evaluate the robustness of integrated photonic devices and circuits in the presence of independently-distributed random variations in the device parameters. By approximating the output of a photonic system in terms of a first or second-order Taylor series, we derive closed-form expressions for the mean and variance of the system output, which allow us to compute the one-standard-deviation (1-sigma) bounds on the expected system performance. Compared to other approaches for evaluating robustness, our method does not require computationally-intensive numerical simulations of the system output and can apply to any statistical distribution of parameter variations, including uniform and normal distributions. We demonstrate the method by analyzing the robustness of two coupled resonator systems: a fifth-order microring filter, and optical delay lines based on 1D Coupled Resonator Optical Waveguides and 2D Floquet topological microring lattice. Our method could provide a useful tool in the design and analysis of robust optical devices and 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 | 0.002 | 0.010 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.002 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| 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".