Monolithic Photonics Using Second-Order Optical Nonlinearities in Multilayer-Core Bragg Reflection Waveguides
Bibliographic record
Abstract
Recent advancements in phase-matching second-order nonlinear processes by using matching-layer-enhanced Bragg reflection waveguides (ML-BRWs) in AlxGa1-xAs material system are discussed. The limitations on the choice of the AlxGa1-xAs layers for applications that require high pump power operation are highlighted. Multilayer-core ML-BRWs are proposed as a new waveguide design with relaxed constraints over the choice of the AlxGa1-xAs layers composition. The tradeoffs associated with material bandgap on the efficiency of second-order nonlinear processes are examined by using this novel structure. The interplay among the various factors, including the nonlinear overlap factor, the effective second-order nonlinearity, and the third-order nonlinear effects result in the presence of an optimum detuning of the core bandgap from the operating wavelength for maximum conversion efficiency. Two different wafer structures are examined by using second-harmonic generation to elucidate these tradeoffs. The conversion efficiency is examined by using 30-ps, 2-ps, and 250-fs pulses at various pump average power levels.
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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 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 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".