Harnessing second-order optical nonlinearities in compound semiconductors
Bibliographic record
Abstract
An overview of recent advances in exact phase matching technologies of second order nonlinear optical processes in compound semiconductors is reported. The technique used utilizes dispersion engineering in Bragg reflection waveguides (BRWs) or 1-dimensoinal photonic bandgap structures to achieve phase matching between the interacting waves. One of its distinguishing features in comparison to other techniques is that it does not involve any demanding technological steps such as oxidation, nor does it rely on periodic modulation of the optical properties of the materials used in the propagation direction. This in turn provides phase matching with significantly lower optical losses in comparison to other techniques. Nonlinear conversion efficiency matching what is achievable in periodically poled lithium niobate is obtained for ridge BRWs fabricated in GaAs/AlGaAs. Most notable applications that would benefit from integrable ultrafast second order optical nonlinearities include monolithically integrated optical parametric oscillators, correlated photon pair sources and monolithic tunable frequency conversion elements.
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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 | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 0.001 |
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".