Phase Matching for Difference Frequency Generation in GaAs Via an Artificial Birefringence Technique Using Silver Nanowires
Bibliographic record
Abstract
The lack of anisotropic properties in GaAs prevents the use of birefringence as a phase matching technique in three-wave mixing with GaAs as a nonlinear medium. When metallic nanowires are embedded in GaAs, the composite structure is characterized as a metamaterial with anisotropic properties, if the separation distance between the nanowires is less than the wavelengths of the mixed waves. The effective permittivity is used to investigate this metamaterial structure with its anisotropic properties theoretically in terms of phase matching for difference frequency generation. The resultant difference frequencies, which are in the mid-infrared region, are broadly tunable from 2.8 to 11 μm. This tuning is performed by varying the pump and the signal wavelengths in the range between 1 to 2 μm. The losses of the structure due to absorption are included using the transfer matrix method.
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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 | 0.000 | 0.000 |
| 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".