Agile multicasting based on cascaded χ^(2) nonlinearities in a step-chirped periodically poled lithium niobate
Bibliographic record
Abstract
We experimentally demonstrate the possibility of agile multicasting for wavelength division multiplexing (WDM) networks, of a single-channel to two and seven channels over the C band, also extendable to S and L bands. This is based on cascaded χ(2) nonlinear mixing processes, namely, second-harmonic generation (SHG)-sum-frequency generation (SFG) and difference-frequency generation (DFG) in a 20-mm-long step-chirped periodically poled lithium niobate crystal, specially designed and fabricated for a 28-nm-wide SH-SF bandwidth centered at around 1.55 μm. The multiple idlers are simultaneously tuned by detuning the pump wavelengths within the broad SH-SF bandwidth. By selectively tuning the pump wavelengths over less than 10 and 6 nm, respectively, multicasting into two and seven idlers is successfully achieved across ~70 WDM channels within the 50 GHz International Telecommunication Union grid spacing.
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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".