Picosecond-pulse wavelength conversion based on cascaded sum-frequency generation/difference-frequency generation in PPLN waveguides
Bibliographic record
Abstract
The wavelength conversion technique based on the cascaded sum-frequency generation/difference-frequency generation (SFG/DFG) process has an advantage of no pump occupation in the communication band, compared to the mostly adopted second-harmonic generation (SHG)/DFG process. In the SFG/DFG-based wavelength conversion, two pump waves and a signal wave are required. The pulsed wave, as a carrier of information, can be applied to the signal or one of the two pump waves. Though the converted wave has the form of pulses, its temporal and spectral characteristics are dependent on the arrangement of the input pulsed wave. Based on numerical simulation, the temporal and spectral characteristics of the pump, signal, converted and sum-frequency waves during their propagations in PPLN waveguides are systematically investigated in this work. In particular, temporal pulse shapes, optical spectra and conversion efficiency are emphasized and compared when picosecond pulse trains are used as the signal and pump waves, respectively.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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".