Portable mid-IR source around 3.7 μm based on temperature-tuned periodically poled lithium niobate (PPLN)
Bibliographic record
Abstract
In this paper, mid-IR light generation based on difference frequency generation (DFG) in a single piece of PPLN is proposed and studied. In the studies, a Yb doped fiber laser at 1.092 μm and a tunable laser around 1.55 μm were used. The output mid-IR laser with the wavelength tunable around 3.7 μm was generated. Since compact Yb doped fiber lasers at 1.092 μm and tunable semiconductor laser diodes around 1.55 μm are available on the market, the proposed mid-IR laser is potentially portable. Our simulations show that tunable mid-IR light as broad as 800 nm can be obtained from a single PPLN chip simply by tuning temperature (from 30 oC to 500 oC) and signal wavelength (from 1.48 μm to 1.62 μm).
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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 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 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".