Compact intracavity mid-infrared upconversion detector – a systematic study
Bibliographic record
Abstract
Mid-IR light detection based on intracavity upconversion using a compact structure has been studied experimentally and theoretically. The mid-IR detector consists of a 47.5 mm MgO doped periodically poled lithium niobate crystal placed in a resonant cavity of a 1064 nm diode-pumped Nd:YVO 4 laser to enhance efficiency. The generated 1064 nm light is mixed with a mid-infrared source emitting at 3469 nm using an intracavity dichroic mirror. This produces short wave infrared 814.2 nm light via sum frequency generation (SFG). The upconverted light overlaps with the high responsivity for commercial off-the-shelf silicon photodetectors, enabling high speed and high sensitivity detection, surpassing direct mid-infrared detection. The lowest power detected was 150 nW, and the theoretical noise equivalent power for state-of-the-art Si detectors is 1.7⋅ f W/Hz. The free-running cavity requires no active stabilization, and the total packaged prototype size is 3.75 × 3.0 × 8.0 cm, which is relatively compact. An experimental power conversion efficiency of up to 36.0% is observed, which agrees well with theoretical simulations. A systematic theoretical study is performed to investigate the potential for further device optimization.
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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 | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 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".