Improved Closed-Loop Slow-Light Temperature Sensor With Millidegree Resolution for Laser Cooling
Bibliographic record
Abstract
For applications such as laser cooling of doped fibers, where it is critical to measure accurately the temperature of a cooled fiber that is very close to room temperature, it is paramount to develop a reliable, very short (mm) fiber temperature sensor with millikelvin resolution and very little drift. We report a second generation of a unique slow-light fiber Bragg grating (FBG) temperature sensor that meets these stringent requirements. Experiments and modeling establish that its temperature response depends only on well-known material constants of the silica FBG and the response of the probe laser’s wavelength controller. The response is independent of the linewidth of the slow-light resonance, hence different FBGs and/or resonances have the exact same response. Examples of measured cooling in optically pumped Yb-doped fibers show that more reliable thermal contact with the cooled fiber is obtained by wrapping the FBG and the cooled fiber.
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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) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 0.001 |
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".