In-situ fiber temperature sensor for anti-Stokes cooling measurements in doped fibers
Bibliographic record
Abstract
The experimental study of cooling by anti-Stokes fluorescence in a fiber or a radiation-balanced fiber laser necessitates the development of a sensor that can measure the temperature of the fiber core with an excellent temperature and spatial resolution, a large dynamic range, a small drift, a fast response, and a low absorptive loss. We report an in-situ slow-light fiber sensor written directly in a Yb-doped silica fiber using a femtosecond laser. The sensor has a spatial resolution of 6.5 mm, an excellent measured temperature resolution of 0.9 m°C/√Hz, and a measured drift as low as 20 m°C/min. One of the grating’s slow-light resonances is interrogated with a tunable 1.55-μm laser to measure the temperature-induced shift in the resonance wavelength when the fiber is optically pumped. The laser frequency is also modulated at 30 kHz to greatly reduce the detection noise. The sensor was pumped with 0.58 mW from a 1020-nm laser and measured a positive temperature change of 0.33 °C. The dominant source of heating is shown to be likely the photodarkening loss induced in the Yb-doped fiber when the FBG was written. The total FBG loss is predicted to be ~24 m<sup>-1</sup> at 1020 nm and expected to reduce after annealing. Projections indicate that if the loss of the rare-earth doped FBG can be decreased to the level of the loss observed in slow-light FBGs written in SMF-28 fibers, these sensors can be used to measure ASF cooling.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| 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 teacher head, 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".