Observation of anti-Stokes-fluorescence cooling in commercial Yb-doped silica fibers
Bibliographic record
Abstract
Optical cooling of Yb-doped silica fibers using anti-Stokes fluorescence (ASF) has emerged as a powerful technique to produce fiber lasers and amplifiers that generate no heat. This paradigm offers an unprecedented opportunity to engineer a new generation of devices with greater power and frequency stability, smaller size, weight, and power consumption, and greater ease of power scaling. While cooling in silica has been demonstrated so far only in custom compositions, here we show that commercial Yb-doped silica fibers can also be cooled by ASF. The best of seven tested fibers cooled by −85 mK from ambient. This is, however, significantly less than the current record (−250 mK) held by a custom aluminophosphosilicate fiber with a similar core area. We show that the commercial fibers do not cool as well because of a lower Yb concentration, higher quenching, and/or higher background absorption. This work establishes that commercial fibers can be used to carry out valuable research on ASF cooling and athermal lasers. It also quantifies the significant improvements in Yb concentration, quenching suppression, and background-absorption reduction achieved in these custom silica compositions. These fibers are expected to have a major impact on fiber lasers and amplifiers, whose performance also depends critically on these three metrics.
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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) | 0.000 | 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".