High-power fiber lasers with integrated rare-earth optical cooler
Bibliographic record
Abstract
High-power lasers (Raman and traditional solid-state) suffer from heat generated by the quantum defect, which deteriorates their performance. The radiation-balanced technique was proposed to solve the problem in the case of solid-state lasers, and the intrinsic heat-mitigation technique, which relies on coherent anti-Stokes Raman scattering (CARS) was proposed to solve the problem of heat generation in the high power Raman laser. Unfortunately radiated energy increases only linearly with the length of the laser medium in both schemes. We propose a radically new approach to solve the problem of heat generation in lasers. We have considered athermal fiber lasers, where rare-earth (RE) ions based refrigeration sources are incorporated in the body of the devices. This new technique, which has been developed for Raman and traditional solid-state lasers, ensures the exponential growth of radiation along the laser medium and provides almost athermal operation.
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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 | 0.000 | 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 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".