Bibliographic record
Abstract
Laser cooling of solids, sometimes also known as optical refrigeration, is a fast developing area of optical science, investigating the interaction of light with condensed matter. Apart from being of fundamental scientific interest, this topic addresses a very important practical issue: design and construction of laser pumped solid-state cryocoolers, which are compact, free from mechanical vibrations, moving parts, fluids and can cause only low electromagnetic interference in the cooled area. The optical cryocooler has a broad area of applications such as in the development of magnetometers for geophysical sensors, in biomedical sensing and can be beneficial for satellite instrumentations and small sensors, where compactness and the lack of vibrations are very important. Simply, a laser cooler works on the conversion of low energy pump photons into high-energy anti-Stokes fluorescence photons by extracting some of the phonons (heat energy) in a material. That is, the process of laser cooling of solids is based on anti-Stokes fluorescence also known as luminescence upconversion, when light quanta in the red tail of the absorption spectrum are absorbed from a pump laser, and blue-shifted photons are spontaneously emitted. The extra energy extracted from the solid-state lattice in the form of the phonons is the quanta of vibrational energy which generates heat. The idea to cool solids with anti-Stokes fluorescence was proposed in 1929 by Peter Pringsheim and first demonstrated experimentally by Epstein's research team in 1995. In 1999, Steven Bowman proposed to use the optical refrigeration by anti-Stokes fluorescence within the laser medium to balance the heat generated by the Stokes shifted stimulated emission in a high-power solid-state bulk laser. Such a laser without internal heating named radiation-balanced or athermal laser was experimentally demonstrated for the first time in 2002. At the present time laser cooling of solids can be largely divided into three main areas: laser cooling of rare-earth doped solids, laser cooling in semiconductors and radiation-balanced lasers. All three areas are very interesting and important and will be considered in this paper.
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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 | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.007 | 0.002 |
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".