Search for Sub-eV Mass Solar Axions by the CERN Axion Solar Telescope with<mml:math xmlns:mml="http://www.w3.org/1998/Math/MathML" display="inline"><mml:mmultiscripts><mml:mi>He</mml:mi><mml:mprescripts/><mml:none/><mml:mn>3</mml:mn></mml:mmultiscripts></mml:math>Buffer Gas
Bibliographic record
Abstract
The CERN Axion Solar Telescope (CAST) has extended its search for solar axions by using $^{3}\mathrm{He}$ as a buffer gas. At $T=1.8\text{ }\text{ }\mathrm{K}$ this allows for larger pressure settings and hence sensitivity to higher axion masses than our previous measurements with $^{4}\mathrm{He}$. With about 1 h of data taking at each of 252 different pressure settings we have scanned the axion mass range $0.39\text{ }\text{ }\mathrm{eV}\ensuremath{\lesssim}{m}_{a}\ensuremath{\lesssim}0.64\text{ }\text{ }\mathrm{eV}$. From the absence of excess x rays when the magnet was pointing to the Sun we set a typical upper limit on the axion-photon coupling of ${g}_{a\ensuremath{\gamma}}\ensuremath{\lesssim}2.3\ifmmode\times\else\texttimes\fi{}{10}^{\ensuremath{-}10}\text{ }\text{ }{\mathrm{GeV}}^{\ensuremath{-}1}$ at 95% C.L., the exact value depending on the pressure setting. Kim-Shifman-Vainshtein-Zakharov axions are excluded at the upper end of our mass range, the first time ever for any solar axion search. In the future we will extend our search to ${m}_{a}\ensuremath{\lesssim}1.15\text{ }\text{ }\mathrm{eV}$, comfortably overlapping with cosmological hot dark matter bounds.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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) | 0.000 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.011 | 0.004 |
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".