Earth as a transducer for axion dark-matter detection
Bibliographic record
Abstract
We demonstrate that ultralight axion dark matter with a coupling to photons induces an oscillating global terrestrial magnetic-field signal in the presence of the background geomagnetic field of the Earth. This signal is similar in structure to that of dark-photon dark matter that was recently pointed out and searched for in [Fedderke et al. Phys. Rev. D 104, 075023 (2021)] and [Fedderke et al. Phys. Rev. D 104, 095032 (2021)]. It has a global vectorial pattern fixed by the Earth's geomagnetic field, is temporally coherent on long timescales, and has a frequency set by the axion mass ${m}_{a}$. In this work, we both compute the detailed signal pattern and undertake a search for this signal in magnetometer network data maintained by the SuperMAG Collaboration. Our analysis identifies no strong evidence for an axion dark-matter signal in the axion mass range $2\ifmmode\times\else\texttimes\fi{}{10}^{\ensuremath{-}18}\text{ }\text{ }\mathrm{eV}\ensuremath{\lesssim}{m}_{a}\ensuremath{\lesssim}7\ifmmode\times\else\texttimes\fi{}{10}^{\ensuremath{-}17}\text{ }\text{ }\mathrm{eV}$. Assuming the axion is all of the dark matter, we place constraints on the axion-photon coupling ${g}_{a\ensuremath{\gamma}}$ in the same mass range; at their strongest, for masses $3\ifmmode\times\else\texttimes\fi{}{10}^{\ensuremath{-}17}\text{ }\text{ }\mathrm{eV}\ensuremath{\lesssim}{m}_{a}\ensuremath{\lesssim}4\ifmmode\times\else\texttimes\fi{}{10}^{\ensuremath{-}17}\text{ }\text{ }\mathrm{eV}$, these constraints are comparable to those obtained by the CAST helioscope.
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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 | 0.001 |
| 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 | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.004 | 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".