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Record W4306773442 · doi:10.1038/s41467-022-33913-6

Search for Dark Matter Axions with CAST-CAPP

2022· article· en· W4306773442 on OpenAlexafffund
C. M. Adair, K. Altenmüller, V. Anastassopoulos, S. Arguedas Cuendis, J. Baier, K. Barth, А. С. Белов, D. Bozicevic, H. Bräuninger, G. Cantatore, F. Caspers, J. Castel, S. A. Çetin, Woohyun Chung, Hyoungsoon Choi, J. Choi, T. Dafní, M. Davenport, A. Dermenev, K. Desch, Babette Döbrich, H. Fischer, W. Funk, J. Galán, A. Gardikiotis, S. Gninenko, J. Golm, M. D. Hasinoff, D. H. H. Hoffmann, D. Díez Ibáñez, I.G. Irastorza, K. Jakovčić, J. Kamiński, M. Karuza, C. Krieger, Çağlar Kutlu, B. Lakić, Jean‐Paul Laurent, Jhinhwan Lee, Shyh‐Yuan Lee, G. Luzón, C. Malbrunot, C. Margalejo, Marios Maroudas, L. Miceli, H. Mirallas, L. Obis, A. Özbey, T. Papaevangelou, M. J. Pivovaroff, M. Rosu, J. Ruz, Elisa Ruiz-Chóliz, Sebastian Schmidt, M. Schümann, Yannis K. Semertzidis, S. K. Solanki, L. Stewart, I. Tsagris, T. Vafeiadis, Julia K. Vogel, Mario Vretenar, SungWoo Youn, K. Zioutas

Bibliographic record

VenueNature Communications · 2022
Typearticle
Languageen
FieldPhysics and Astronomy
TopicDark Matter and Cosmic Phenomena
Canadian institutionsUniversity of British Columbia
FundersLawrence Livermore National LaboratoryAgencia Estatal de InvestigaciónInstitute for Basic ScienceEuropean Social FundU.S. Department of EnergyState Scholarships FoundationNatural Sciences and Engineering Research Council of CanadaEuropean CommissionCERNEuropean Regional Development FundDeutsche Forschungsgemeinschaft
KeywordsDark matterAxionComputational biologyPhysicsBiologyAstrophysics

Abstract

fetched live from OpenAlex

Abstract The CAST-CAPP axion haloscope, operating at CERN inside the CAST dipole magnet, has searched for axions in the 19.74 μ eV to 22.47 μ eV mass range. The detection concept follows the Sikivie haloscope principle, where Dark Matter axions convert into photons within a resonator immersed in a magnetic field. The CAST-CAPP resonator is an array of four individual rectangular cavities inserted in a strong dipole magnet, phase-matched to maximize the detection sensitivity. Here we report on the data acquired for 4124 h from 2019 to 2021. Each cavity is equipped with a fast frequency tuning mechanism of 10 MHz/ min between 4.774 GHz and 5.434 GHz. In the present work, we exclude axion-photon couplings for virialized galactic axions down to g a γ γ = 8 × 10 −14 GeV −1 at the 90% confidence level. The here implemented phase-matching technique also allows for future large-scale upgrades.

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 imitation

Not 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.

metaresearch head score (Codex)0.001
metaresearch head score (Gemma)0.001
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Bench or experimental · Consensus signal: Bench or experimental
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.003
Threshold uncertainty score0.011

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.001
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0030.000

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.

Opus teacher head0.016
GPT teacher head0.283
Teacher spread0.267 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designBench or experimental
Domainnot available
GenreEmpirical

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".

Quick stats

Citations88
Published2022
Admission routes2
Has abstractyes

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