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Record W3101047343

Accelerator Testing of the General Antiparticle Spectrometer, a Novel Approach to Indirect Dark Matter Detection

2005· article· en· W3101047343 on OpenAlexaff
C.J. Hailey, T. Aramaki, William W. Craig, L. Fabris, F. Gahbauer, Jason E. Koglin, N. Madden, Kaya Mori, H.T. Yu, K.P. Ziock

Bibliographic record

VenueCERN Document Server (European Organization for Nuclear Research) · 2005
Typearticle
Languageen
FieldPhysics and Astronomy
TopicDark Matter and Cosmic Phenomena
Canadian institutionsCanadian Institute for Theoretical Astrophysics
FundersLawrence Livermore National Laboratory
KeywordsPhysicsAntiprotonDark matterNuclear physicsParticle physicsAntiparticleAnnihilationPionSpectrometerNeutralinoWIMPAstrophysicsProtonLeptonElectron
DOInot available

Abstract

fetched live from OpenAlex

We report on recent accelerator testing of a prototype general antiparticle spectrometer (GAPS). GAPS is a novel approach for indirect dark matter searches that exploits the antideuterons produced in neutralino-neutralino annihilations. GAPS captures these antideuterons into a target with the subsequent formation of exotic atoms. These exotic atoms decay with the emission of X-rays of precisely defined energy and a correlated pion signature from nuclear annihilation. This signature uniquely characterizes the antideuterons. Preliminary analysis of data from a prototype GAPS in an antiproton beam at the KEK accelerator in Japan has confirmed the multi-X-ray/pion star topology and indicated X-ray yields consistent with prior expectations. Moreover our success in utilizing solid rather than gas targets represents a significant simplification over our original approach and offers potential gains in sensitivity through reduced dead mass in the target area.

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)0.005
metaresearch head score (Gemma)0.002
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 score0.005
Threshold uncertainty score0.025

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0050.002
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0010.001
Science and technology studies0.0010.001
Scholarly communication0.0010.001
Open science0.0020.002
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0020.000

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 head0.032
GPT teacher head0.253
Teacher spread0.221 · 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

Citations54
Published2005
Admission routes1
Has abstractyes

Explore more

Same venueCERN Document Server (European Organization for Nuclear Research)Same topicDark Matter and Cosmic PhenomenaFrench-language works237,207