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Record W2907807420 · doi:10.1103/physrevd.100.023001

Galactic Center gas clouds and novel bounds on ultralight dark photon, vector portal, strongly interacting, composite, and super-heavy dark matter

2019· article· en· W2907807420 on OpenAlexafffund
Amit Bhoonah, Joseph Bramante, Fatemeh Elahi, Sarah Schon

Bibliographic record

VenuePhysical review. D/Physical review. D. · 2019
Typearticle
Languageen
FieldPhysics and Astronomy
TopicDark Matter and Cosmic Phenomena
Canadian institutionsPerimeter InstituteArthur B. McDonald-Canadian Astroparticle Physics Research InstituteQueen's University
FundersNatural Sciences and Engineering Research Council of CanadaInstitut Périmètre de physique théoriqueHigh Energy PhysicsMinistero dello Sviluppo EconomicoNational Science FoundationGovernment of CanadaCERNKavli Institute for Theoretical Physics, University of California, Santa BarbaraIndustry CanadaOntario Ministry of Economic Development and InnovationAspen Center for Physics
KeywordsPhysicsDark matterMilky WayAstrophysicsGalaxyBaryonic dark matterGalactic CenterLight dark matterMetallicityCenter (category theory)Dark matter haloGalactic haloBaryonScalar field dark matterParticle physicsCosmologyHaloDark energy

Abstract

fetched live from OpenAlex

Cold gas clouds recently discovered hundreds of parsecs from the center of the Milky Way Galaxy have the potential to detect dark matter. With a detailed treatment of gas cloud microphysical interactions, we determine Galactic Center gas cloud temperatures, unbound electron abundances, atomic ionization fractions, heating rates, and cooling rates and find how these quantities vary with metallicity. Considering a number of different dark sector heating mechanisms, we set new bounds on ultralight dark photon dark matter for masses ${10}^{\ensuremath{-}22}\ensuremath{-}{10}^{\ensuremath{-}10}\text{ }\text{ }\mathrm{eV}$, vector portal dark matter coupled through a sub--mega electron volt mass boson, and up to $1{0}^{60}\text{ }\text{ }\mathrm{GeV}$ mass dark matter that interacts with baryons.

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: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.003
Threshold uncertainty score0.008

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0010.001
Science and technology studies0.0010.002
Scholarly communication0.0020.002
Open science0.0010.001
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 head0.009
GPT teacher head0.339
Teacher spread0.330 · 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 designObservational
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

Citations65
Published2019
Admission routes2
Has abstractyes

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