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Record W2046448011 · doi:10.1093/mnras/stt2392

The imprint of warm dark matter on the cosmological 21-cm signal

2014· article· en· W2046448011 on OpenAlexafffund
Michael Sitwell, Andrei Mesinger, Yin-Zhe Ma, Kris Sigurdson

Bibliographic record

VenueMonthly Notices of the Royal Astronomical Society · 2014
Typearticle
Languageen
FieldPhysics and Astronomy
TopicRadio Astronomy Observations and Technology
Canadian institutionsUniversity of British Columbia
FundersNatural Sciences and Engineering Research Council of CanadaAspen Center for Physics
KeywordsPhysicsReionizationAstrophysicsDark matterWarm dark matterMatter power spectrumCosmologySIGNAL (programming language)HaloDark AgesStar formationOptical depthGalaxyRedshiftScalar field dark matterDark energy

Abstract

fetched live from OpenAlex

We investigate the effects of warm dark matter (WDM) on the cosmic 21-cm signal. If dark matter exists as WDM instead of cold dark matter (CDM), its non-negligible velocities can inhibit the formation of low-mass haloes that normally form first in CDM models, therefore delaying star formation. The absence of early sources delays the build-up of UV and X-ray backgrounds that affect the 21-cm radiation signal produced by neutral hydrogen. With use of the 21CMFAST code, we demonstrate that the pre-reionization 21-cm signal can be changed significantly in WDM models with a free-streaming length equivalent to that of a thermal relic with mass mX of up to ∼10–20 keV. In such a WDM cosmology, the 21-cm signal traces the growth of more massive haloes, resulting in a delay of the 21-cm absorption signature and followed by accelerated X-ray heating. CDM models where astrophysical sources have a suppressed photon-production efficiency can delay the 21-cm signal as well, although its subsequent evolution is not as rapid as compared to WDM. This motivates using the gradient of the global 21-cm signal to differentiate between some CDM and WDM models. Finally, we show that the degeneracy between the astrophysics and mX can be broken with the 21-cm power spectrum, as WDM models should have a bias-induced excess of power on large scales. This boost in power should be detectable with current interferometers for models with mX ≲ 3 keV, while next-generation instruments will easily be able to measure this difference for all relevant WDM models.

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)0.000
metaresearch head score (Gemma)0.003
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Simulation or modeling · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.002
Threshold uncertainty score0.007

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.003
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.000
Science and technology studies0.0000.000
Scholarly communication0.0010.001
Open science0.0000.001
Research integrity0.0000.001
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 head0.008
GPT teacher head0.194
Teacher spread0.186 · 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 designSimulation or modeling
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

Citations114
Published2014
Admission routes2
Has abstractyes

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