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Record W2114962824 · doi:10.1088/0004-637x/742/2/129

IMPACTS OF DARK STARS ON REIONIZATION AND SIGNATURES IN THE COSMIC MICROWAVE BACKGROUND

2011· article· en· W2114962824 on OpenAlexaff
Pat Scott, Aparna Venkatesan, Elinore Roebber, Paolo Gondolo, E. Pierpaoli, G. P. Holder

Bibliographic record

VenueThe Astrophysical Journal · 2011
Typearticle
Languageen
FieldPhysics and Astronomy
TopicRadio Astronomy Observations and Technology
Canadian institutionsMcGill University
Fundersnot available
KeywordsReionizationPhysicsAstrophysicsCosmic microwave backgroundStarsDark matterAstronomyAnisotropyRedshiftGalaxy

Abstract

fetched live from OpenAlex

We perform a detailed and systematic investigation of the possible impacts of dark stars on the reionization history of the universe, and its signatures in the cosmic microwave background (CMB). We compute hydrogen reionization histories, CMB optical depths, and anisotropy power spectra for a range of stellar populations including dark stars. If dark stars capture large amounts of dark matter (DM) via nuclear scattering, reionization can be substantially delayed, leading to decreases in the integrated optical depth to last scattering and large-scale power in the EE polarization power spectrum. Using the integrated optical depth observed by the Wilkinson Microwave Anistropy Probe seven-year mission, in our canonical reionization model we rule out the section of parameter space where dark stars with high scattering-induced capture rates tie up 90% of all the first star-forming baryons, and live for 250 Myr. When nuclear scattering delivers only moderate amounts of DM, reionization can instead be sped up slightly, modestly increasing the CMB optical depth. If dark stars do not obtain any DM via nuclear scattering, effects on reionization and the CMB are negligible. The effects of dark stars on reionization and its CMB markers can be largely mimicked or compensated for by changes in the existing parameters of reionization models, making dark stars difficult to disentangle from astrophysical uncertainties, but also widening the range of standard parameters in reionization models that can be made consistent with observations.

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 distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation 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 score0.815
Threshold uncertainty score0.218

Codex and Gemma teacher scores by category

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

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 head0.018
GPT teacher head0.229
Teacher spread0.212 · 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 teacher head, 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

Citations25
Published2011
Admission routes1
Has abstractyes

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