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Record W4285046073 · doi:10.3847/1538-4357/ac746b

Probing Population III Initial Mass Functions with He ii/Hα Intensity Mapping

2022· article· en· W4285046073 on OpenAlexaff
Jasmine Parsons, Lluís Mas-Ribas, Guochao Sun, Tzu‐Ching Chang, Michael O. Gonzalez, Richard H. Mebane

Bibliographic record

VenueThe Astrophysical Journal · 2022
Typearticle
Languageen
FieldPhysics and Astronomy
TopicGalaxies: Formation, Evolution, Phenomena
Canadian institutionsMcGill University
Fundersnot available
KeywordsPhysicsAstrophysicsStarsPopulationStar formationRedshiftGalaxyIntensity mappingInitial mass functionLine (geometry)H-alphaSpectral lineEmission spectrumAstronomy

Abstract

fetched live from OpenAlex

Abstract We demonstrate the potential of line-intensity mapping to place constraints on the initial mass function (IMF) of Population III stars via measurements of the mean He ii 1640 Å/Hα line-intensity ratio. We extend the 21cmFAST code with modern high-redshift galaxy-formation and photoionization models, and estimate the line emission from Population II and Population III galaxies at redshifts 5 ≤ z ≤ 20. In our models, mean ratio values of He ii/H α ≳ 0.1 indicate top-heavy Population III IMFs with stars of several hundred solar masses, reached at z ≳ 10 when Population III stars dominate star formation. A next-generation space mission with capabilities moderately superior to those of CDIM will be able to probe this scenario by measuring the He ii and Hα fluctuation power spectrum signals and their cross-correlation at high significance up to z ∼ 20. Moreover, regardless of the IMF, a ratio value of He ii/Hα ≲ 0.01 indicates low Population III star formation and, therefore, it signals the end of the period dominated by this stellar population. However, a detection of the corresponding He ii power spectrum may be only possible for top-heavy Population III IMFs or through cross-correlation with the stronger Hα signal. Finally, ratio values of 0.01 ≲ He ii/Hα ≲ 0.1 are complex to interpret because they can be driven by several competing effects. We discuss how various measurements at different redshifts and the combination of the line-intensity ratio with other probes can assist in constraining the Population III IMF in this case.

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)0.001
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 score0.001
Threshold uncertainty score0.004

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0010.000

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 head0.011
GPT teacher head0.205
Teacher spread0.194 · 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

Citations20
Published2022
Admission routes1
Has abstractyes

Explore more

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