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Record W7132705252

Fires in the deep

2024· article· en· W7132705252 on OpenAlexfundno aff
D. A. Kann, N. E. White, S. R. Oates, Andrea Melandri, M. (Miroslav) Jelínek, A. De Ugarte Postigo, A. J. Levan, Antonio Martin-Carrillo, Andreja Gomboc

Bibliographic record

VenueRUNG · 2024
Typearticle
Languageen
FieldEngineering
TopicFire dynamics and safety research
Canadian institutionsnot available
FundersBrookhaven National LaboratoryPlanetary Science DivisionSmithsonian Astrophysical ObservatoryInstituto de Astrofísica de CanariasOffice of ScienceMax-Planck-Institut für AstronomieLawrence Berkeley National LaboratoryMinistry of Science and ICT, South KoreaEötvös Loránd TudományegyetemNational Central UniversityNational Research Foundation of KoreaGordon and Betty Moore FoundationQueen's University BelfastDurham UniversityYork UniversityBanco Bilbao Vizcaya ArgentariaKorea Astronomy and Space Science InstituteSpace Telescope Science InstituteNational Research FoundationOhio State UniversityUniversity of Texas at AustinCarnegie Mellon UniversityUniversity of ArizonaLos Alamos National LaboratoryCollege of Engineering, Michigan State UniversityUniversity of WashingtonPrinceton UniversityAlfred P. Sloan FoundationJohns Hopkins UniversityInstituto de Astrofísica de AndalucíaQueen's UniversityHarvard UniversityMinisterio de Economía y CompetitividadUniversity of LeicesterU.S. Department of EnergySmithsonian InstitutionNational Aeronautics and Space AdministrationNew Mexico State UniversityUniversity of PortsmouthVanderbilt UniversityScience Mission DirectorateYale UniversityFundación BBVANational Science Foundation
KeywordsRedshiftGamma-ray burstGalaxyTelescopeLuminosityJames Webb Space TelescopeBrightnessSpitzer Space TelescopeUniverse
DOInot available

Abstract

fetched live from OpenAlex

Context.Gamma-ray bursts (GRBs) are ideal probes of the Universe at high redshift (z), pinpointing the locations of the earliest star-forming galaxies and providing bright backlights with simple featureless power-law spectra that can be used to spectrally fingerprint the intergalactic medium and host galaxy during the period of reionization.Future missions such as Gamow Explorer (hereafter Gamow) are being proposed to unlock this potential by increasing the rate of identification of high-z (z > 5) GRBs in order to rapidly trigger observations from 6 -10 m ground telescopes, the James Webb Space Telescope (JWST), and the upcoming Extremely Large Telescopes (ELTs).Aims.Gamow was proposed to the NASA 2021 Medium-Class Explorer (MIDEX) program as a fast-slewing satellite featuring a wide-field lobster-eye X-ray telescope (LEXT) to detect and localize GRBs with arcminute accuracy, and a narrow-field multi-channel photo-z infrared telescope (PIRT) to measure their photometric redshifts for > 80% of the LEXT detections using the Lyman-α dropout technique.We use a large sample of observed GRB afterglows to derive the PIRT sensitivity requirement.Methods.We compiled a complete sample of GRB optical-near-infrared (optical-NIR) afterglows from 2008 to 2021, adding a total of 66 new afterglows to our earlier sample, including all known high-z GRB afterglows.This sample is expanded with over 2837 unpublished data points for 40 of these GRBs.We performed full light-curve and spectral-energy-distribution analyses of these afterglows to derive their true luminosity at very early times.We compared the high-z sample to the comparison sample at lower redshifts.For all the light curves, where possible, we determined the brightness at the time of the initial finding chart of Gamow, at different high redshifts and in different NIR bands.This was validated using a theoretical approach to predicting the afterglow brightness.We then followed the evolution of the luminosity to predict requirements for groundand space-based follow-up.Finally, we discuss the potential biases between known GRB afterglow samples and those to be detected by Gamow.Results.We find that the luminosity distribution of high-z GRB afterglows is comparable to those at lower redshift, and we therefore are able to use the afterglows of lower-z GRBs as proxies for those at high z.We find that a PIRT sensitivity of 15 µJy (21 mag AB) in a 500 s exposure simultaneously in five NIR bands within 1000s of the GRB trigger will meet the Gamow mission requirements.Depending on the z and NIR band, we find that between 75% and 85% of all afterglows at z > 5 will be recovered by Gamow at 5σ detection significance, allowing the determination of a robust photo-z.As a check for possible observational biases and selection effects, we compared the results with those obtained through population-synthesis models, and find them to be consistent. Conclusions.Gamow and other high-z GRB missions will be capable of using a relatively modest 0.3m onboard NIR photo-z telescope to rapidly identify and report high-z GRBs for further follow-up by larger facilities, opening a new window onto the era of reionization and the high-redshift Universe.

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)0.003
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.060
Threshold uncertainty score0.200

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.003
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0010.001
Scholarly communication0.0040.004
Open science0.0010.003
Research integrity0.0010.002
Insufficient payload (model declined to judge)0.0600.015

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 head0.007
GPT teacher head0.237
Teacher spread0.230 · 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 designNot applicable
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

Citations0
Published2024
Admission routes1
Has abstractyes

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