MétaCan
Menu
← Back to cohort
Record W3005223778 · doi:10.1051/0004-6361/202037665

A robust two-parameter description of the stellar profile of elliptical galaxies

2020· article· en· W3005223778 on OpenAlexfundno aff

Bibliographic record

VenueAstronomy and Astrophysics · 2020
Typearticle
Languageen
FieldPhysics and Astronomy
TopicGalaxies: Formation, Evolution, Phenomena
Canadian institutionsnot available
FundersLawrence Berkeley National LaboratoryJapan Society for the Promotion of ScienceScience and Technology Facilities CouncilToray Science FoundationOhio State UniversityHigh Energy Accelerator Research OrganizationNew Mexico State UniversityNational Astronomical Observatory of JapanYork UniversityOffice of SciencePrinceton UniversityAlfred P. Sloan FoundationUniversity of WashingtonCollege of Engineering, Michigan State UniversityJohns Hopkins UniversityCarnegie Mellon UniversityMinistry of Education, Culture, Sports, Science and TechnologyHarvard UniversityBrookhaven National LaboratoryCabinet Office, Government of JapanNational Science FoundationUniversity of PortsmouthVanderbilt UniversityYale UniversityAcademia SinicaEuropean CommissionJapan Science and Technology AgencyU.S. Department of Energy
KeywordsElliptical galaxySurface brightness fluctuationVelocity dispersionStellar massFundamental plane (elliptical galaxies)GalaxyLenticular galaxySurface brightnessBrightest cluster galaxy

Abstract

fetched live from OpenAlex

Context.The stellar density profile of a galaxy is typically summarised with two numbers: the total stellar mass and half-light radius. The total mass of a galaxy, however, is not a well-defined quantity, due to the finite depth of photometric observations and the arbitrariness of the distinction between galaxy and diffuse intra-group light. This limits our ability to make accurate comparisons between models and observations. Aims.I wish to provide a more robust two-parameter description of the stellar density distribution of elliptical galaxies, in terms of quantities that can be measured unambiguously. Methods.I propose using the stellar mass enclosed within 10 kpc in projection,M*,10, and the mass-weighted stellar density slope within the same aperture, Γ*,10, for this purpose. I measured the distribution inM*,10and Γ*,10of a sample of elliptical galaxies from the Sloan Digital Sky Survey and the Galaxy And Mass Assembly survey, using photometry from the Hyper Suprime-Cam survey. I measured, at fixed (M*,10, Γ*,10), what the spread is in the galaxy surface brightness profile and central stellar velocity dispersion within the sample. As a first application, I then compared the observedM*,10 − Γ*,10relation of elliptical galaxies with that of similarly selected galaxies in the EAGLE REFERENCEsimulation. Results.The pair of values of (M*,10, Γ*,10) can be used to predict the stellar density profile in the inner 10 kpc of a galaxy with better than 20% accuracy. Similarly,M*,10and Γ*,10can be combined to obtain a proxy for stellar velocity dispersion that is at least as good as the stellar mass fundamental plane. The average stellar density slope of EAGLE elliptical galaxies matches that of observed ones atM*,10 = 1011M⊙well, but the EAGLEM*,10 − Γ*,10relation is shallower and has a larger intrinsic scatter compared to observations. Conclusions.This new parameterisation of the stellar density profile of massive elliptical galaxies provides a more robust way of comparing results from different photometric surveys and from hydrodynamical simulations, with respect to a description based on total stellar mass and half-light radius.

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)0.002
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: Simulation or modeling
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.004
Threshold uncertainty score0.007

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.002
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.001
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0010.001
Open science0.0010.000
Research integrity0.0010.000
Insufficient payload (model declined to judge)0.0010.001

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 head0.017
GPT teacher head0.192
Teacher spread0.175 · 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

Citations7
Published2020
Admission routes1
Has abstractyes

Explore more

Same venueAstronomy and Astrophysics→Same topicGalaxies: Formation, Evolution, Phenomena→French-language works237,207→