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Weak-lensing analysis of galaxy pairs using CS82 data

2019· article· en· W3103804284 on OpenAlexaboutno aff
Elizabeth Johana Gonzalez, Facundo Rodríguez, D. G. Lambas, Martı́n Makler, Valeria Mesa, Sol Alonso, Fernanda Duplancic, M. E. S. Pereira, Huanyuan Shan

Bibliographic record

VenueSpringer Link (Chiba Institute of Technology) · 2019
Typearticle
Languageen
FieldPhysics and Astronomy
TopicGalaxies: Formation, Evolution, Phenomena
Canadian institutionsnot available
Fundersnot available
KeywordsPhysicsAstrophysicsWeak gravitational lensingHaloGalaxyStrong gravitational lensingVirial massMass ratioGravitational lensRedshift

Abstract

fetched live from OpenAlex

Here we analyze a sample of close galaxy pairs (relative projected separation < 25 h -1 kpc and relative radial velocities < 350 km s -1 ) using a weak-lensing analysis based on the Canada-France-Hawaii Telescope Stripe 82 Survey (CS82). We determine halo masses for the total sample of pairs as well as for interacting, red, and higher-luminosity pair subsamples with ∼3σ confidence. The derived lensing signal for the total sample can be fitted either by a Singular Isothermal Sphere (SIS) with σ V = 223 ± 24 km s -1 or a Navarro-Frenk-White (NFW) profile with R 200 = 0.30 ± 0.03 h -1 Mpc. The pair total masses and total r band luminosities imply an average mass-to-light ratio of ∼200 h M ⊙ /L ⊙ . On the other hand, red pairs which include a larger fraction of elliptical galaxies, show a larger mass-to-light ratio of ∼345 h M ⊙ /L ⊙ . Derived lensing masses were compared to a proxy of the dynamical mass, obtaining a good correlation. However, there is a large discrepancy between lensing masses and the dynamical mass estimates, which could be accounted for by astrophysical processes such as dynamical friction, by the inclusion of unbound pairs, and by significant deviations of the density distribution from SIS and NFW profiles in the inner regions. We also compared lensing masses with group mass estimates, finding very good agreement with the sample of groups with two members. Red and blue pairs show large differences between group and lensing masses, which is likely due to the single mass-to-light ratio adopted to compute the group masses.

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 categoriesMeta-epidemiology (narrow)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.024
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0010.002
Science and technology studies0.0000.000
Scholarly communication0.0000.001
Open science0.0010.001
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 head0.019
GPT teacher head0.241
Teacher spread0.222 · 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.

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

Citations6
Published2019
Admission routes1
Has abstractyes

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