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Comparison of the excess mass around CFHTLenS galaxy-pairs to predictions from a semi-analytic model using galaxy-galaxy-galaxy lensing

2019· article· en· W3101463691 on OpenAlexaboutno aff
P. Šimon, Hananeh Saghiha, Stefan Hilbert, Peter Schneider, C. Boever, Angus H. Wright

Bibliographic record

VenueSpringer Link (Chiba Institute of Technology) · 2019
Typearticle
Languageen
FieldPhysics and Astronomy
TopicGalaxies: Formation, Evolution, Phenomena
Canadian institutionsnot available
FundersBundesministerium für Wirtschaft und EnergieDeutsche Forschungsgemeinschaft
KeywordsAstrophysicsPhysicsInteracting galaxyLenticular galaxyGalaxyGalaxy mergerBrightest cluster galaxyGalaxy formation and evolutionAstronomyGalaxy group

Abstract

fetched live from OpenAlex

\nThe matter environment of galaxies is connected to the physics of galaxy formation and evolution. In particular, the average matter distribution around galaxy pairs is a strong test for galaxy models. Utilising galaxy-galaxy-galaxy lensing as a direct probe, we map out the distribution of correlated surface mass-density around galaxy pairs in the Canada-France-Hawaii Telescope Lensing Survey (CFHTLenS). We have compared, for the first time, these so-called excess mass maps to predictions provided by a recent semi-analytic model, which is implanted within the dark-matter Millennium Simulation. We analysed galaxies with stellar masses between 109 − 1011 M⊙ in two photometric redshift bins, for lens redshifts z ≲ 0.6. The projected separation of the galaxy pairs ranges between 170 − 300 h−1 kpc, thereby focusing on pairs inside groups and clusters. To allow us a better interpretation of the maps, we discuss the impact of chance pairs, that is galaxy pairs that appear close to each other in projection only. We have introduced an alternative correlation map that is less affected by projection effects but has a lower signal-to-noise ratio. Our tests with synthetic data demonstrate that the patterns observed in both types of maps are essentially produced by correlated pairs which are close in redshift (Δz ≲ 5 × 10−3). We also verify the excellent accuracy of the map estimators. In an application to the galaxy samples in the CFHTLenS, we obtain a 3σ − 6σ significant detection of the excess mass and an overall good agreement with the galaxy model predictions. There are, however, a few localised spots in the maps where the observational data disagrees with the model predictions on a ≈3.5σ confidence level. Although we have no strong indications for systematic errors in the maps, this disagreement may be related to the residual B-mode pattern observed in the average of all maps. Alternatively, misaligned galaxy pairs inside dark matter halos or lensing by a misaligned distribution of the intra-cluster gas might also cause the unanticipated bulge in the distribution of the excess mass between lens pairs.\n

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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 score0.167
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0010.001
Science and technology studies0.0000.001
Scholarly communication0.0000.001
Open science0.0010.001
Research integrity0.0000.001
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 head0.020
GPT teacher head0.253
Teacher spread0.233 · 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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