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Record W4415462384 · doi:10.33232/001c.146033

Clustering of DESI galaxies split by thermal Sunyaev-Zeldovich effect

2025· article· en· W4415462384 on OpenAlex
M. Rashkovetskyi, Daniel J. Eisenstein, J. Aguilar, S. P. Ahlen, Abhijeet Anand, D. Bianchi, David Brooks, F. J. Castander, T. Claybaugh, Andrei Cuceu, Kyle Dawson, Axel de la Macorra, Arjun Dey, Peter Doel, Simone Ferraro, Andreu Font-Ribera, J. E. Forero-Romero, E. Gaztañaga, G. Gutiérrez, H. K. Herrera-Alcantar, K. Honscheid, Cullan Howlett, Mustapha Ishak, R. R. Joyce, R. Kehoe, Theodore Kisner, O. Lahav, Andrew Lambert, Martin Landriau, Marc Manera, R. Miquel, Eva-Maria Mueller, S. Nadathur, N. Palanque‐Delabrouille, Will J. Percival, Francisco Prada, Ignasi Pérez-Ràfols, Ashley J. Ross, Graziano Rossi, E. Sánchez, David J. Schlegel, M. Schubnell, J. Silber, David Sprayberry, G. Tarlé, Benjamin A. Weaver, Rongpu Zhou, Hu Zou

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.

Bibliographic record

VenueThe Open Journal of Astrophysics · 2025
Typearticle
Languageen
FieldPhysics and Astronomy
TopicAstronomy and Astrophysical Research
Canadian institutionsPerimeter InstituteUniversity of Waterloo
FundersDivision of Astronomical SciencesScience and Technology Facilities CouncilU.S. Department of EnergyGordon and Betty Moore FoundationAgencia Estatal de InvestigaciónOffice of ScienceNational Aeronautics and Space AdministrationCommissariat à l'Énergie Atomique et aux Énergies AlternativesNational Science Foundation
KeywordsRedshiftGalaxyDark matterCosmologyCluster analysisDark energyCluster (spacecraft)

Abstract

fetched live from OpenAlex

The thermal Sunyaev-Zeldovich (tSZ) effect is associated with galaxy clusters - extremely large and dense structures tracing the dark matter with a higher bias than isolated galaxies. We propose to use the tSZ data to separate galaxies from redshift surveys into distinct subpopulations corresponding to different densities and biases independently of the redshift survey systematics. Leveraging the information from different environments, as in density-split and density-marked clustering, is known to tighten the constraints on cosmological parameters, like <mml:math xmlns:mml="http://www.w3.org/1998/Math/MathML" display="inline"> <mml:msub> <mml:mi>Ω</mml:mi> <mml:mi>m</mml:mi> </mml:msub> </mml:math> , <mml:math xmlns:mml="http://www.w3.org/1998/Math/MathML" display="inline"> <mml:msub> <mml:mi>σ</mml:mi> <mml:mn>8</mml:mn> </mml:msub> </mml:math> and neutrino mass. We use data from the Dark Energy Spectroscopic Instrument (DESI) and the Atacama Cosmology Telescope (ACT) in their region of overlap to demonstrate informative tSZ splitting of Luminous Red Galaxies (LRGs). We discover a significant increase in the large-scale clustering of DESI LRGs corresponding to detections starting from 1-2 sigma in the ACT DR6 + Planck tSZ Compton- <mml:math xmlns:mml="http://www.w3.org/1998/Math/MathML" display="inline"> <mml:mi>y</mml:mi> </mml:math> map, below the cluster candidate threshold (4 sigma). We also find that such galaxies have higher line-of-sight coordinate (and velocity) dispersions and a higher number of close neighbors than both the full sample and near-zero tSZ regions. We produce simple simulations of tSZ maps that are intrinsically consistent with galaxy catalogs and do not include systematic effects, and find a similar pattern of large-scale clustering enhancement with tSZ effect significance. Moreover, we observe that this relative bias pattern remains largely unchanged with variations in the galaxy-halo connection model in our simulations. This is promising for future cosmological inference from tSZ-split clustering with semi-analytical models. Thus, we demonstrate that valuable cosmological information is present in the lower signal-to-noise regions of the thermal Sunyaev-Zeldovich map, extending far beyond the individual cluster candidates.

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.

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)0.001
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Bench or experimental · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.783
Threshold uncertainty score0.597

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0020.001
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 head0.008
GPT teacher head0.294
Teacher spread0.287 · 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