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Record W4283398329 · doi:10.1103/physrevd.105.123526

Cross-correlation of Dark Energy Survey Year 3 lensing data with ACT and <mml:math xmlns:mml="http://www.w3.org/1998/Math/MathML" display="inline"><mml:mi>P</mml:mi><mml:mi>l</mml:mi><mml:mi>a</mml:mi><mml:mi>n</mml:mi><mml:mi>c</mml:mi><mml:mi>k</mml:mi></mml:math> thermal Sunyaev-Zel’dovich effect observations. II. Modeling and constraints on halo pressure profiles

2022· article· en· W4283398329 on OpenAlexfundno aff
S. Pandey, M. Gatti, Eric J. Baxter, J. Colin Hill, Xiao Fang, C. Doux, G. Giannini, Marco Raveri, J. DeRose, Hung-Jin Huang, E. Barry Moser, Nicholas Battaglia, A. Alarcon, A. Amon, M. R. Becker, A. Campos, C. Chang, R. Chen, A. Choi, K. Eckert, J. Elvin-Poole, S. Everett, A. Ferté, I. Harrison, N. MacCrann, J. McCullough, J. Myles, A Navarro-Alsina, J. Prat, R. P. Rollins, C. Sánchez, T. Shin, M. A. Troxel, I. Tutusaus, B. Yin, M. Aguena, S. Allam, F. Andrade-Oliveira, G. M. Bernstein, E. Bertin, Boris Bolliet, J. R. Bond, D. Brooks, Erminia Calabrese, A. Carnero Rosell, M. Carrasco Kind, J. Carretero, R. Cawthon, M. Costanzi, M. Crocce, L. N. da Costa, M. E. S. Pereira, J. De Vicente, S. Desai, H. T. Diehl, J. P. Dietrich, P. Doel, Jo Dunkley, A. E. Evrard, Simone Ferraro, I. Ferrero, B. Flaugher, P. Fosalba, J. García-Bellido, E. Gaztañaga, D. W. Gerdes, T. Giannantonio, D. Gruen, R. A. Gruendl, J. Gschwend, G. Gutierrez, K. Herner, Adam D. Hincks, S. R. Hinton, K. Honscheid, John P. Hughes, Dragan Huterer, Bhuvnesh Jain, D.J James, T. Jeltema, E. Krause, K. Kuehn, O. Lahav, M. Lima, Martine Lokken, Mathew S. Madhavacheril, M. A. G. Maia, J. J. McMahon, P. Melchior, F. Menanteau, R. Miquel, J. J. Mohr, Kavilan Moodley, R. Morgan, F. Nati, Michael D. Niemack, Lyman A. Page, A. Palmese, F. Paz-Chinchón, A. Pieres, M. Rodriguez-Monroy, A. K. Romer, E. Sánchez, V. Scarpine, Emmanuel Schaan, S. Serrano, I. Sevilla-Noarbe, E. Sheldon, B. D. Sherwin, Cristobál Sifón, M. Smith, M. Soares-Santos, David N. Spergel, E. Suchyta, M. E. C. Swanson, G. Tarlé, D. Thomas, C. To, T.N Varga, J. Weller, Edward J. Wollack, Zhilei Xu

Bibliographic record

VenuePhysical review. D/Physical review. D. · 2022
Typearticle
Languageen
FieldPhysics and Astronomy
TopicGalaxies: Formation, Evolution, Phenomena
Canadian institutionsnot available
FundersH2020 European Research CouncilSLAC National Accelerator LaboratoryFondo Nacional de Desarrollo Científico y TecnológicoIntegrated Electronics Engineering Center, Binghamton UniversityEuropean Regional Development FundScience and Technology Facilities CouncilKavli Institute for Cosmological Physics, University of ChicagoOffice of ScienceUniversity of Illinois at Urbana-ChampaignCentro de Investigaciones Energéticas, Medioambientales y TecnológicasConselho Nacional de Desenvolvimento Científico e TecnológicoMinisterio de Economía y CompetitividadAgencia Nacional de Investigación y DesarrolloGeneralitat de CatalunyaUniversity of PortsmouthArts and Culture TrustHigh Energy PhysicsDeutsche ForschungsgemeinschaftArgonne National LaboratoryCentres de Recerca de CatalunyaTexas A and M UniversityUniversity of ChicagoNational Research FoundationOhio State UniversityMinistério da Ciência, Tecnologia e InovaçãoFundação Carlos Chagas Filho de Amparo à Pesquisa do Estado do Rio de JaneiroCanada Foundation for InnovationHigher Education Funding Council for EnglandUniversity College LondonNational Aeronautics and Space AdministrationLawrence Berkeley National LaboratoryFinanciadora de Estudos e ProjetosUniversity of PennsylvaniaEuropean CommissionU.S. Department of EnergyPrinceton UniversityCenter for Cosmology and Astroparticle Physics, Ohio State UniversityUniversity of SussexNational Institute of Standards and TechnologyGordon and Betty Moore FoundationInstitut de Física d'Altes EnergiesNational Centre for Supercomputing ApplicationsFermilabNational Science Foundation
KeywordsPhysicsAstrophysicsDark energyRedshiftCosmic microwave backgroundCosmologyPlanckWeak gravitational lensingHaloGalaxyBaryonGravitational lensSouth Pole TelescopeAstronomy

Abstract

fetched live from OpenAlex

Hot, ionized gas leaves an imprint on the cosmic microwave background via the thermal Sunyaev-Zel'dovich (tSZ) effect. The cross-correlation of gravitational lensing (which traces the projected mass) with the tSZ effect (which traces the projected gas pressure) is a powerful probe of the thermal state of ionized baryons throughout the Universe and is sensitive to effects such as baryonic feedback. In a companion paper (Gatti et al. Phys. Rev. D 105, 123525 (2022)), we present tomographic measurements and validation tests of the cross-correlation between Galaxy shear measurements from the first three years of observations of the Dark Energy Survey and tSZ measurements from a combination of Atacama Cosmology Telescope and Planck observations. In this work, we use the same measurements to constrain models for the pressure profiles of halos across a wide range of halo mass and redshift. We find evidence for reduced pressure in low-mass halos, consistent with predictions for the effects of feedback from active Galactic nuclei. We infer the hydrostatic mass bias ($B\ensuremath{\equiv}{M}_{500c}/{M}_{\mathrm{SZ}}$) from our measurements, finding $B=1.8\ifmmode\pm\else\textpm\fi{}0.1$ when adopting the Planck-preferred cosmological parameters. We additionally find that our measurements are consistent with a nonzero redshift evolution of $B$, with the correct sign and sufficient magnitude to explain the mass bias necessary to reconcile cluster count measurements with the Planck-preferred cosmology. Our analysis introduces a model for the impact of intrinsic alignments (IAs) of galaxy shapes on the shear-tSZ correlation. We show that IA can have a significant impact on these correlations at current noise levels.

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: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.048
Threshold uncertainty score0.095

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.002
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.001
Bibliometrics0.0030.002
Science and technology studies0.0000.000
Scholarly communication0.0010.000
Open science0.0000.001
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0030.001

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 head0.020
GPT teacher head0.297
Teacher spread0.277 · 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

Citations42
Published2022
Admission routes1
Has abstractyes

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Same venuePhysical review. D/Physical review. D.Same topicGalaxies: Formation, Evolution, PhenomenaFrench-language works237,207