Abstract
The kinematic and thermal Sunyaev-Zel'dovich (kSZ and tSZ) effects probe the abundance and thermodynamics of ionized gas in galaxies and clusters. We present a new hybrid estimator to measure the kSZ effect by combining cosmic microwave background temperature anisotropy maps with photometric and spectroscopic optical survey data. The method interpolates a velocity reconstruction from a spectroscopic catalog at the positions of objects in a photometric catalog, which makes it possible to leverage the high number density of the photometric catalog and the precision of the spectroscopic survey. Combining this hybrid kSZ estimator with a measurement of the tSZ effect simultaneously constrains the density and temperature of free electrons in the photometrically selected galaxies. Using the 1000 deg2 of overlap between the Atacama Cosmology Telescope (ACT) Data Release 5, the first three years of data from the Dark Energy Survey (DES), and the Baryon Oscillation Spectroscopic Survey (BOSS) Data Release 12, we detect the kSZ signal at 4.8σ and reject the null (no-kSZ) hypothesis at 5.1σ. This corresponds to 2.0σ per 100,000 photometric objects with a velocity field based on a spectroscopic survey with 1/5th the density of the photometric catalog. For comparison, a recent ACT analysis using exclusively spectroscopic data from BOSS measured the kSZ signal at 2.1σ per 100,000 objects. Our derived constraints on the thermodynamic properties of the galaxy halos are consistent with previous measurements. With future surveys, such as the Dark Energy Spectroscopic Instrument and the Rubin Observatory Legacy Survey of Space and Time, we expect that this hybrid estimator could result in measurements with significantly better signal-to-noise than those that rely on spectroscopic data alone.
Original language | English |
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Article number | 023516 |
Journal | Physical Review D |
Volume | 108 |
Issue number | 2 |
DOIs | |
State | Published - Jul 15 2023 |
Funding
A. C. T. operated in the Parque Astronómico Atacama in northern Chile under the auspices of the Agencia Nacional de Investigación y Desarrollo (ANID). Support for ACT was through the U.S. National Science Foundation through Awards No. AST-0408698, No. AST-0965625, and No. AST-1440226 for the ACT project, as well as Awards No. PHY-0355328, No. PHY-0855887, and No. PHY-1214379. Funding was also provided by Princeton University, the University of Pennsylvania, and a Canada Foundation for Innovation (CFI) award to UBC. The development of multichroic detectors and lenses was supported by NASA Grants No. NNX13AE56G and No. NNX14AB58G. Detector research at N. I. S. T. was supported by the NIST Innovations in Measurement Science program. Computing for ACT was performed using the Princeton Research Computing resources at Princeton University, the National Energy Research Scientific Computing Center (NERSC), and the Niagara supercomputer at the SciNet HPC Consortium. M. M. K. is supported by the NSF Graduate Research Fellowship under Grant No. DGE-1256260. J. C. H. acknowledges support from NSF Grant No. AST-2108536, NASA Grants No. 21-ATP21-0129, and No. 22-ADAP22-0145, DOE Grant No. DE-SC00233966, the Sloan Foundation, and the Simons Foundation. C. S. acknowledges support from the Agencia Nacional de Investigación y Desarrollo (ANID) through FONDECYT Grant No. 11191125 and BASAL Project No. FB210003. This work was supported by a grant from the Simons Foundation (Grant No. CCA 918271, PBL). K. M. acknowledges support from the National Research Foundation of South Africa. E. C. acknowledges support from the European Research Council (ERC) under the European Union’s Horizon 2020 research and innovation programme (Grant Agreement No. 849169). We would also like to gratefully acknowledge the many publicly available software packages that made this work possible. We relied heavily on emcee , m op-c- gt A21, pixell , and a stropy , a community-developed core p ython package for Astronomy . We also used healp ix and the p ython wrapper for healp ix which is healpy . In addition to these we made use of libsharp , the matplotlib package, n um p y , pandas and s ci p y .
Funders | Funder number |
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National Science Foundation | DGE-1256260, AST-1440226, AST-2108536, PHY-1214379, AST-0965625, 21-ATP21-0129, 22-ADAP22-0145, AST-0408698, PHY-0855887, PHY-0355328 |
U.S. Department of Energy | DE-SC00233966 |
National Aeronautics and Space Administration | NNX13AE56G, NNX14AB58G |
National Institute of Standards and Technology | |
Alfred P. Sloan Foundation | |
Simons Foundation | |
Princeton University | |
University of Pennsylvania | |
Horizon 2020 Framework Programme | 849169 |
Canada Foundation for Innovation | |
European Research Council | |
National Research Foundation | |
Fondo Nacional de Desarrollo Científico y Tecnológico | FB210003, 11191125, CCA 918271 |
Agencia Nacional de Investigación y Desarrollo |