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Title: Modelling the large-scale redshift-space 3-point correlation function of galaxies

Journal Article · · Monthly Notices of the Royal Astronomical Society
DOI:https://doi.org/10.1093/mnras/stx490· OSTI ID:1530294
 [1];  [2]
  1. Lawrence Berkeley National Lab. (LBNL), Berkeley, CA (United States); Univ. of California, Berkeley, CA (United States)
  2. Harvard-Smithsonian Center for Astrophysics, Cambridge, MA (United States)

We present a configuration-space model of the large-scale galaxy 3-point correlation function (3PCF) based on leading-order perturbation theory and including redshift-space distortions (RSD). This model should be useful in extracting distance-scale information from the 3PCF via the baryon acoustic oscillation method. We include the first redshift-space treatment of biasing by the baryon-dark matter relative velocity. Overall, on large scales the effect of RSD is primarily a renormalization of the 3PCF that is roughly independent of both physical scale and triangle opening angle; for our adopted Ωm and bias values, the rescaling is a factor of ~1.8. We also present an efficient scheme for computing 3PCF predictions from our model, important for allowing fast exploration of the space of cosmological parameters in future analyses.

Research Organization:
Lawrence Berkeley National Laboratory (LBNL), Berkeley, CA (United States)
Sponsoring Organization:
USDOE Office of Science (SC)
Grant/Contract Number:
AC02-05CH11231
OSTI ID:
1530294
Journal Information:
Monthly Notices of the Royal Astronomical Society, Vol. 469, Issue 2; ISSN 0035-8711
Publisher:
Royal Astronomical SocietyCopyright Statement
Country of Publication:
United States
Language:
English
Citation Metrics:
Cited by: 31 works
Citation information provided by
Web of Science

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Cited By (5)

Estimating Covariance Matrices for Two- and Three-Point Correlation Function Moments in Arbitrary Survey Geometries text January 2019
Galactos
  • Friesen, Brian; Patwary, Md. Mostofa Ali; Austin, Brian
  • Proceedings of the International Conference for High Performance Computing, Networking, Storage and Analysis https://doi.org/10.1145/3126908.3126927
conference November 2017
DEMNUni: massive neutrinos and the bispectrum of large scale structures journal March 2018
DEMNUni: Massive neutrinos and the bispectrum of large scale structures text January 2017
Estimating covariance matrices for two- and three-point correlation function moments in Arbitrary Survey Geometries journal October 2019