2019
DOI: 10.1088/1475-7516/2019/06/013
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Study on the mapping of halo clustering from real space to redshift space

Abstract: The mapping of galaxy clustering from real space to redshift space introduces the anisotropic property to the measured galaxy density power spectrum in redshift space, known as the redshift space distortion (RSD) effect. The mapping formula is intrinsically non-linear, which is complicated by the higher order polynomials due to indefinite orders of cross correlations between density and velocity fields, and the Finger-of-God (FoG) effect due to the randomness of the galaxy peculiar velocity field. In previous … Show more

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Cited by 8 publications
(5 citation statements)
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“…Further, loop corrections in the perturbative part can be added to improve its modelling of the small scales at the considered redshifts. Alternatively, these corrections can be calibrated by simulations [43,44]. The model has also been already extended to general theories of gravity and dark energy [22,23].…”
Section: Discussionmentioning
confidence: 99%
“…Further, loop corrections in the perturbative part can be added to improve its modelling of the small scales at the considered redshifts. Alternatively, these corrections can be calibrated by simulations [43,44]. The model has also been already extended to general theories of gravity and dark energy [22,23].…”
Section: Discussionmentioning
confidence: 99%
“…Meanwhile, one of the authors has tested the TNS-based [33] dark matter clustering mapping formula from real to redshift space in [58]. The halo density bias and the halo clustering mapping formula of this model will be tested in [59]. However, these investigations so far overlook an important physical process of non-linear structure formation, namely the shell crossing and the resultant multi-streaming effect.…”
Section: Introductionmentioning
confidence: 99%
“…The above results are widely known in the literature (e.g., Scoccimarro 2004). Several models of RSD are based upon Equation ( 6), or Equation ( 5) or its equivalent forms (e.g., Scoccimarro 2004;Matsubara 2008;Taruya et al 2010;Seljak & McDonald 2011;Okumura et al 2012a;Zhang et al 2013;Zheng et al 2013;Zheng & Song 2016;Song et al 2018;Zheng et al 2019).…”
Section: Power Spectrum Based Modelsmentioning
confidence: 68%