Study on the mapping of dark matter clustering from real space to redshift space

Zheng, Yi; Song, Yong-Seon

doi:10.1088/1475-7516/2016/08/050

Cited by 26 publications

(51 citation statements)

References 96 publications

(122 reference statements)

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“…For this purpose, we consider the commonly used TNS model (Taruya et al 2010). This model can reproduce the broadband power spectrum including RSD from simulations at linear and mildly non-linear scales Taruya et al 2013;Ishikawa et al 2014;Zheng and Song 2016;Gil-Marín et al 2016a,b;Bose and Koyama 2016). The model is combined with the generalised bias prescription of McDonald and Roy (2009).…”

Section: Introductionmentioning

confidence: 99%

Assessing non-linear models for galaxy clustering I: unbiased growth forecasts from multipole expansion

Markovič

Pourtsidou

Bose

2019

The Open Journal of Astrophysics

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We assess the performance of the Taruya, Nishimichi and Saito (TNS) model for the halo redshift space power spectrum, focusing on utilising mildly non-linear scales to constrain the growth rate of structure f . Using simulations with volume and number density typical of forthcoming Stage IV galaxy surveys, we determine ranges of validity for the model at redshifts z = 0.5 and z = 1. We proceed to perform a Bayesian MCMC analysis utilising the monopole, quadrupole, and hexadecapole spectra, followed by an exploratory Fisher matrix analysis. As previously noted in other forecasts as well as in real data analyses, we find that including the hexadecapole can significantly improve the constraints. However, a restricted range of scales is required for the hexadecapole in order for the growth parameter estimation to remain unbiased, limiting the improvement. We consistently quantify these effects by employing the multipole expansion formalism in both our Fisher and MCMC forecasts.A way to attack this challenge is by using perturbation theory based models (Bernardeau et al. 2002;Kaiser 1987;Scoccimarro 2004) that can be easily extended to include non-standard theories of gravity and dark energy (see Koyama 2016, 2017; Bose et al. 2018a,b, for example). These can be combined with phenomenological ingredients to model non-linear physics (Taruya et al. 2010;Senatore and Zaldarriaga 2014;de la Bella et al. 2017). Additionally, a model for the galaxy bias is required to relate the dark matter and galaxy distributions .An important factor, which is the main focus of this paper, is our ability to use these prescriptions to model non-linear structure formation in an unbiased manner, and how this affects the growth of structure parameter estimation with Stage IV surveys. dida.markovic@port.ac.uk benjamin.bose@unige.ch a.pourtsidou@qmul.ac.uk 1 www.euclid-ec.org 2 https://wfirst.gsfc.nasa.gov/ 3 www.desi.lbl.gov

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Section: Introductionmentioning

confidence: 99%

Assessing non-linear models for galaxy clustering I: unbiased growth forecasts from multipole expansion

Markovič

Pourtsidou

Bose

2019

The Open Journal of Astrophysics

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“…The detailed simulation parameters are listed in table 1. The hybrid RSD model for dark matter was verified with the simulations introduced above in our previous work [96,97]. In this manuscript, we test the hybrid RSD model for halos on the halo catalogs generated from the same simulations.…”

Section: Verification Of Theoretical Modelmentioning

confidence: 57%

“…The same treatment is applied to higher order polynomial measurements, which are computed by combining fields such as of u z (r), ∇ z u z (r), δ h u z (r) and u z ∇ z u z (r). The detailed methodology of higher order polynomial calculation is explained in [96] with dark matter particles as an example. The key strategy is that we compute these various field combinations in the configuration space, and transform them into the Fourier space, where we complete all two-point statistical measurements and derive P perturbed,h .…”

Section: The Mapping Formula Accuracy Testmentioning

confidence: 99%

Study on the mapping of halo clustering from real space to redshift space

Zheng

Song

2019

J. Cosmol. Astropart. Phys.

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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 works, we have verified the robustness of advanced TNS mapping formula in our hybrid RSD model in dark matter case, where the halo bias models are not taken into account for the halo mapping formula in redshift space. Using 100 realizations of halo catalogs in N-body simulations, we find that our halo RSD model with the known halo bias model and the effective FoG function accurately predicts the halo power spectrum measurements, within 1∼2% accuracy up to k ∼ 0.2 h Mpc −1 , depending on different halo masses and redshifts. Theoretical RSD model for halo clusteringUnderstanding the halo clustering in redshift space is a key stepstone towards theoretically describing the observed galaxy clustering in the Universe. In our previous work [96], the RSD model for dark matter clustering in redshift space was studied in detail. The model has been proved to accurately reconstruct the linear growth rate within 1% at k < 0.18 h Mpc −1 for simulations of different cosmologies with different Hubble parameters [97]. This theoretical RSD model will be applied to the halo clustering case in this manuscript. We will describe the RSD model in this section. Besides, the halo density bias model [108] and halo velocity bias model [105] adopted in this paper will be presented as well. The advanced TNS model for halosMatter distribution in the universe is inhomogeneous at small scales. The gravitational attraction arising from this inhomogeneity perturbs galaxies and causes their motions deviating from the Hubble flow. These deviations, named peculiar velocities of galaxies, disturb the galaxy redshifts and hence the galaxy distribution in redshift space in an anisotropic way.

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“…This model was introduced in [16] and is one of the best approaches to perturbation theory known at present, having been applied in the recent BOSS galaxy clustering analysis [4,8]. It has also been thoroughly validated against simulations and has stood up to other perturbative models [9,18,20,29,47,[56][57][58][59][60][61]. The model is given by [16]…”

Section: Tnsmentioning

confidence: 99%

Nonlinear contributions to angular power spectra

et al. 2020

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Future galaxy clustering surveys will probe small scales where non-linearities become important. Since the number of modes accessible on intermediate to small scales is very high, having a precise model at these scales is important especially in the context of discriminating alternative cosmological models from the standard one. In the mildly nonlinear regime, such models typically differ from each other, and galaxy clustering data will become very precise on these scales in the near future. As the observable quantity is the angular power spectrum in redshift space, it is important to study the effects of non-linear density and redshift space distortion (RSD) in the angular power spectrum. We compute non-linear contributions to the angular power spectrum using a flat-sky approximation that we introduce in this work, and compare the results of different perturbative approaches with N -body simulations. We find that the TNS perturbative approach is significantly closer to the N -body result than Eulerian or Lagrangian 1-loop approximations, effective field theory of large scale structure or a halofit-inspired model. However, none of these prescriptions is accurate enough to model the angular power spectrum well into the non-linear regime. In addition, for narrow redshift bins, ∆z 0.01, the angular power spectrum acquires nonlinear contributions on all scales, right down to = 2, and is hence not a reliable tool at this time. To overcome this problem, we need to model non-linear RSD terms, for example as TNS does, but for a matter power spectrum that remains reasonably accurate well into the deeply non-linear regime, such as halofit.

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Study on the mapping of dark matter clustering from real space to redshift space

Cited by 26 publications

References 96 publications

Assessing non-linear models for galaxy clustering I: unbiased growth forecasts from multipole expansion

Assessing non-linear models for galaxy clustering I: unbiased growth forecasts from multipole expansion

Study on the mapping of halo clustering from real space to redshift space

Nonlinear contributions to angular power spectra

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