Quantification of the multi-streaming effect in redshift space distortion

Zheng, Yi; Zhang, Pengjie; Oh, Minji

doi:10.1088/1475-7516/2017/05/030

Cited by 14 publications

(19 citation statements)

References 76 publications

(110 reference statements)

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“…The analysis using the k max from Table 1 shows a significant degeneracy between f and σ v that has also been found previously (Zheng et al 2017;. The improvement on the TNS constraints at z = 1 is mainly due to the much higher k max at z = 1 compared to that at z = 0.5.…”

Section: Tablesupporting

confidence: 79%

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: Tablesupporting

confidence: 79%

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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“…Our results are summarised in Table 2. The analysis using the k max from Table 1 shows a significant degeneracy between f and σ v for the TNS model which has also been found previously [35,65]. The improvement on the TNS constraints at z = 1 is mainly due to the much higher k max at z = 1 compared to that at z = 0.5.…”

supporting

confidence: 78%

Assessing non-linear models for galaxy clustering – II. Model validation and forecasts for Stage IV surveys

Bose

Pourtsidou

Markovič

et al. 2020

Monthly Notices of the Royal Astronomical Society

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We provide a detailed comparison of two different models for the halo redshift space power spectrum, namely the commonly applied TNS model and an effective field theory of large scale structure (EFTofLSS) inspired model. In a least χ 2 analysis using simulation data, we determine ranges of validity for the models. In all our analyses we vary all nuisance parameters and the growth rate of structure, f , using survey specifications typical of Stage IV galaxy surveys. We determine that the TNS model with a Lorentzian damping and using standard Eulerian perturbative modelling outperforms other variants of the TNS model. But we also find that the EFTofLSS-based model is able to fit the data down to smaller scales compared to this optimal TNS variant at z = 0.5, while the two models perform equally well at z = 1. We then conduct an exploratory Fisher analysis to investigate parameter degeneracies, using the full anisotropic power spectrum. Next, we move on to a Bayesian MCMC analysis utilising the monopole, quadrupole, and hexadecapole spectra, with a restricted range of scales for the latter in order for the f constraints to remain unbiased. In contrast to the exploratory Fisher matrix forecasts, our MCMC analysis finds that the EFTofLSS-based model provides tighter marginalised constraints on the growth rate at z = 0.5 than the TNS model, despite having additional nuisance parameters. The two perform comparatively at z = 1. We also investigate the impact of priors on nuisance parameters which can be reasonably obtained from higher order statistics or external data sets. We find that conservative priors have limited impact on the constraints. Finally, we extend previous work to provide a consistent comparison between Fisher matrix and MCMC forecasts for the EFTofLSS model using the multipole expansion formalism, and reach good agreement between them.

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“…In this work, we consider both the Gaussian and the Lorentzian forms of the damping factor, as already done in previous works (see e.g. Scoccimarro 2004;Taruya et al 2010;Marulli et al 2012b;Xu et al 2012Xu et al , 2013Zheng et al 2017):…”

Section: Modelling Redshift-space Distortionsmentioning

confidence: 99%

Validating the methodology for constraining the linear growth rate from clustering anisotropies

García-Farieta

Marulli

Moscardini

et al. 2020

Monthly Notices of the Royal Astronomical Society

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Redshift-space clustering distortions provide one of the most powerful probes to test the gravity theory on the largest cosmological scales. In this paper we perform a systematic validation study of the state-of-the-art statistical methods currently used to constrain the linear growth rate from redshift-space distortions in the galaxy two-point correlation function. The numerical pipelines are tested on mock halo catalogues extracted from large N-body simulations of the standard cosmological framework, in the redshift range 0.5 z 2. We consider both the monopole and quadrupole multipole moments of the redshift-space two-point correlation function, as well as the radial and transverse clustering wedges, in the comoving scale range 10 < r[h −1 Mpc] < 55. Moreover, we investigate the impact of redshift measurement errors, up to δz ∼ 0.5%, which introduce spurious clustering anisotropies. We quantify the systematic uncertainties on the growth rate and linear bias measurements due to the assumptions in the redshiftspace distortion model. Considering both the dispersion model and two widely-used models based on perturbation theory, that is the Scoccimarro (2004) model and the Taruya et al. (2010) model, we find that the linear growth rate is underestimated by about 5 − 10% at z < 1, while limiting the analysis at larger scales, r > 30 h −1 Mpc, the discrepancy is reduced below 5%. At higher redshifts, we find instead an overall good agreement between measurements and model predictions. The Taruya et al. (2010) model is the one which performs better, with growth rate uncertainties below about 3%. The effect of redshift errors is degenerate with the one of small-scale random motions, and can be marginalised over in the statistical analysis, not introducing any statistically significant bias in the linear growth constraints, especially at z ≥ 1.

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Quantification of the multi-streaming effect in redshift space distortion

Cited by 14 publications

References 76 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

Assessing non-linear models for galaxy clustering – II. Model validation and forecasts for Stage IV surveys

Validating the methodology for constraining the linear growth rate from clustering anisotropies

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