Probing scalar tensor theories for gravity in redshift space

Sabiu, Cristiano G.; Mota, David F.; Llinares, Claudio; Park, Changbom

doi:10.1051/0004-6361/201527776

Cited by 14 publications

(13 citation statements)

References 57 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…Although the scale-dependent growth rates predict an enhancement in the redshift-space clustering in f (R) models, this is only seen at relatively small scales, x < 20 h −1 Mpc (x < 50 h −1 Mpc in F4). At these small scales, we will find deviations from linear theory due to the effect of virial motions, and one should take into account the predicted enhanced peculiar velocities in MOG models (Zu et al 2014;Hellwing et al 2014;Sabiu et al 2016). That means that, in order to use the growth rate inferred from galaxy redshift catalogues to constrain this class of models, it is necessary to model these effects in detail, and to test the analysis method with realistic MOG mocks (Barreira et al 2016).…”

Section: Discussionmentioning

confidence: 99%

Real- and redshift-space halo clustering in f ( R ) cosmologies

Arnalte-Mur

Hellwing

Norberg

2017

Mon. Not. R. Astron. Soc.

View full text Add to dashboard Cite

The full-text may be used and/or reproduced, and given to third parties in any format or medium, without prior permission or charge, for personal research or study, educational, or not-for-pro t purposes provided that:• a full bibliographic reference is made to the original source • a link is made to the metadata record in DRO • the full-text is not changed in any way The full-text must not be sold in any format or medium without the formal permission of the copyright holders.Please consult the full DRO policy for further details. ABSTRACTWe present two-point correlation function statistics of the mass and the haloes in the chameleon f(R) modified gravity scenario using a series of large-volume N-body simulations. Three distinct variations of f(R) are considered (F4, F5 and F6) and compared to a fiducial cold dark matter ( CDM) model in the redshift range z ∈ [0, 1]. We find that the matter clustering is indistinguishable for all models except for F4, which shows a significantly steeper slope.The ratio of the redshift-to real-space correlation function at scales >20 h −1 Mpc agrees with the linear General Relativity (GR) Kaiser formula for the viable f(R) models considered. We consider three halo populations characterized by spatial abundances comparable to that of luminous red galaxies and galaxy clusters. The redshift-space halo correlation functions of F4 and F5 deviate significantly from CDM at intermediate and high redshift, as the f(R) halo bias is smaller than or equal to that of the CDM case. Finally, we introduce a new model-independent clustering statistic to distinguish f(R) from GR: the relative halo clustering ratio -R. The sampling required to adequately reduce the scatter in R will be available with the advent of the next-generation galaxy redshift surveys. This will foster a prospective avenue to obtain largely model-independent cosmological constraints on this class of modified gravity models.

show abstract

Section: Discussionmentioning

confidence: 99%

Real- and redshift-space halo clustering in f ( R ) cosmologies

Arnalte-Mur

Hellwing

Norberg

2017

Mon. Not. R. Astron. Soc.

View full text Add to dashboard Cite

show abstract

“…There is a growing interest in extending RSD studies to smaller scales as a test of modified gravity and interacting dark energy models (e.g. Jennings et al 2012;Marulli et al 2012;Hellwing et al 2014;Taruya et al 2014;Zu et al 2014;Xu 2015;Barreira et al 2016;Sabiu et al 2016;Arnalte-Mur et al 2017). These future developments provide the main motivation for our work.…”

Section: Introductionmentioning

confidence: 99%

On the streaming model for redshift-space distortions

Kuruvilla

Porciani

2018

Monthly Notices of the Royal Astronomical Society

View full text Add to dashboard Cite

The streaming model describes the mapping between real and redshift space for 2point clustering statistics. Its key element is the probability density function (PDF) of line-of-sight pairwise peculiar velocities. Following a kinetic-theory approach, we derive the fundamental equations of the streaming model for ordered and unordered pairs. In the first case, we recover the classic equation while we demonstrate that modifications are necessary for unordered pairs. We then discuss several statistical properties of the pairwise velocities for DM particles and haloes by using a suite of high-resolution N-body simulations. We test the often used Gaussian ansatz for the PDF of pairwise velocities and discuss its limitations. Finally, we introduce a mixture of Gaussians which is known in statistics as the generalised hyperbolic distribution and show that it provides an accurate fit to the PDF. Once inserted in the streaming equation, the fit yields an excellent description of redshift-space correlations at all scales that vastly outperforms the Gaussian and exponential approximations. Using a principal-component analysis, we reduce the complexity of our model for large redshiftspace separations. Our results increase the robustness of studies of anisotropic galaxy clustering and are useful for extending them towards smaller scales in order to test theories of gravity and interacting dark-energy models.

show abstract

“…Ongoing studies seek to go beyond the 2-point statistics explored methods like the 3-point statistics (Sabiu et al 2016;Slepian et al 2017), the 4-point statistics (Sabiu et al 2019), the density field or voids (Ryden 1995;Sutter et al 2012;Bos et al 2012;Chan et al 2014;Cai et al 2015;Sutter et al 2014;Mao et al 2017;Ramanah et al 2019;Hamaus et al 2020;Lavaux & Jasche 2021), the Minkowski functionals (Minkowski 1903;Mecke et al 1994;Schmalzing & Gorski 1998;Kerscher et al 1998;Park & Kim 2010;Appleby et al 2020Appleby et al , 2021a, deep learning (Ravanbakhsh et al 2017;Mathuriya et al 2018;He et al 2019;Ntampaka et al 2019;Pan et al 2020;Li et al 2020;Mao et al 2021;Villaescusa-Navarro et al 2021;Ni et al 2021;Wu et al 2021), and so on. While all of them can explore the non-Gaussian clustering information encoded in the LSS, in this analysis we investigate a statistical tool namely the mark weighted correlation function (MCF; Beisbart & Kerscher 2000;Beisbart et al 2002;Gottlöber et al 2002;Sheth & Tormen 2004;Sheth et al 2005;Skibba et al 2006;White & Padmanabhan 2009;Satpathy et al 2019;…”

Section: Introductionmentioning

confidence: 99%

Cosmological constraints from the density gradient weighted correlation function

Xiao,

Yang,

Luo

et al. 2022

Preprint

Self Cite

View full text Add to dashboard Cite

The mark weighted correlation function (MCF) W (s, µ) is a computationally efficient statistical measure which can probe clustering information beyond that of the conventional 2-point statistics. In this work, we extend the traditional mark weighted statistics by using powers of the density field gradient |∇ρ/ρ| α as the weight, and use the angular dependence of the scale-averaged MCFs to constrain cosmological parameters. The analysis shows that the gradient based weighting scheme is statistically more powerful than the density based weighting scheme, while combining the two schemes together is more powerful than separately using either of them. Utilising the density weighted or the gradient weighted MCFs with α = 0.5, 1, we can strengthen the constraint on Ω m by factors of 2 or 4, respectively, compared with the standard 2-point correlation function, while simultaneously using the MCFs of the two weighting schemes together can be 1.25 times more statistically powerful than using the gradient weighting scheme alone. The mark weighted statistics may play an important role in cosmological analysis of future large-scale surveys. Many issues, including the possibility of using other types of weights, the influence of the bias on this statistics, as well as the usage of MCFs in the tomographic Alcock-Paczynski method, are worth further investigations.

show abstract

Probing scalar tensor theories for gravity in redshift space

Cited by 14 publications

References 57 publications

Real- and redshift-space halo clustering in f ( R ) cosmologies

Real- and redshift-space halo clustering in f ( R ) cosmologies

On the streaming model for redshift-space distortions

Cosmological constraints from the density gradient weighted correlation function

Contact Info

Product

Resources

About