UZH-Logo

Maintenance Infos

Nonlinear clustering in models with primordial non-Gaussianity: The halo model approach


Smith, R E; Desjacques, V; Marian, L (2011). Nonlinear clustering in models with primordial non-Gaussianity: The halo model approach. Physical Review D, 83(4):043526.

Abstract

We develop the halo model of large-scale structure as an accurate tool for probing primordial non-Gaussianity. In this study we focus on understanding the matter clustering at several redshifts in the context of primordial non-Gaussianity that is a quadratic correction to the local Gaussian potential, characterized by the parameter fNL. In our formulation of the halo model we pay special attention to the effect of halo exclusion and show that this can potentially solve the long-standing problem of excess power on large scales in this model. The halo model depends on the mass function, clustering of halo centers, and the density profiles. We test these ingredients using a large ensemble of high-resolution Gaussian and non-Gaussian numerical simulations, covering fNL={0,+100,-100}. In particular, we provide a first exploration of how halo density profiles change in the presence of primordial non-Gaussianity. We find that for fNL positive (negative) high-mass haloes have an increased (decreased) core density, so being more (less) concentrated than in the Gaussian case. We also examine the halo bias and show that, if the halo model is correct, then there is a small asymmetry in the scale dependence of the bias on very large scales, which arises because the Gaussian bias must be renormalized. We show that the matter power spectrum is modified by ˜2.5% and ˜3.5% on scales &ktilde;1.0hMpc-1 at z=0 and z=1, respectively. Our halo model calculation reproduces the absolute amplitude to within ≲10% and the ratio of non-Gaussian to Gaussian spectra to within ≲1%. We also measure the matter correlation function and find similarly good levels of agreement between the halo model and the data. We anticipate that this modeling will be useful for constraining fNL from measurements of the shear correlation function in future weak lensing surveys such as Euclid.

Abstract

We develop the halo model of large-scale structure as an accurate tool for probing primordial non-Gaussianity. In this study we focus on understanding the matter clustering at several redshifts in the context of primordial non-Gaussianity that is a quadratic correction to the local Gaussian potential, characterized by the parameter fNL. In our formulation of the halo model we pay special attention to the effect of halo exclusion and show that this can potentially solve the long-standing problem of excess power on large scales in this model. The halo model depends on the mass function, clustering of halo centers, and the density profiles. We test these ingredients using a large ensemble of high-resolution Gaussian and non-Gaussian numerical simulations, covering fNL={0,+100,-100}. In particular, we provide a first exploration of how halo density profiles change in the presence of primordial non-Gaussianity. We find that for fNL positive (negative) high-mass haloes have an increased (decreased) core density, so being more (less) concentrated than in the Gaussian case. We also examine the halo bias and show that, if the halo model is correct, then there is a small asymmetry in the scale dependence of the bias on very large scales, which arises because the Gaussian bias must be renormalized. We show that the matter power spectrum is modified by ˜2.5% and ˜3.5% on scales &ktilde;1.0hMpc-1 at z=0 and z=1, respectively. Our halo model calculation reproduces the absolute amplitude to within ≲10% and the ratio of non-Gaussian to Gaussian spectra to within ≲1%. We also measure the matter correlation function and find similarly good levels of agreement between the halo model and the data. We anticipate that this modeling will be useful for constraining fNL from measurements of the shear correlation function in future weak lensing surveys such as Euclid.

Citations

25 citations in Web of Science®
18 citations in Scopus®
Google Scholar™

Altmetrics

Downloads

84 downloads since deposited on 19 Feb 2012
31 downloads since 12 months
Detailed statistics

Additional indexing

Item Type:Journal Article, refereed, original work
Communities & Collections:07 Faculty of Science > Institute for Computational Science
Dewey Decimal Classification:530 Physics
Language:English
Date:February 2011
Deposited On:19 Feb 2012 12:02
Last Modified:05 Apr 2016 14:55
Publisher:American Physical Society
ISSN:1550-7998 (P) 1089-4918 (E)
Additional Information:Publisher’s Note: Nonlinear clustering in models with primordial non-Gaussianity: The halo model approach [Phys. Rev. D 83, 043526 (2011)] Robert E. Smith, Vincent Desjacques, and Laura Marian (Received 3 March 2011; published 11 March 2011) DOI: 10.1103/PhysRevD.83.069901 PACS numbers: 98.80.�k, 99.10.Fg This paper was published online on 24 February 2011 with Fig. 7 being inadvertently replaced by a duplicate of Fig. 6. The paper has been corrected as of 3 March 2011. The figures are correct in the printed version of the journal.
Publisher DOI:https://doi.org/10.1103/PhysRevD.83.043526
Related URLs:http://arxiv.org/abs/1009.5085

Download

[img]
Preview
Content: Accepted Version
Filetype: PDF (Version 1)
Size: 2MB
View at publisher
[img]
Preview
Content: Accepted Version
Filetype: PDF (Version 2)
Size: 2MB

TrendTerms

TrendTerms displays relevant terms of the abstract of this publication and related documents on a map. The terms and their relations were extracted from ZORA using word statistics. Their timelines are taken from ZORA as well. The bubble size of a term is proportional to the number of documents where the term occurs. Red, orange, yellow and green colors are used for terms that occur in the current document; red indicates high interlinkedness of a term with other terms, orange, yellow and green decreasing interlinkedness. Blue is used for terms that have a relation with the terms in this document, but occur in other documents.
You can navigate and zoom the map. Mouse-hovering a term displays its timeline, clicking it yields the associated documents.

Author Collaborations