Revealing modified gravity signals in matter and halo hierarchical clustering

Revealing modified gravity signals in matter and halo hierarchical clustering We use a set of N-body simulations employing a modified gravity (MG) model with Vainshtein screening to study matter and halo hierarchical clustering. As test-case scenarios we consider two normal branch Dvali-Gabadadze-Porrati (nDGP) gravity models with mild and strong growth rate enhancement. We study higher-order correlation functions ξn(R) up to n=9 and associated reduced cumulants Sn(R)≡ξn(R)/σ(R)2n-2. We find that the matter probability distribution functions are strongly affected by the fifth force on scales up to 50h-1  Mpc, and the deviations from general relativity (GR) are maximized at z=0. For reduced cumulants Sn, we find that at small scales R≤6h-1  Mpc the MG is characterized by lower values, with the deviation growing from 7% in the reduced skewness up to even 40% in S5. To study the halo clustering we use a simple abundance matching and divide haloes into thee fixed number density samples. The halo two-point functions are weakly affected, with a relative boost of the order of a few percent appearing only at the smallest pair separations (r≤5h-1  Mpc). In contrast, we find a strong MG signal in Sn(R)’s, which are enhanced compared to GR. The strong model exhibits a >3σ level signal at various scales for all halo samples and in all cumulants. In this context, we find that the reduced kurtosis to be an especially promising cosmological probe of MG. Even the mild nDGP model leaves a 3σ imprint at small scales R≤3h-1  Mpc, while the stronger model deviates from a GR signature at nearly all scales with a significance of >5σ. Since the signal is persistent in all halo samples and over a range of scales, we advocate that the reduced kurtosis estimated from galaxy catalogs can potentially constitute a strong MG-model discriminatory as well as GR self-consistency test. http://www.deepdyve.com/assets/images/DeepDyve-Logo-lg.png Physical Review D American Physical Society (APS)

Revealing modified gravity signals in matter and halo hierarchical clustering

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Revealing modified gravity signals in matter and halo hierarchical clustering

Abstract

We use a set of N-body simulations employing a modified gravity (MG) model with Vainshtein screening to study matter and halo hierarchical clustering. As test-case scenarios we consider two normal branch Dvali-Gabadadze-Porrati (nDGP) gravity models with mild and strong growth rate enhancement. We study higher-order correlation functions ξn(R) up to n=9 and associated reduced cumulants Sn(R)≡ξn(R)/σ(R)2n-2. We find that the matter probability distribution functions are strongly affected by the fifth force on scales up to 50h-1  Mpc, and the deviations from general relativity (GR) are maximized at z=0. For reduced cumulants Sn, we find that at small scales R≤6h-1  Mpc the MG is characterized by lower values, with the deviation growing from 7% in the reduced skewness up to even 40% in S5. To study the halo clustering we use a simple abundance matching and divide haloes into thee fixed number density samples. The halo two-point functions are weakly affected, with a relative boost of the order of a few percent appearing only at the smallest pair separations (r≤5h-1  Mpc). In contrast, we find a strong MG signal in Sn(R)’s, which are enhanced compared to GR. The strong model exhibits a >3σ level signal at various scales for all halo samples and in all cumulants. In this context, we find that the reduced kurtosis to be an especially promising cosmological probe of MG. Even the mild nDGP model leaves a 3σ imprint at small scales R≤3h-1  Mpc, while the stronger model deviates from a GR signature at nearly all scales with a significance of >5σ. Since the signal is persistent in all halo samples and over a range of scales, we advocate that the reduced kurtosis estimated from galaxy catalogs can potentially constitute a strong MG-model discriminatory as well as GR self-consistency test.
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Publisher
The American Physical Society
Copyright
Copyright © © 2017 American Physical Society
ISSN
1550-7998
eISSN
1550-2368
D.O.I.
10.1103/PhysRevD.96.023515
Publisher site
See Article on Publisher Site

Abstract

We use a set of N-body simulations employing a modified gravity (MG) model with Vainshtein screening to study matter and halo hierarchical clustering. As test-case scenarios we consider two normal branch Dvali-Gabadadze-Porrati (nDGP) gravity models with mild and strong growth rate enhancement. We study higher-order correlation functions ξn(R) up to n=9 and associated reduced cumulants Sn(R)≡ξn(R)/σ(R)2n-2. We find that the matter probability distribution functions are strongly affected by the fifth force on scales up to 50h-1  Mpc, and the deviations from general relativity (GR) are maximized at z=0. For reduced cumulants Sn, we find that at small scales R≤6h-1  Mpc the MG is characterized by lower values, with the deviation growing from 7% in the reduced skewness up to even 40% in S5. To study the halo clustering we use a simple abundance matching and divide haloes into thee fixed number density samples. The halo two-point functions are weakly affected, with a relative boost of the order of a few percent appearing only at the smallest pair separations (r≤5h-1  Mpc). In contrast, we find a strong MG signal in Sn(R)’s, which are enhanced compared to GR. The strong model exhibits a >3σ level signal at various scales for all halo samples and in all cumulants. In this context, we find that the reduced kurtosis to be an especially promising cosmological probe of MG. Even the mild nDGP model leaves a 3σ imprint at small scales R≤3h-1  Mpc, while the stronger model deviates from a GR signature at nearly all scales with a significance of >5σ. Since the signal is persistent in all halo samples and over a range of scales, we advocate that the reduced kurtosis estimated from galaxy catalogs can potentially constitute a strong MG-model discriminatory as well as GR self-consistency test.

Journal

Physical Review DAmerican Physical Society (APS)

Published: Jul 15, 2017

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