Alcock–Paczyński effect on void-finding

Under the assumption of statistical isotropy, and in the absence of directional selection effects, a stack of voids is expected to be spherically symmetric, which makes it an excellent object to use for an Alcock–Paczyński (AP) test. This test is commonly carried out using the void-galaxy cross-correlation function (CCF), which has emerged as a competitive probe, especially in combination with the galaxy-galaxy auto-correlation function. Current studies of the AP effect around voids assume that void-centre positions are influenced by the choice of fiducial cosmology in the same way as galaxy positions. We show that this assumption, though prevalent in the literature, is complicated by the response of void-finding algorithms to shifts in tracer positions. Using stretched simulation boxes to emulate the AP effect, we investigate how the void-galaxy CCF changes due to its presence, revealing an additional effect imprinted in the CCF that must be accounted for. The effect originates from the response of void finders to the distorted tracer field – which leads to reduction of the amplitude of the AP signal in the CCF – and thus depends on the specific void-finding algorithm used. We present results for four different void-finding packages, namely REVOLVER , VIDE , voxel , and the spherical void finder in the Pylians3 library, demonstrating how incorrect treatment of the AP effect results in biases in the recovered parameters, regardless of the technique used. Finally, we propose a method to alleviate this issue without resorting to complex and finder-specific modelling of the void-finder response to AP.

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Publication Details

Journal
Astronomy and Astrophysics
Published
2024-10-03
DOI
https://doi.org/10.1051/0004-6361/202451358
Citations
4
Primary Topic
Bayesian Methods and Mixture Models
Type
article
Field-Weighted Citation Impact
1.39

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article

Alcock–Paczyński effect on void-finding

Will J. Percival, Slađana Radinović, S. Nadathur, Alex Woodfinden et al.
4 citations
Astronomy and Astrophysics
Bayesian Methods and Mixture Models
1.39
article

Alcock–Paczyński effect on void-finding

Will J. Percival, Slađana Radinović, S. Nadathur, Alex Woodfinden, Elena Massara, Hans A. Winther, E. Paillas, Tristan Sohrab Fraser
article en
4 citations

Abstract

Under the assumption of statistical isotropy, and in the absence of directional selection effects, a stack of voids is expected to be spherically symmetric, which makes it an excellent object to use for an Alcock–Paczyński (AP) test. This test is commonly carried out using the void-galaxy cross-correlation function (CCF), which has emerged as a competitive probe, especially in combination with the galaxy-galaxy auto-correlation function. Current studies of the AP effect around voids assume that void-centre positions are influenced by the choice of fiducial cosmology in the same way as galaxy positions. We show that this assumption, though prevalent in the literature, is complicated by the response of void-finding algorithms to shifts in tracer positions. Using stretched simulation boxes to emulate the AP effect, we investigate how the void-galaxy CCF changes due to its presence, revealing an additional effect imprinted in the CCF that must be accounted for. The effect originates from the response of void finders to the distorted tracer field – which leads to reduction of the amplitude of the AP signal in the CCF – and thus depends on the specific void-finding algorithm used. We present results for four different void-finding packages, namely REVOLVER , VIDE , voxel , and the spherical void finder in the Pylians3 library, demonstrating how incorrect treatment of the AP effect results in biases in the recovered parameters, regardless of the technique used. Finally, we propose a method to alleviate this issue without resorting to complex and finder-specific modelling of the void-finder response to AP.

Astronomy and AstrophysicsVol. 691
Institute of Space Sciences (ES), University of Waterloo (CA), Perimeter Institute (CA), University of Oslo (NO), University of Portsmouth (GB)
Innovation, Science and Economic Development Canada, Government of Canada, Norges Forskningsråd, Institut Périmètre de physique théorique, Ministry of Colleges and Universities, Science and Technology Facilities Council
Openalex Percentile: Top 15%
Bayesian Methods and Mixture Models
1.39
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