Subhaloes gone Notts: the clustering properties of subhaloes

We present a study of the substructure finder dependence of subhalo clustering in the Aquarius Simulation. We run 11 different subhalo finders on the haloes of the Aquarius Simulation and study their differences in the density profile, mass fraction and two-point correlation function of subhaloes in...

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Main Authors: Pujol, Arnau, Gaztanaga, Enrique, Giocoli, Carlo, Knebe, Alexander, Pearce, Frazer R., Skibba, Ramin A., Ascasibar, Yago, Behroozi, Peter, Elahi, Pascal, Han, Jiaxin, Lux, Hanni, Muldrew, Stuart I., Neyrinck, Mark, Onions, Julian, Potter, Doug, Tweed, Dylan
Format: Article
Published: Oxford University Press 2014
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Online Access:https://eprints.nottingham.ac.uk/42643/
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author Pujol, Arnau
Gaztanaga, Enrique
Giocoli, Carlo
Knebe, Alexander
Pearce, Frazer R.
Skibba, Ramin A.
Ascasibar, Yago
Behroozi, Peter
Elahi, Pascal
Han, Jiaxin
Lux, Hanni
Muldrew, Stuart I.
Neyrinck, Mark
Onions, Julian
Potter, Doug
Tweed, Dylan
author_facet Pujol, Arnau
Gaztanaga, Enrique
Giocoli, Carlo
Knebe, Alexander
Pearce, Frazer R.
Skibba, Ramin A.
Ascasibar, Yago
Behroozi, Peter
Elahi, Pascal
Han, Jiaxin
Lux, Hanni
Muldrew, Stuart I.
Neyrinck, Mark
Onions, Julian
Potter, Doug
Tweed, Dylan
author_sort Pujol, Arnau
building Nottingham Research Data Repository
collection Online Access
description We present a study of the substructure finder dependence of subhalo clustering in the Aquarius Simulation. We run 11 different subhalo finders on the haloes of the Aquarius Simulation and study their differences in the density profile, mass fraction and two-point correlation function of subhaloes in haloes. We also study the mass and vmax dependence of subhalo clustering. As the Aquarius Simulation has been run at different resolutions, we study the convergence with higher resolutions. We find that the agreement between finders is at around the 10 per cent level inside R200 and at intermediate resolutions when a mass threshold is applied, and better than 5 per cent when vmax is restricted instead of mass. However, some discrepancies appear in the highest resolution, underlined by an observed resolution dependence of subhalo clustering. This dependence is stronger for the smallest subhaloes, which are more clustered in the highest resolution, due to the detection of subhaloes within subhaloes (the sub-subhalo term). This effect modifies the mass dependence of clustering in the highest resolutions. We discuss implications of our results for models of subhalo clustering and their relation with galaxy clustering.
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spelling nottingham-426432020-05-04T16:45:04Z https://eprints.nottingham.ac.uk/42643/ Subhaloes gone Notts: the clustering properties of subhaloes Pujol, Arnau Gaztanaga, Enrique Giocoli, Carlo Knebe, Alexander Pearce, Frazer R. Skibba, Ramin A. Ascasibar, Yago Behroozi, Peter Elahi, Pascal Han, Jiaxin Lux, Hanni Muldrew, Stuart I. Neyrinck, Mark Onions, Julian Potter, Doug Tweed, Dylan We present a study of the substructure finder dependence of subhalo clustering in the Aquarius Simulation. We run 11 different subhalo finders on the haloes of the Aquarius Simulation and study their differences in the density profile, mass fraction and two-point correlation function of subhaloes in haloes. We also study the mass and vmax dependence of subhalo clustering. As the Aquarius Simulation has been run at different resolutions, we study the convergence with higher resolutions. We find that the agreement between finders is at around the 10 per cent level inside R200 and at intermediate resolutions when a mass threshold is applied, and better than 5 per cent when vmax is restricted instead of mass. However, some discrepancies appear in the highest resolution, underlined by an observed resolution dependence of subhalo clustering. This dependence is stronger for the smallest subhaloes, which are more clustered in the highest resolution, due to the detection of subhaloes within subhaloes (the sub-subhalo term). This effect modifies the mass dependence of clustering in the highest resolutions. We discuss implications of our results for models of subhalo clustering and their relation with galaxy clustering. Oxford University Press 2014-03-11 Article PeerReviewed Pujol, Arnau, Gaztanaga, Enrique, Giocoli, Carlo, Knebe, Alexander, Pearce, Frazer R., Skibba, Ramin A., Ascasibar, Yago, Behroozi, Peter, Elahi, Pascal, Han, Jiaxin, Lux, Hanni, Muldrew, Stuart I., Neyrinck, Mark, Onions, Julian, Potter, Doug and Tweed, Dylan (2014) Subhaloes gone Notts: the clustering properties of subhaloes. Monthly Notices of the Royal Astronomical Society, 438 (4). pp. 3205-3221. ISSN 1365-2966 methods: numerical galaxies: haloes cosmology: theory https://academic.oup.com/mnras/article-lookup/doi/10.1093/mnras/stt2446 doi:10.1093/mnras/stt2446 doi:10.1093/mnras/stt2446
spellingShingle methods: numerical
galaxies: haloes
cosmology: theory
Pujol, Arnau
Gaztanaga, Enrique
Giocoli, Carlo
Knebe, Alexander
Pearce, Frazer R.
Skibba, Ramin A.
Ascasibar, Yago
Behroozi, Peter
Elahi, Pascal
Han, Jiaxin
Lux, Hanni
Muldrew, Stuart I.
Neyrinck, Mark
Onions, Julian
Potter, Doug
Tweed, Dylan
Subhaloes gone Notts: the clustering properties of subhaloes
title Subhaloes gone Notts: the clustering properties of subhaloes
title_full Subhaloes gone Notts: the clustering properties of subhaloes
title_fullStr Subhaloes gone Notts: the clustering properties of subhaloes
title_full_unstemmed Subhaloes gone Notts: the clustering properties of subhaloes
title_short Subhaloes gone Notts: the clustering properties of subhaloes
title_sort subhaloes gone notts: the clustering properties of subhaloes
topic methods: numerical
galaxies: haloes
cosmology: theory
url https://eprints.nottingham.ac.uk/42643/
https://eprints.nottingham.ac.uk/42643/
https://eprints.nottingham.ac.uk/42643/