Climbing halo merger trees with TreeFrog

Pascal J. Elahi, Rhys J.J. Poulton, Rodrigo J. Tobar, Rodrigo Cañas, Claudia Del P. Lagos, Chris Power, Aaron S.G. Robotham

Research output: Contribution to journalArticle

Abstract

We present TreeFrog, a massively parallel halo merger tree builder that is capable comparing different halo catalogues and producing halo merger trees. The code is written in c++11, use the MPI and OpenMP API's for parallelisation, and includes python tools to read/manipulate the data products produced. The code correlates binding energy sorted particle ID lists between halo catalogues, determining optimal descendant/progenitor matches using multiple snapshots, a merit function that maximises the number of shared particles using pseudo-radial moments, and a scheme for correcting halo merger tree pathologies. Focusing on VELOCIraptor catalogues for this work, we demonstrate how searching multiple snapshots spanning a dynamical time significantly reduces the number of stranded halos, those lacking a descendant or a progenitor, critically correcting poorly resolved halos. We present a new merit function that improves the distinction between primary and secondary progenitors, reducing tree pathologies. We find FOF accretion rates and merger rates show similar mass ratio dependence. The model merger rates from Poole, et al. [2017, 472, 3659] agree with the measured net growth of halos through mergers.

Original languageEnglish
Article numbere028
Number of pages16
JournalPublications of the Astronomical Society of Australia
Volume36
DOIs
Publication statusE-pub ahead of print - 5 Aug 2019

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merger
halos
pathology
catalogs
application programming interface
data products
accretion
mass ratios
lists
binding energy
moments
energy
rate
code
particle

Cite this

@article{003fc1db48d642a58c5d67b207a93c87,
title = "Climbing halo merger trees with TreeFrog",
abstract = "We present TreeFrog, a massively parallel halo merger tree builder that is capable comparing different halo catalogues and producing halo merger trees. The code is written in c++11, use the MPI and OpenMP API's for parallelisation, and includes python tools to read/manipulate the data products produced. The code correlates binding energy sorted particle ID lists between halo catalogues, determining optimal descendant/progenitor matches using multiple snapshots, a merit function that maximises the number of shared particles using pseudo-radial moments, and a scheme for correcting halo merger tree pathologies. Focusing on VELOCIraptor catalogues for this work, we demonstrate how searching multiple snapshots spanning a dynamical time significantly reduces the number of stranded halos, those lacking a descendant or a progenitor, critically correcting poorly resolved halos. We present a new merit function that improves the distinction between primary and secondary progenitors, reducing tree pathologies. We find FOF accretion rates and merger rates show similar mass ratio dependence. The model merger rates from Poole, et al. [2017, 472, 3659] agree with the measured net growth of halos through mergers.",
keywords = "dark matter, galaxies: evolution, galaxies: halos, methods: numerical",
author = "Elahi, {Pascal J.} and Poulton, {Rhys J.J.} and Tobar, {Rodrigo J.} and Rodrigo Ca{\~n}as and Lagos, {Claudia Del P.} and Chris Power and Robotham, {Aaron S.G.}",
year = "2019",
month = "8",
day = "5",
doi = "10.1017/pasa.2019.18",
language = "English",
volume = "36",
journal = "Publications of the Astronomincal Society of Australia (PASA)",
issn = "1323-3580",
publisher = "Cambridge University Press",

}

Climbing halo merger trees with TreeFrog. / Elahi, Pascal J.; Poulton, Rhys J.J.; Tobar, Rodrigo J.; Cañas, Rodrigo; Lagos, Claudia Del P.; Power, Chris; Robotham, Aaron S.G.

In: Publications of the Astronomical Society of Australia, Vol. 36, e028, 05.08.2019.

Research output: Contribution to journalArticle

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T1 - Climbing halo merger trees with TreeFrog

AU - Elahi, Pascal J.

AU - Poulton, Rhys J.J.

AU - Tobar, Rodrigo J.

AU - Cañas, Rodrigo

AU - Lagos, Claudia Del P.

AU - Power, Chris

AU - Robotham, Aaron S.G.

PY - 2019/8/5

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KW - dark matter

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