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DarkMix: Mixture Models for the Detection and Characterization of Dark Matter Halos

Hurtado-Gil, Lluís and Kuhn, Michael A. and Arnalte-Mur, Pablo and Feigelson, Eric D. and Martínez, Vicent (2022) DarkMix: Mixture Models for the Detection and Characterization of Dark Matter Halos. Astrophysical Journal, 939 (1). Art. No. 34. ISSN 0004-637X. doi:10.3847/1538-4357/ac88d4.

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Dark matter simulations require statistical techniques to properly identify and classify their halos and structures. Nonparametric solutions provide catalogs of these structures but lack the additional learning of a model-based algorithm and might misclassify particles in merging situations. With mixture models, we can simultaneously fit multiple density profiles to the halos that are found in a dark matter simulation. In this work, we use the Einasto profile to model the halos found in a sample of the Bolshoi simulation, and we obtain their location, size, shape, and mass. Our code is implemented in the R statistical software environment and can be accessed on

Item Type:Article
Related URLs:
URLURL TypeDescription
Hurtado-Gil, Lluís0000-0001-9674-1345
Kuhn, Michael A.0000-0002-0631-7514
Arnalte-Mur, Pablo0000-0003-0791-7885
Feigelson, Eric D.0000-0002-5077-6734
Martínez, Vicent0000-0002-9937-0532
Additional Information:This work has been funded by project PID2019-109592GB-I00/AEI/10.13039/501100011033 from the Spanish Ministerio de Ciencia e Innovación—Agencia Estatal de Investigación, by the Project of excellence Prometeo/2020/085 from the Conselleria d’Innovació Universitats, Ciència i Societat Digital de la Generalitat Valenciana, and by the Acción Especial UV-INV-AE19-1199364 from the Vicerrectorado de Investigación de la Universitat de València. The CosmoSim database used in this paper is a service by the Leibniz-Institute for Astrophysics Potsdam (AIP). The MultiDark database was developed in cooperation with the Spanish MultiDark Consolider Project CSD2009-00064. The Bolshoi and MultiDark simulations have been performed within the Bolshoi project of the University of California High-Performance AstroComputing Center (UC-HiPACC) and were run at the NASA Ames Research Center. The MultiDark-Planck (MDPL) and the BigMD simulation suite have been performed in the Supermuc supercomputer at LRZ using time granted by PRACE. E.D.F. thanks Penn State’s Center for Astrostatistics for an environment where cross-disciplinary research can be effectively pursued.
Funding AgencyGrant Number
Ministerio de Ciencia, Innovación y Universidades (MCIU)PID2019-109592GB-100/AEI/10.13039/501100011033
Conselleria de Innovación, Universidades, Ciencia y Sociedad Digital, Generalitat ValencianaPrometeo/2020/085
Universitat de ValènciaUV-INV-AE19-1199364
Issue or Number:1
Record Number:CaltechAUTHORS:20221116-602322900.14
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Usage Policy:No commercial reproduction, distribution, display or performance rights in this work are provided.
ID Code:117892
Deposited By: Research Services Depository
Deposited On:30 Nov 2022 18:53
Last Modified:30 Nov 2022 18:53

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