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Modeling Dense Star Clusters in the Milky Way and beyond with the Cluster Monte Carlo Code

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Modeling Dense Star Clusters in the Milky Way and beyond with the Cluster Monte Carlo Code

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dc.contributor.author Rodriguez, Carl L. es_ES
dc.contributor.author Weatherford, Newlin C. es_ES
dc.contributor.author Coughlin, Scott C. es_ES
dc.contributor.author Amaro-Seoane, Pau es_ES
dc.contributor.author Breivik, Katelyn es_ES
dc.contributor.author Chatterjee, Sourav es_ES
dc.contributor.author Fragione, Giacomo es_ES
dc.contributor.author Kiroglu, Fulya es_ES
dc.contributor.author Kremer, Kyle es_ES
dc.contributor.author Rui, Nicholas Z. es_ES
dc.contributor.author Ye, Claire S. es_ES
dc.contributor.author Zevin, Michael es_ES
dc.contributor.author Rasio, Frederic A. es_ES
dc.date.accessioned 2023-07-24T18:02:33Z
dc.date.available 2023-07-24T18:02:33Z
dc.date.issued 2022-02-01 es_ES
dc.identifier.issn 0067-0049 es_ES
dc.identifier.uri http://hdl.handle.net/10251/195421
dc.description.abstract [EN] We describe the public release of the Cluster Monte Carlo (CMC) code, a parallel, star-by-star N-body code for modeling dense star clusters. CMC treats collisional stellar dynamics using Henon's method, where the cumulative effect of many two-body encounters is statistically reproduced as a single effective encounter between nearest-neighbor particles on a relaxation timescale. The star-by-star approach allows for the inclusion of additional physics, including strong gravitational three- and four-body encounters, two-body tidal and gravitational-wave captures, mass loss in arbitrary galactic tidal fields, and stellar evolution for both single and binary stars. The public release of CMC is pinned directly to the COSMIC population synthesis code, allowing dynamical star cluster simulations and population synthesis studies to be performed using identical assumptions about the stellar physics and initial conditions. As a demonstration, we present two examples of star cluster modeling: first, we perform the largest (N = 10(8)) star-by-star N-body simulation of a Plummer sphere evolving to core collapse, reproducing the expected self-similar density profile over more than 15 orders of magnitude; second, we generate realistic models for typical globular clusters, and we show that their dynamical evolution can produce significant numbers of black hole mergers with masses greater than those produced from isolated binary evolution (such as GW190521, a recently reported merger with component masses in the pulsational pair-instability mass gap). es_ES
dc.description.sponsorship We thank Kuldeep Sharma, Xiaoqi Yu, and Mike Grudic for testing this release of CMC and providing feedback, and Elena Gonzalez and Miguel Martinez for useful comments and discussions. This work was supported by NSF grant AST2009916 at Carnegie Mellon University, a New Investigator Research Grant to C.R. from the Charles E. Kaufman Foundation, and NSF grant AST-1716762 at Northwestern University. This work used the Extreme Science and Engineering Discovery Environment (XSEDE), which is supported by National Science Foundation grant No. ACI-1548562. Specifically, it used the Bridges-2 system, which is supported by NSF award No. ACI-1928147, at the Pittsburgh Supercomputing Center (PSC). N.C.W. acknowledges support from the CIERA Riedel Family Graduate Fellowship. F.K. acknowledges support from the Turkish Fulbright Commission. K.K. is supported by an NSF Astronomy and Astrophysics Postdoctoral Fellowship under award AST-2001751. P.A.-S. acknowledges support from the Ramon y Cajal Programme of the Ministry of Economy, Industry and Competitiveness of Spain, as well as the financial support of Programa Estatal de Generacion de Conocimiento (ref. PGC2018-096663-B-C43) (MCIU/FEDER). N.Z.R. acknowledges support from the Dominic Orr Graduate Fellowship at Caltech. es_ES
dc.language Inglés es_ES
dc.publisher American Astronomical Society es_ES
dc.relation.ispartof The Astrophysical Journal Supplement Series es_ES
dc.rights Reconocimiento (by) es_ES
dc.subject.classification MATEMATICA APLICADA es_ES
dc.title Modeling Dense Star Clusters in the Milky Way and beyond with the Cluster Monte Carlo Code es_ES
dc.type Artículo es_ES
dc.identifier.doi 10.3847/1538-4365/ac2edf es_ES
dc.relation.projectID info:eu-repo/grantAgreement/AEI/Plan Estatal de Investigación Científica y Técnica y de Innovación 2017-2020/PGC2018-096663-B-C43/ES/FISICA FUNDAMENTAL, DETECCION ACUSTICA Y ASTRONOMIA MULTI-MENSAJERO CON TELESCOPIOS DE NEUTRINOS EN LA UPV/ es_ES
dc.relation.projectID info:eu-repo/grantAgreement/NSF//ACI-1548562/ es_ES
dc.relation.projectID info:eu-repo/grantAgreement/MINECO//RYC-2015-17563/ES/RYC-2015-17563/ es_ES
dc.relation.projectID info:eu-repo/grantAgreement/NSF//AST-2001751/ es_ES
dc.relation.projectID info:eu-repo/grantAgreement/NSF//AST-2009916/ es_ES
dc.relation.projectID info:eu-repo/grantAgreement/NSF//AST-1716762/ es_ES
dc.relation.projectID info:eu-repo/grantAgreement/NSF//ACI-1928147/ es_ES
dc.rights.accessRights Abierto es_ES
dc.contributor.affiliation Universitat Politècnica de València. Escuela Técnica Superior de Ingeniería del Diseño - Escola Tècnica Superior d'Enginyeria del Disseny es_ES
dc.description.bibliographicCitation Rodriguez, CL.; Weatherford, NC.; Coughlin, SC.; Amaro-Seoane, P.; Breivik, K.; Chatterjee, S.; Fragione, G.... (2022). Modeling Dense Star Clusters in the Milky Way and beyond with the Cluster Monte Carlo Code. The Astrophysical Journal Supplement Series. 258(2):1-21. https://doi.org/10.3847/1538-4365/ac2edf es_ES
dc.description.accrualMethod S es_ES
dc.relation.publisherversion https://doi.org/10.3847/1538-4365/ac2edf es_ES
dc.description.upvformatpinicio 1 es_ES
dc.description.upvformatpfin 21 es_ES
dc.type.version info:eu-repo/semantics/publishedVersion es_ES
dc.description.volume 258 es_ES
dc.description.issue 2 es_ES
dc.relation.pasarela S\487084 es_ES
dc.contributor.funder Agencia Estatal de Investigación es_ES
dc.contributor.funder National Science Foundation, EEUU es_ES
dc.contributor.funder European Regional Development Fund es_ES
dc.contributor.funder Ministerio de Economía y Competitividad es_ES
dc.contributor.funder Ministerio de Economía, Industria y Competitividad es_ES


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