Abstract
The Large Magellanic Cloud (LMC) harbours a rich and diverse system of star clusters, whose ages, chemical abundances and positions provide information about the LMC history of star formation. We use Science Verification imaging data from the Dark Energy Survey (DES) to increase the census of known star clusters in the outer LMC and to derive physical parameters for a large sample of such objects using a spatially and photometrically homogeneous data set. Our sample contains 255 visually identified cluster candidates, of which 109 were not listed in any previous catalogue. We quantify the crowding effect for the stellar sample produced by the DES Data Management pipeline and conclude that the stellar completeness is <10 per cent inside typical LMC cluster cores. We therefore reanalysed the DES co-add images around each candidate cluster and remeasured positions and magnitudes for their stars. We also implement a maximum-likelihood method to fit individual density profiles and colour-magnitude diagrams. For 117 (from a total of 255) of the cluster candidates (28 uncatalogued clusters), we obtain reliable ages, metallicities, distance moduli and structural parameters, confirming their nature as physical systems. The distribution of cluster metallicities shows a radial dependence, with no clusters more metal rich than [Fe/H] ≃ -0.7 beyond 8 kpc from the LMC centre. The age distribution has two peaks at ≃1.2 and ≃2.7 Gyr.
Original language | English |
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Pages (from-to) | 519-541 |
Number of pages | 23 |
Journal | Monthly Notices of the Royal Astronomical Society |
Volume | 461 |
Issue number | 1 |
DOIs | |
State | Published - Sep 1 2016 |
Externally published | Yes |
Funding
ACKNOWLEDGEMENTS We would like to thank the anonymous referee for many useful suggestions. This paper has gone through internal review by the DES collaboration. AdP acknowledges financial support from the Brazilian Institution CNPq. EdB acknowledges financial support from the European Research Council (ERC-StG-335936, CLUSTERS). We are grateful for the extraordinary contributions of our CTIO colleagues and the DECam Construction, Commissioning and Science Verification teams in achieving the excellent instrument and telescope conditions that have made this work possible. The success of this project also relies critically on the expertise and dedication of the DES Data Management group. Funding for the DES Projects has been provided by the US Department of Energy, the US National Science Foundation, the Ministry of Science and Education of Spain, the Science and Technology FacilitiesCouncil of theUnitedKingdom, theHigher Education Funding Council for England, the NationalCenter for Supercomputing Applications at the University of Illinois at Urbana-Champaign, the Kavli Institute of Cosmological Physics at the University of Chicago, the Center for Cosmology and Astro-Particle Physics at the Ohio State University, the Mitchell Institute for Fundamental Physics and Astronomy at Texas A and M University, Financiadora de Estudos e Projetos, Fundaç ão Carlos Chagas Filho de Amparo à Pesquisa do Estado do Rio de Janeiro, Conselho Nacional de Desenvolvimento Científico e Tecnológico and the Ministério da Ciência, Tecnologia e Inovaç ão, the Deutsche Forschungsgemeinschaft and the Collaborating Institutions in the Dark Energy Survey. The Collaborating Institutions are Argonne National Laboratory, the University of California at Santa Cruz, the University of Cambridge, Centro de Investigaciones Enérgeticas, Medioambientales y Tecnológicas-Madrid, the University of Chicago, University College London, the DES-Brazil Consortium, the University of Edinburgh, the Eidgenössische Technische Hochschule (ETH) Zürich, Fermi National Accelerator Laboratory, the University of Illinois at Urbana-Champaign, the Institut de Ciències de l'Espai (IEEC/CSIC), the Institut de Física d'Altes Energies, Lawrence Berkeley National Laboratory, the Ludwig-Maximilians Universität München and the associated Excellence Cluster Universe, the University of Michigan, the National Optical Astronomy Observatory, the University of Nottingham, The Ohio State University, the University of Pennsylvania, the University of Portsmouth, SLAC National Accelerator Laboratory, Stanford University, the University of Sussex and Texas A and M University. The DES data management system is supported by the National Science Foundation under Grant Number AST-1138766. The DES participants from Spanish institutions are partially supported by MINECO under grants AYA2012-39559, ESP2013-48274, FPA2013-47986 and Centro de Excelencia Severo Ochoa SEV-2012-0234. Research leading to these results has received funding from the European Research Council under the European Union's Seventh Framework Programme (FP7/2007-2013) including ERC grant agreements 240672, 291329 and 306478.
Funders | Funder number |
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Centro de Excelencia Severo Ochoa | SEV-2012-0234 |
Collaborating Institutions are Argonne National Laboratory | |
Collaborating Institutions in the Dark Energy Survey | |
Institut de Ciències de l'Espai | |
Mitchell Institute for Fundamental Physics and Astronomy | |
National Science Foundation | AST-1138766 |
U.S. Department of Energy | |
University of Illinois at Urbana-Champaign | |
Stanford University | |
Fermilab | |
Lawrence Berkeley National Laboratory | |
University of California, Santa Cruz | |
University of Pennsylvania | |
Ohio State University | |
University of Chicago | |
University of Michigan | |
University of Portsmouth | |
National Centre for Supercomputing Applications | |
Seventh Framework Programme | 1138766, 240672, 306478, 335936, 291329 |
SLAC National Accelerator Laboratory | |
Science and Technology Facilities Council | |
Higher Education Funding Council for England | |
University College London | |
European Research Council | |
University of Nottingham | |
University of Sussex | |
University of Edinburgh | |
Deutsche Forschungsgemeinschaft | |
Eidgenössische Technische Hochschule Zürich | |
Ministerio de Economía y Competitividad | FPA2013-47986, AYA2012-39559, ESP2013-48274 |
Ministério da Ciência, Tecnologia e Inovação | |
Conselho Nacional de Desenvolvimento Científico e Tecnológico | |
Fundação Carlos Chagas Filho de Amparo à Pesquisa do Estado do Rio de Janeiro | |
Financiadora de Estudos e Projetos | |
Seventh Framework Programme | |
Ludwig-Maximilians-Universität München | |
Ministry of Education and Science of Ukraine | |
Institut de Física d'Altes Energies |
Keywords
- Galaxies: star clusters: general
- Magellanic Cloud
- Methods: statistical