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Open cluster remnants in low-density Galactic fields

Published online by Cambridge University Press:  18 January 2010

D. B. Pavani
Affiliation:
Universidade Federal de Pelotas (UFPel), Campus Universitário, s/n, Caixa Postal 354, CEP 96010-900 Pelotas, RS, Brazil email: dpavani@if.ufrgs.br
L. O. Kerber
Affiliation:
Universidade Estadual de Santa Cruz (UESC), Campus Soane Nazaré de Andrade km 16 Rodovia Ilhéus–Itabuna CEP 45662-000, Ilhéus, Bahia, Brazil e-mail: kerber@astro.iag.usp.br, maciel@astro.iag.usp.br
E. Bica
Affiliation:
Universidade Federal do Rio Grande do Sul (UFRGS), Av. Bento Goncalves 9500, Caixa Postal 15051, CEP 91501-970 Porto Alegre, RS, Brazil email: bica@if.ufrgs.br
W. J. Maciel
Affiliation:
Instituto de Astronomia, Geofísica e Ciências Atmosféricas da Universidade de São Paulo (IAG/USP), Rua do Matão, 1226, Cidade Universitária, CEP 05508-090 São Paulo/SP, Brazil
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Abstract

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Open cluster remnants (OCRs) are fundamental objects to investigate open cluster dissolution processes (e.g., Bica et al. 2001; Carraro 2002; Pavani et al. 2003; Carraro et al. 2007; Pavani & Bica 2007). They are defined as poorly populated concentrations of stars, with enough members to show evolutionary sequences in colour–magnitude diagrams (CMDs) as a result of the dynamical evolution of an initially more massive physical system. An OCR is intrinsically poorly populated, which makes its differentiation from field-star fluctuations difficult. Among the possible approaches to establish the nature of OCRs, we adopted CMD analysis combined with a robust statistical tool applied to 2mass data. In addition, photometry is the main information source available for possible OCRs (POCRs). We developed a statistical diagnostic tool to analyse the CMDs of POCRs and verify them as physical systems, explore membership probabilityies taking into account field contamination and derive age, distance and reddening values in a self-consistent way. We present the results of our analysis of 88 POCRs that are part of a larger sample that is widely distributed across the sky, with a significant density contrast of bright stars compared to the Galactic field. The 88 objects are projected onto low-density Galactic fields, at relatively high latitudes (|b| > 15°). Studies of larger POCR samples will provide a better understanding of OCR properties and constraints for theoretical models, including new insights into the evolution of open clusters and their dissolution rates. The results of this ongoing survey will provide a general picture of these fossil stellar systems and their connection to Galactic-disk evolution.

Type
Contributed Papers
Copyright
Copyright © International Astronomical Union 2010

References

Bica, E., Santiago, B. X., Dutra, C. M., Dottori, H., de Oliveira, M. R., & Pavani, D. 2001, A&A, 366, 827Google Scholar
Carraro, G. 2002, A&A, 385, 471Google Scholar
Carraro, G., de La Fuente Marcos, R., Villanova, S., Moni Bidin, C., de La Fuente Marcos, C., Solivella, G., & Baumgardt, H. 2007, A&A, 466, 931Google Scholar
Girardi, L., Bertelli, G., Bressan, A., Chiosi, C., Groenewegen, M. A. T.Marigo, P., Salasnich, B., & Weiss, A. 2002, A&A, 391, 185Google Scholar
Kerber, L. O, Santiago, B. X., Castro, R., & Valls–Gabaud, D. 2002, A&A, 390, 121Google Scholar
Kerber, L. O. & Santiago, B. X. 2005, A&A, 435, 77Google Scholar
Miguell, K. J., Rich, R. M., Shara, M., & Fall, S. M. 1996, A&A, 111, 2314Google Scholar
Pavani, D. B., Bica, E., Ahumada, A. V., & Clariá, J. J. 2003, A&A, 399, 113Google Scholar
Pavani, D. B. & Bica, E. 2007, A&A, 468, 139Google Scholar
Reid, M. J. 1993, ARA&A, 31 345Google Scholar