Hostname: page-component-586b7cd67f-t7fkt Total loading time: 0 Render date: 2024-11-26T16:07:53.304Z Has data issue: false hasContentIssue false
  • English
  • Français

The Hubble Catalog of Variables (HCV)

Published online by Cambridge University Press:  29 August 2019

K. V. Sokolovsky ,
A. Z. Bonanos ,
P. Gavras ,
M. Yang ,
D. Hatzidimitriou ,
M. I. Moretti ,
A. Karampelas ,
I. Bellas-Velidis ,
Z. Spetsieri  and
E. Pouliasis
...Show all authors
K. V. Sokolovsky
Affiliation:
IAASARS, National Observatory of Athens, Greece email: [email protected] Sternberg Astronomical Inst. MSU, Moscow, Russia Astro Space Center, LPI RAS, Moscow, Russia
A. Z. Bonanos
Affiliation:
IAASARS, National Observatory of Athens, Greece email: [email protected]
P. Gavras
Affiliation:
IAASARS, National Observatory of Athens, Greece email: [email protected]
M. Yang
Affiliation:
IAASARS, National Observatory of Athens, Greece email: [email protected]
D. Hatzidimitriou
Affiliation:
IAASARS, National Observatory of Athens, Greece email: [email protected] Department of Physics, National and Kapodistrian University of Athens, Greece
M. I. Moretti
Affiliation:
IAASARS, National Observatory of Athens, Greece email: [email protected] INAF-Osservatorio Astronomico di Capodimonte, Napoli, Italy
A. Karampelas
Affiliation:
IAASARS, National Observatory of Athens, Greece email: [email protected] American Community Schools of Athens, Halandri, Greece
I. Bellas-Velidis
Affiliation:
IAASARS, National Observatory of Athens, Greece email: [email protected]
Z. Spetsieri
Affiliation:
IAASARS, National Observatory of Athens, Greece email: [email protected] Department of Physics, National and Kapodistrian University of Athens, Greece
E. Pouliasis
Affiliation:
IAASARS, National Observatory of Athens, Greece email: [email protected] Department of Physics, National and Kapodistrian University of Athens, Greece
I. Georgantopoulos
Affiliation:
IAASARS, National Observatory of Athens, Greece email: [email protected]
V. Charmandaris
Affiliation:
IAASARS, National Observatory of Athens, Greece email: [email protected]
K. Tsinganos
Affiliation:
IAASARS, National Observatory of Athens, Greece email: [email protected]
N. Laskaris
Affiliation:
Athena Research and Innovation Center, Maroussi, Greece
G. Kakaletris
Affiliation:
Athena Research and Innovation Center, Maroussi, Greece
A. Nota
Affiliation:
Space Telescope Science Institute, Baltimore, MD, USA European Space Agency, Research and Scientific Support Dept., Baltimore, MD, USA
D. Lennon
Affiliation:
European Space Astronomy Centre, Madrid, Spain
C. Arviset
Affiliation:
European Space Astronomy Centre, Madrid, Spain
B. C. Whitmore
Affiliation:
Space Telescope Science Institute, Baltimore, MD, USA
T. Budavari
Affiliation:
The Johns Hopkins University, Baltimore, MD, USA
R. Downes
Affiliation:
Space Telescope Science Institute, Baltimore, MD, USA
S. Lubow
Affiliation:
Space Telescope Science Institute, Baltimore, MD, USA
A. Rest
Affiliation:
Space Telescope Science Institute, Baltimore, MD, USA
L. Strolger
Affiliation:
Space Telescope Science Institute, Baltimore, MD, USA
R. White
Affiliation:
Space Telescope Science Institute, Baltimore, MD, USA
Rights & Permissions [Opens in a new window]

Abstract

Core share and HTML view are not available for this content. However, as you have access to this content, a full PDF is available via the ‘Save PDF’ action button.

The Hubble Source Catalog (HSC) combines lists of sources detected on images obtained with the WFPC2, ACS and WFC3 instruments aboard the Hubble Space Telescope (HST) and now available in the Hubble Legacy Archive. The catalogue contains time-domain information for about two million of its sources detected using the same instrument and filter on at least five HST visits. The Hubble Catalog of Variables (HCV) aims to identify HSC sources showing significant brightness variations. A magnitude-dependent threshold in the median absolute deviation of photometric measurements (an outlier-resistant measure of light-curve scatter) is adopted as the variability detection statistic. It is supplemented with a cut in χred2 that removes sources with large photometric errors. A pre-processing procedure involving bad image identification, outlier rejection and computation of local magnitude zero-point corrections is applied to the HSC light-curves before computing the variability detection statistics. About 52 000 HSC sources have been identified as candidate variables, among which 7,800 show variability in more than one filter. Visual inspection suggests that ∼70% of the candidates detected in multiple filters are true variables, while the remaining ∼30% are sources with aperture photometry corrupted by blending, imaging artefacts or image processing anomalies. The candidate variables have AB magnitudes in the range 15–27m, with a median of 22m. Among them are the stars in our own and nearby galaxies, and active galactic nuclei.

Keywords

Techniques: photometricstars: variables: other
Type
Contributed Papers
Information
Proceedings of the International Astronomical Union , Volume 14 , Symposium S339: Southern Horizons in Time-Domain Astronomy , November 2017 , pp. 91 - 94
Copyright
© International Astronomical Union 2019 

References

Anderson, J., & van der Marel, R. P. 2010, ApJ, 710, 103210.1088/0004-637X/710/2/1032CrossRefGoogle Scholar
Andrae, R., Schulze-Hartung, T., & Melchior, P. 2010, arXiv:1012.3754Google Scholar
Bellini, A., Anderson, J., & Bedin, L. R. 2011, PASP, 123, 62210.1086/659878CrossRefGoogle Scholar
Bertin, E., & Arnouts, S. 1996, A&AS, 117, 393Google Scholar
Brown, T. M., Ferguson, H. C., Smith, E., et al. 2004, AJ, 127, 2738CrossRefGoogle Scholar
Budavári, T., & Lubow, S. H. 2012, ApJ, 761, 18810.1088/0004-637X/761/2/188CrossRefGoogle Scholar
Czerny, B., Beaton, R., Bejger, M., et al. 2018, Space Sci. Rev, 214, #32CrossRefGoogle Scholar
Freedman, W. L., Madore, B. F., Gibson, B. K., 2001, ApJ, 553, 4710.1086/320638CrossRefGoogle Scholar
Gavras, P., Bonanos, A. Z., Bellas-Velidis, I., et al. 2017, in: Brescia, M. (eds.), Astroinformatics, Proc. IAUS 325 (CUP: Cambridge, UK), p. 369Google Scholar
Hack, W. J., Dencheva, N., Fruchter, A. S., et al. 2012, AAS Meeting Abstracts #220, 135.15Google Scholar
Huang, C. D., Riess, A. G., Hoffmann, S. L., et al. 2018, arXiv:1801.02711Google Scholar
Jenkner, H., Doxsey, R. E., Hanisch, R. J., et al. 2006, ADASS XV, 351, 406Google Scholar
Koekemoer, A. M., Ellis, R. S., McLure, R. J., et al. 2013, ApJS, 209, 310.1088/0067-0049/209/1/3CrossRefGoogle Scholar
Lasker, B. M., Lattanzi, M. G., McLean, B. J., et al. 2008, AJ, 136, 73510.1088/0004-6256/136/2/735CrossRefGoogle Scholar
Nascimbeni, V., Bedin, L. R., Heggie, D. C., et al. 2014, MNRAS, 442, 238110.1093/mnras/stu930CrossRefGoogle Scholar
Riess, A. G., Rodney, S. A., Scolnic, D. M., et al. 2018, ApJ, 853, 126CrossRefGoogle Scholar
Sokolovsky, K. V., Gavras, P., Karampelas, A., et al. 2017, MNRAS, 464, 27410.1093/mnras/stw2262CrossRefGoogle Scholar
Sokolovsky, K., Bonanos, A., Gavras, P., et al. 2017, in: Catelan, M. & Gieren, W. (eds.), Wide-Field Variability Surveys: A 21st Century Perspective, EPJ Web of Conferences, 152, 02005CrossRefGoogle Scholar
Whitmore, B., Lindsay, K., & Stankiewicz, M. 2008, ADASS XVII, 394, 481Google Scholar
Whitmore, B. C., Allam, S. S., Budavári, T., et al. 2016, AJ, 151, 13410.3847/0004-6256/151/6/134CrossRefGoogle Scholar
Yang, M., Bonanos, A. Z., Gavras, P., et al. 2017, arXiv:1711.11491Google Scholar
Zhang, M., Bakos, G. Á., P enev, K., et al. 2016, PASP, 128, 035001CrossRefGoogle Scholar