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A catalog of 159,238 white dwarf ages

Published online by Cambridge University Press:  09 October 2020

Ted von Hippel Open the ORCID record for Ted von Hippel [Opens in a new window] ,
Adam Moss ,
Isabelle Kloc ,
Natalie Moticska ,
Jimmy Sargent ,
Elliot Robinson ,
David Stenning ,
David van Dyk ,
Elizabeth Jeffery Open the ORCID record for Elizabeth Jeffery [Opens in a new window]  and
Morgan Fouesneau
...Show all authors
Ted von Hippel
Affiliation:
Embry-Riddle Aeronautical University, Daytona Beach, FL, USA
Adam Moss
Affiliation:
University of Oklahoma, Norman, OK, USA
Isabelle Kloc
Affiliation:
Embry-Riddle Aeronautical University, Daytona Beach, FL, USA
Natalie Moticska
Affiliation:
Embry-Riddle Aeronautical University, Daytona Beach, FL, USA
Jimmy Sargent
Affiliation:
Embry-Riddle Aeronautical University, Daytona Beach, FL, USA
Elliot Robinson
Affiliation:
Embry-Riddle Aeronautical University, Daytona Beach, FL, USA
David Stenning
Affiliation:
Imperial College, London, UK
David van Dyk
Affiliation:
Imperial College, London, UK
Elizabeth Jeffery
Affiliation:
California Polytechnic State University, San Luis Obispo, CA, USA
Morgan Fouesneau
Affiliation:
Max Planck Institute for Astronomy, Heidelberg, Germany
Coryn Bailer-Jones
Affiliation:
Max Planck Institute for Astronomy, Heidelberg, Germany
Rights & Permissions [Opens in a new window]

Abstract

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We employ Pan-STARRS photometry, Gaia trigonometric parallaxes, modern stellar evolution and atmosphere models, and our Bayesian fitting approach to determine cooling and total ages for 159,238 white dwarfs. In many cases we are able to derive precise ages (better than 5%) for individual white dwarfs. These results are meant for broad use within the white dwarf and stellar astrophysics communities and we plan to make available on-line the posterior distributions for cooling age, total age, initial stellar mass, and other parameters.

Keywords

Galaxy: stellar contentstars: evolutionstars: white dwarfs
Type
Contributed Papers
Information
Proceedings of the International Astronomical Union , Volume 15 , Symposium S357: White Dwarfs as Probes of Fundamental Physics: Tracers of Planetary, Stellar and Galactic Evolution , October 2019 , pp. 188 - 191
Copyright
© International Astronomical Union 2020

References

Bergeron, P., Wesemael, F., & Beauchamp, A. 1995, PASP, 107, 104710.1086/133661CrossRefGoogle Scholar
Bischoff-Kim, A. & Montgomery, M. H. 2018, AJ, 155, 18710.3847/1538-3881/aab70eCrossRefGoogle Scholar
Bossini, D. et al. 2019, AA, 623, A10810.1051/0004-6361/201834693CrossRefGoogle Scholar
Bressan, A., Marigo, P., Girardi, L., Salasnich, B., Dal Cero, C., Rubele, S., & Nanni, A. 2012, MNRAS, 427, 12710.1111/j.1365-2966.2012.21948.xCrossRefGoogle Scholar
Cacciari, C., Pancino, E., & Bellazzini, M. 2016, AN, 337, 899Google Scholar
DeGennaro, S., von Hippel, T., Jefferys, W. H., Stein, N., van Dyk, D. A., & Jeffery, E. 2009, ApJ, 696, 1210.1088/0004-637X/696/1/12CrossRefGoogle Scholar
Fouesneau, M., Rix, H-W. von Hippel, T., Hogg, D. W. & Tian, H., 2019, ApJ, 870, 1Google Scholar
Gentile Fusillo, N. P. et al. 2019, MNRAS, 482, 457010.1093/mnras/sty3016CrossRefGoogle Scholar
Hills, S., von Hippel, T., Courteau, S., & Geller, A. M. 2015, AJ, 149, 9410.1088/0004-6256/149/3/94CrossRefGoogle Scholar
Hodapp, K. W. et al. 2004, AN, 325, 636Google Scholar
Jeffery, E. J., von Hippel, T., DeGennaro, S., Stein, N., Jefferys, W. H., & van Dyk, D. 2011, ApJ, 730, 3510.1088/0004-637X/730/1/35CrossRefGoogle Scholar
Jeffery, E. J., von Hippel, T., van Dyk, D. A., Stenning, D. C., Robinson, E., Stein, N., & Jefferys, W. H. 2016, ApJ, 828, 7910.3847/0004-637X/828/2/79CrossRefGoogle Scholar
O’Malley, E. M., von Hippel, T., & van Dyk, D. A. 2013, ApJ, 775, 110.1088/0004-637X/775/1/1CrossRefGoogle Scholar
Stein, N. M., van Dyk, D. A., von Hippel, T., DeGennaro, S., Jeffery, E. J., Jefferys, W. H. et al. 2013, Statistical Analysis and Data Mining, 6, 3410.1002/sam.11172CrossRefGoogle Scholar
Stenning, D. C., Wagner-Kaiser, R., Robinson, E., van Dyk, D. A., von Hippel, T., Sarajedini, A., & Stein, N. 2016, ApJ, 826, 4110.3847/0004-637X/826/1/41CrossRefGoogle Scholar
van Dyk, D. A., DeGennaro, S., Stein, N., Jefferys, W. H., & von Hippel, T. 2009, Annals of Applied Statistics, 3, 11710.1214/08-AOAS219CrossRefGoogle Scholar
von Hippel, T., Jefferys, W. H., Scott, J., Stein, N., Winget, D. E., DeGennaro, S., Dam, A., & Jeffery, E. 2006, ApJ, 645, 143610.1086/504369CrossRefGoogle Scholar
Wagner-Kaiser, R., Stenning, D., Robinson, E., von Hippel, T., Sarajedini, A., van Dyk, D. A., Stein, N., & Jefferys, W. H. 2016a, ApJ, 826, 4210.3847/0004-637X/826/1/42CrossRefGoogle Scholar
Wagner-Kaiser, R., Stenning, D. C., Sarajedini, A., von Hippel, T., van Dyk, D. A., Robinson, E., Stein, N., & Jefferys, W. H. 2016b, MNRAS, 463, 376810.1093/mnras/stw2247CrossRefGoogle Scholar
Williams, K. A., Bolte, M., & Koester, D. 2009, ApJ, 693, 35510.1088/0004-637X/693/1/355CrossRefGoogle Scholar