Improvements in stellar ages in the era of

Alexey Mints1,2,3 Saskia Hekker2,3 1Leibniz-Institut f¨urAstrophysik Potsdam (AIP), Potsdam, Germany

2Max Planck Institute for Solar System Research, G¨ottingen,Germany

3Stellar Astrophysics Centre, Aarhus University, Denmark

Data Method Recently, the Gaia mission [1, 2] provided precise for over 1.5 billion We use the bayesian isochrone fitting tool UniDAM to stars. We make use of these data by including a prior into the Unified tool derive ages, and distances for stars, using the to estimate Distances, Ages, and Masses (UniDAM, [3, 4]) in a consistent way. effective temperature, surface gravity, , Gaia We provide estimates of stellar masses, ages and distances, for a large set of stars. parallax and 2MASS/AllWISE as inputs. Estimates with Estimates with A soft upper limit prior is put on the extinction. The Survey Gaia DR2 Reference Survey Gaia DR2 Reference method is summarized in [3, 16]. UniDAM takes into parallaxes parallaxes account non-gaussianity and possible multi-modality of APOGEE (DR14) 139,253 [5] LAMOST GAC (DR2)* 321,194 [6] Gaia-ESO (DR2) 5,140 [7] LAMOST GAC VB (DR2)* 927,972 [6] the Probability Distribution Functions (PDFs), provid- GALAH (DR1) 321,836 [8] RAVE (DR5) 347,741 [9] ing a set of possible solutions for each star. GCS 8,079 [10] RAVE on* 362,405 [11] UniDAM source code and resulting catalogue are public LAMOST (DR4) 4,405,230 [12] SEGUE 108,471 [13] LAMOST CANNON* 406,870 [14] TESS-HERMES (DR1) 14,669 [15] (see QR-codes at the bottom). Total see to the right 5,439,104 Number of sources with Gaia DR2 overlap, for which at least one solution was obtained, for different surveys. *- LAMOST GAC, LAMOST-Cannon and RAVE-on were processed but not included into the total, as they contain the same stars as LAMOST DR4 and RAVE DR5.

Results

We run UniDAM on surveys listed in the table above. In the figure, we show the comparison of median uncertainties for distance modulus σµd (left) and log(age) στ (right) as a function of the estimated distance modulus µd for the RAVE-on survey. The red line shows results obtained without Gaia parallaxes; blue line shows results with parallaxes; black line shows our precision predictions for Gaia end-of-mission Gaia quality. Dashed and dotted lines are the naive Gaia parallax to distance modulus uncertainty propagation for DR2 (F2(µd)) and for end-of-mission uncertainty values (F1(µd)). In the figure we indicate with labels regions where Gaia parallax uncertainty dominates the final uncertainty (A), where Gaia DR2 parallax has almost no impact (C) and the intermediate region (B). In the right figure we indicate with a vertical line the distance modulus beyond which the use of Gaia DR2 parallax has little impact on the age uncertainty (improvement is less than 10 percent, compare red and blue lines). The decrease m of the log(age) uncertainty with distance for stars with µd < 7 .5 is caused by the decrease of the fraction of main-sequence stars, for which ages are very uncertain, with distance. Similar plots for other surveys are presented in our paper [2].

Acknowledgments References

The research leading to the presented results has received funding from the [1] Gaia Collaboration, T. Prusti, J. H. J. de Bruijne, et al. The Gaia mission. A&A, 595:A1, November 2016. European Research Council under the European Community’s Seventh Framework Programme (FP7/2007- 2013)/ERC grant agreement (No 338251, [2] Gaia Collaboration, A. G. A. Brown, A. Vallenari, et al. Gaia Data Release 2. Summary of the contents and survey properties. A&A, 616:A1, August 2018. StellarAges). [3] Mints, A. and S. Hekker. A Unified tool to estimate Distances, Ages, and Masses (UniDAM) from spectrophotometric data. A&A, 604:A108, August 2017. [4] Mints, Alexey and Saskia Hekker. UniDAM: Unified tool to estimate Distances, Ages, and Masses. Astrophysics Source Code Library, April 2018. [5] C. P. Ahn, R. Alexandroff, C. Allende Prieto, et al. The Tenth Data Release of the : First Spectroscopic Data from the SDSS-III Apache Point Observatory Galactic Evolution Experiment. ApJS, 211:17, April 2014. Links [6] M. S. Xiang, X. W. Liu, H. B. Yuan, et al. LAMOST Spectroscopic Survey of the Galactic Anticentre (LSS-GAC): the second release of value-added catalogues. MNRAS, 467:1890–1914, May 2017. [7] G. Gilmore, S. Randich, M. Asplund, et al. The Gaia-ESO Public Spectroscopic Survey. The Messenger, 147:25–31, March 2012. [8] S. Martell, S. Sharma, S. Buder, et al. The GALAH Survey: Observational Overview and Gaia DR1 companion. ArXiv e-prints, September 2016. [9] A. Kunder, G. Kordopatis, M. Steinmetz, et al. The Experiment (RAVE): Fifth Data Release. ArXiv e-prints, September 2016. [10] L. Casagrande, R. Sch¨onrich,M. Asplund, et al. New constraints on the chemical evolution of the solar neighbourhood and Galactic disc(s). Improved astrophysical parameters for the Geneva-Copenhagen Survey. A&A, 530:A138, June 2011. [11] A. R. Casey, K. Hawkins, D. W. Hogg, et al. The RAVE-on Catalog of Stellar Atmospheric Parameters and Chemical Abundances for Chemo-dynamic Studies in the Gaia Era. ApJ, 840:59, May 2017. [12] A.-L. Luo, Y.-H. Zhao, G. Zhao, et al. The first data release (DR1) of the LAMOST regular survey. Research in Astronomy and Astrophysics, 15:1095, August 2015. [13] B. Yanny, C. Rockosi, H. J. Newberg, et al. SEGUE: A Spectroscopic Survey of 240,000 Stars with g = 14-20. AJ, 137:4377–4399, May 2009. [14] A. Y. Q. Ho, M. K. Ness, D. W. Hogg, et al. Survey Cross-Calibration with The Cannon: Apogee-scale Stellar Labels from Lamost Spectra. ArXiv e-prints, January 2016. [15] S. Sharma, D. Stello, S. Buder, et al. The TESS-HERMES survey Data Release 1: high-resolution spectroscopy of the TESS southern continuous viewing zone. ArXiv e-prints, July 2017. [16] Mints, Alexey and Saskia Hekker. Isochrone fitting in the Gaia era. A&A, 618:A54, October 2018. Links to UniDAM homepage (left), source code (center) and catalogue paper (right) http://www.mps.mpg.de/sage [email protected]