Dissemin is shutting down on January 1st, 2025

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American Astronomical Society, Astronomical Journal, 2(164), p. 62, 2022

DOI: 10.3847/1538-3881/ac7788

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wdwarfdate: A Python Package to Derive Bayesian Ages of White Dwarfs

This paper is made freely available by the publisher.
This paper is made freely available by the publisher.

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Abstract

Abstract White dwarfs have been successfully used as cosmochronometers in the literature; however, their reach has been limited in comparison to their potential. We present wdwarfdate, a publicly available Python package to derive the Bayesian age of a white dwarf, based on its effective temperature (T eff) and surface gravity (log g). We make this software easy to use with the goal of transforming the usage of white dwarfs as cosmochronometers into an accessible tool. The code estimates the mass and cooling age of the white dwarf, as well as the mass and main-sequence age of the progenitor star, allowing for a determination of the total age of the object. We test the reliability of the method by estimating the parameters of white dwarfs from previous studies and find agreement with the literature within measurement errors. In addition, we use wdwarfdate to infer the total age of 18 white dwarfs that are in possible wide binaries with M dwarfs; this leads to an additional set of age-calibrated low-mass stars. By analyzing the limitation of the code we find a typical uncertainty of 10% on the total age when both input parameters have uncertainties of 1%, and an uncertainty of 25% on the total age when T eff has an uncertainty of 10% and log g of 1%. Furthermore, wdwarfdate assumes single-star evolution and can be applied to calculate the total age of a white dwarf with parameters in the range 1500 ≲ T eff ≲ 90,000 K and 7.9 ≲ log g ≲ 9.3. Finally, the code assumes a uniform mixture of C/O in the core and single-star evolution, which is reliable in the range of white dwarf masses 0.45−1.1 M (7.73 ≲ log g ≲ 8.8).