wdwarfdate: A Python Package to Derive Bayesian Ages of White Dwarfs
Rocio Kiman (1,2,3, 4), Siyi Xu (5), Jacqueline K. Faherty (3),, Jonathan Gagne (6, 7), Ruth Angus (3,8, 9), Timothy D. Brandt (10),, Sarah L. Casewell (11), Kelle L. Cruz (2,3,4, 8) ((1) Kavli Institute, for Theoretical Physics, University of California, Santa Barbara, (2)

TL;DR
The paper introduces wdwarfdate, a Python package that estimates the Bayesian total age of white dwarfs using their temperature and gravity, making cosmochronology more accessible.
Contribution
It provides a user-friendly software tool for deriving white dwarf ages, including progenitor and cooling ages, with validated accuracy and defined parameter ranges.
Findings
Achieves about 10% total age uncertainty with 1% input errors.
Provides age estimates consistent with previous studies.
Defines parameter ranges for reliable age determination.
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 (Teff) and surface gravity (logg). 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. By analyzing the limitation of the code we find a typical uncertainty of…
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