Untangling the White Dwarf Luminosity Functions

TL;DR

This paper explores a probabilistic method for analyzing white dwarf luminosity functions to better understand the Milky Way's star formation history, improving upon previous averaging techniques.

Contribution

It introduces a probabilistic approach using the generalized Schmidt density estimator to assign individual objects, enhancing the analysis of white dwarf luminosity functions.

Findings

Probabilistic method improves luminosity function analysis.

Enhanced understanding of Milky Way star formation history.

Method reduces information loss compared to previous approaches.

Abstract

The inversion of the white dwarf luminosity function provides an independent way to prove the past star formation history of the Milky Way independent of any cosmological models. In Rowell & Hambly (2011), the effective volume method uses the average properties of all the objects in a given bin, so a significant amount of information is lost in the early stage of the analysis, in this work, I explore the possibility of assigning objects individually in a probabilistic way using the generalised Schmidt density estimator (1/Vmax).