Searching for white dwarfs candidates in Sloan Digital Sky Survey Data

TL;DR

This paper explores methods to identify white dwarf candidates in Sloan Digital Sky Survey data using photometric and spectral features, aiming to improve detection over previous approaches without relying on atmospheric models.

Contribution

It introduces new criteria for white dwarf candidate selection based on observational data, enhancing detection capabilities beyond prior methods.

Findings

Identified potential white dwarf candidates using new criteria.

Compared effectiveness of different selection criteria.

Improved detection rate over previous methods.

Abstract

Large amount of observational spectroscopic data are recently available from different observational projects, like Sloan Digital Sky Survey. It's become more urgent to identify white dwarfs stars based on data itself i.e. without modelling white dwarf atmospheres. In particular, existing methods of white dwarfs identification presented in Kleinman et al. (2004) and in Eisenstein et al. (2006) did not allow to find all the white dwarfs in examined data. We intend to test various criteria of searching for white dwarf candidates, based on photometric and spectral features.