Determining distances to stars statistically from photometry

TL;DR

This paper introduces a statistical method for estimating stellar distances in the Milky Way using large photometric datasets, improving understanding of the galaxy's structure.

Contribution

It defines statistical photometric parallax and demonstrates its application to mapping the Milky Way's stellar halo and tidal streams using SDSS data.

Findings

Mapped the Milky Way stellar halo density distribution

Applied statistical photometric parallax to large star samples

Used volunteer computing to optimize model parameters

Abstract

In determining the distances to stars within the Milky Way galaxy, one often uses photometric or spectroscopic parallax. In these methods, the type of each individual star is determined, and the absolute magnitude of that star type is compared with the measured apparent magnitude to determine individual distances. In this article, we define the term statistical photometric parallax, in which statistical knowledge of the absolute magnitudes of stellar populations is used to determine the underlying density distributions of those stars. This technique has been used to determine the density distribution of the Milky Way stellar halo and its component tidal streams, using very large samples of stars from the Sloan Digital Sky Survey. Most recently, the volunteer computing platform MilkyWay@home has been used to find the best fit model parameters for the density of these halo stars.