Measuring the local dark matter density

TL;DR

This paper investigates the challenges in accurately measuring the local dark matter density using stellar motion data, emphasizing the importance of systematic errors and applying advanced statistical methods to real data.

Contribution

It introduces a Monte Carlo Markov Chain approach to assess data quality needs and re-evaluates local dark matter density estimates with realistic error considerations.

Findings

Systematic errors outweigh observational errors in density measurements.

Collisionless simulations help identify data quality requirements.

Revised local dark matter density estimates with realistic error bars.

Abstract

We examine systematic problems in determining the local matter density from the vertical motion of stars, i.e. the 'Oort limit'. Using collisionless simulations and a Monte Carlo Markov Chain technique, we determine the data quality required to detect local dark matter at its expected density. We find that systematic errors are more important than observational errors and apply our technique to Hipparcos data to reassign realistic error bars to the local dark matter density.