Building an Optimal Census of the Solar Neighborhood with Pan-STARRS Data

TL;DR

This paper evaluates how to optimize the creation of a reliable and complete catalog of nearby stars within 100 parsecs using Pan-STARRS astrometric data, focusing on proper motion and parallax cuts.

Contribution

It introduces an optimal method for selecting nearby stars in Pan-STARRS data by analyzing proper motion and parallax thresholds to maximize catalog reliability and completeness.

Findings

Achieves 99% reliability with specific cuts

Attains 60% completeness with optimized thresholds

Provides guidelines for catalog construction based on galactic latitude

Abstract

We estimate the fidelity of solar neighborhood (D < 100 pc) catalogs soon to be derived from Pan-STARRS astrometric data. We explore two quantities used to measure catalog quality: completeness, the fraction of desired sources included in a catalog; and reliability, the fraction of entries corresponding to desired sources. We show that the main challenge in identifying nearby objects with Pan-STARRS will be reliably distinguishing these objects from distant stars, which are vastly more numerous. We explore how joint cuts on proper motion and parallax will impact catalog reliability and completeness. Using synthesized astrometry catalogs, we derive optimum parallax and proper motion cuts to build a census of the solar neighborhood with the Pan-STARRS 3 Pi Survey. Depending on the Galactic latitude, a parallax cut pi / sigma pi > 5 combined with a proper motion cut ranging from mu / sigma mu > 1-8 achieves 99% reliability and 60% completeness.