Abstract

Astrometric surveys such as Gaia and LSST will measure parallaxes for hundreds of millions of stars. Yet they will not measure a single distance. Rather, a distance must be estimated from a parallax. In this didactic article, I show that doing this is not trivial once the fractional parallax error is larger than about 20%, which will be the case for about 80% of stars in the Gaia catalog. Estimating distances is an inference problem in which the use of prior assumptions is unavoidable. I investigate the properties and performance of various priors and examine their implications. A supposed uninformative uniform prior in distance is shown to give very poor distance estimates (large bias and variance). Any prior with a sharp cut-off at some distance has similar problems. The choice of prior depends on the information one has available—and is willing to use—concerning, e.g., the survey and the Galaxy. I demonstrate that a simple prior which decreases asymptotically to zero at infinite distance has good performance, accommodates nonpositive parallaxes, and does not require a bias correction.

Keywords

ParallaxStarsMeasure (data warehouse)Prior probabilityVariance (accounting)GalaxyInferenceCosmic distance ladderPhysicsSimple (philosophy)Distance measuresAstrophysicsComputer scienceMathematicsBayesian probabilityStatisticsAstronomyArtificial intelligenceRedshift

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Publication Info

Year
2015
Type
article
Volume
127
Issue
956
Pages
994-1009
Citations
485
Access
Closed

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Cite This

Coryn A. L. Bailer‐Jones (2015). Estimating Distances from Parallaxes. Publications of the Astronomical Society of the Pacific , 127 (956) , 994-1009. https://doi.org/10.1086/683116

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DOI
10.1086/683116