Characterizing the astrometric errors in the Gaia catalogue Berry Holl
Characterizing the astrometric errors in the Gaia catalogue Berry Holl
Characterizing the astrometric errors in the Gaia catalogue Berry Holl
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Term<strong>in</strong>ologyxis a measured or derived quantity (e.g. parallax of a star):erroruncerta<strong>in</strong>tye = x − x trueRandom variability <strong>in</strong> measurement.unknown~knownDescribed by probability distributioncharacterized by e.g. mean, standard deviation, skewness etc.Normally estimated quite well:- by repeat<strong>in</strong>g (assum<strong>in</strong>g identical experiments),- observation process knowledge (e.g. photons Poisson statistics).biasNonzero mean <strong>in</strong> probability distribution.often unknownIf assumed zero leads to systematic <strong>errors</strong>.These are difficult to determ<strong>in</strong>e by repeat<strong>in</strong>g <strong>the</strong> experiment(e.g. observ<strong>in</strong>g Castor while you should be observ<strong>in</strong>g Pollux)31Why we need to understand <strong>errors</strong>Essential for <strong>in</strong>terpret<strong>in</strong>g data, examples:proper motion of stars <strong>in</strong> clusterData po<strong>in</strong>ts + standard uncerta<strong>in</strong>tyDeterm<strong>in</strong>e membershipy = µ i− exclud<strong>in</strong>g iσ diffOutcome does not critically depend onuncerta<strong>in</strong>ty (e.g. +/- 10% does not change result)valueCompute velocity dispersion (excl. 4)1 2 3 4 5 6 7 8 9 10data po<strong>in</strong>tσ 2 computed = σ2 <strong>in</strong>tr<strong>in</strong>sic + σ2 dataIf <strong>the</strong> latter two are of similar size, <strong>the</strong> datauncerta<strong>in</strong>ties need to be very well known.Depend<strong>in</strong>g on <strong>the</strong> application uncerta<strong>in</strong>ties can be of crucial importance!32