Estimating Distances from Parallaxes. VI. A Method for Inferring Distances and Transverse Velocities from Parallaxes and Proper Motions Demonstrated on Gaia Data Release 3

Author:

Bailer-Jones C. A. L.

Abstract

Abstract The accuracy of stellar distances inferred purely from parallaxes degrades rapidly with distance. Proper motion measurements, when combined with some idea of typical velocities, provide independent information on stellar distances. Here, I build a direction- and distance-dependent model of the distribution of stellar velocities in the Galaxy, then use this together with parallaxes and proper motions to infer kinegeometric distances and transverse velocities for stars in Gaia DR3. Using noisy simulations, I assess the performance of the method and compare its accuracy to purely parallax-based (geometric) distances. Over the whole Gaia catalog, kinegeometric distances are on average 1.25 times more accurate than geometric ones. This average masks a large variation in the relative performance, however. Kinegeometric distances are considerably better than geometric ones beyond several kpc, for example. On average, kinegeometric distances can be measured to an accuracy of 19% and velocities ( v α * 2 + v δ 2 ) to 16 km s−1 (median absolute deviations). In Gaia DR3, kinegeometric distances are smaller than geometric ones on average for distant stars, but the pattern is more complex in the bulge and disk. With the much more accurate proper motions expected in Gaia DR5, a further improvement in the distance accuracy by a factor of (only) 1.35 on average is predicted (with kinegeometric distances still 1.25 times more accurate than geometric ones). The improvement attained from proper motions is limited by the width of the velocity prior, in a way that the improvement from better parallaxes is not limited by the width of the distance prior.

Funder

Deutsches Zentrum für Luft- und Raumfahrt

Publisher

American Astronomical Society

Subject

Space and Planetary Science,Astronomy and Astrophysics

同舟云学术

1.学者识别学者识别

2.学术分析学术分析

3.人才评估人才评估

"同舟云学术"是以全球学者为主线,采集、加工和组织学术论文而形成的新型学术文献查询和分析系统,可以对全球学者进行文献检索和人才价值评估。用户可以通过关注某些学科领域的顶尖人物而持续追踪该领域的学科进展和研究前沿。经过近期的数据扩容,当前同舟云学术共收录了国内外主流学术期刊6万余种,收集的期刊论文及会议论文总量共计约1.5亿篇,并以每天添加12000余篇中外论文的速度递增。我们也可以为用户提供个性化、定制化的学者数据。欢迎来电咨询!咨询电话:010-8811{复制后删除}0370

www.globalauthorid.com

TOP

Copyright © 2019-2024 北京同舟云网络信息技术有限公司
京公网安备11010802033243号  京ICP备18003416号-3