2013/09/03 by Sourabh Banerjee, Ayanendranath Basu, Banerjee, Sourabh +9
Computer Science · Environmental Science · Mathematics · Physics and Astronomy · #62P35 (Primary) #65C60 (Secondary) #85A05 #85A15 #85A35 #Advanced Statistical Methods and Models #Applications (stat.AP) #Astrophysics of Galaxies (astro-ph.GA) #FOS: Computer and information sciences #FOS: Physical sciences #Gaussian Processes and Bayesian Inference #Impact of Light on Environment and Health #Solar and Stellar Astrophysics (astro-ph.SR) #Statistical and numerical algorithms #Target Tracking and Data Fusion in Sensor Networks #astro-ph.GA #astro-ph.SR #msc:62P35 #msc:65C60 #msc:85A05 #msc:85A15 #msc:85A35 #stat.AP
paper · pdf · doi:10.48550/arxiv.1309.0675
25 pages, 10 Figures. This version incorporates the suggestions made by the referees. To appear in SIAM/ASA Journal on Uncertainty Quantification
openalex publication_date 2013/09/03 · arxiv created 2014/08/15 · arxiv updated 2014/08/19 · openalex created_date 2022/10/02 · openalex updated_date 2026/07/28
We propose a method to estimate the location of the Sun in the disk of the Milky Way using a method based on the Hellinger distance and construct confidence sets on our estimate of the unknown location using a bootstrap based method. Assuming the Galactic disk to be two-dimensional, the sought solar location then reduces to the radial distance separating the Sun from the Galactic center and the angular separation of the Galactic center to Sun line, from a pre-fixed line on the disk. On astronomical scales, the unknown solar location is equivalent to the location of us earthlings who observe the velocities of a sample of stars in the neighborhood of the Sun. This unknown location is estimated by undertaking pairwise comparisons of the estimated density of the observed set of velocities of the sampled stars, with densities estimated using synthetic stellar velocity data sets generated at chosen locations in the Milky Way disk according to four base astrophysical models. The "match" between the pair of estimated densities is parameterized by the affinity measure based on the familiar Hellinger distance. We perform a novel cross-validation procedure to establish a desirable "consistency" property of the proposed method.