Direct Solver Aiming at Elimination of Systematic Errors in 3D Stellar Positions

The determination of three-dimensional positions and velocities of stars based on the observations collected by a space telescope suffers from the uncertainty of random as well as systematic errors. The systematic errors are introduced by imperfections of the telescope’s optics and detectors as well as in the pointing accuracy of the satellite. The fine art of astrometry consists of heuristically finding the best possible calibration model that will account for and remove these systematic errors. Since this is a process based on trial and error, appropriate software is needed that is efficient enough to solve the system of astrometric equations and reveal the astrometric parameters of stars for the given calibration model within a reasonable time. In this work, we propose a novel architecture and corresponding prototype of a direct solver optimized for running on supercomputers. The main advantages expected of this direct method over an iterative one are the numerical robustness, accuracy of the method, and the explicit calculation of the variance-covariance matrix for the estimation of the accuracy and correlation of the unknown parameters. This solver is supposed to handle astrometric systems with billions of equations within several hours. To reach the desired performance, state-of-the-art libraries for parallel computing are used along with the hand-crafted subroutines optimized for hybrid parallelism model and advanced vector extensions of modern CPUs. The developed solver is tested using the mock science data related to the Japan Astrometry Satellite Mission for INfrared Exploration (JASMINE).