Neural Network Analysis of S2-Star Dynamics: Extended mass

Autor:	Galikyan, N., Khlghatyan, Sh., Kocharyan, A. A., Gurzadyan, V. G.
Rok vydání:	2024
Předmět:	General Relativity and Quantum Cosmology Astrophysics - Instrumentation and Methods for Astrophysics
Zdroj:	Eur. Phys. J. Plus 139, 246 (2024)
Druh dokumentu:	Working Paper
DOI:	10.1140/epjp/s13360-024-05042-0
Popis:	Physics-informed neural network (PINN) analysis of the dynamics of S-stars in the vicinity of the supermassive black hole in the Galactic center is performed within General Relativity treatment. The aim is to reveal the role of possible extended mass (dark matter) configuration in the dynamics of the S-stars, in addition to the dominating central black hole's mass. The PINN training fails to detect the extended mass perturbation in the observational data for S2 star within the existing data accuracy, and the precession constraint indicates no signature of extended mass up to 0.01% of the central mass inside the apocenter of S2. Neural networks analysis thus confirm its efficiency in the analysis of the S-star dynamics. Comment: 6 pages, 3 figs; Eur Phys J Plus (in press)
Databáze:	arXiv
Externí odkaz:	http://arxiv.org/abs/2403.09748 Zobrazit plný text záznamu View this record from Arxiv