S2-star dynamics probing the Galaxy core cluster

TL;DR

This paper uses neural networks and scattering models to analyze the orbit precession of the S2 star, providing insights into the star density of the Milky Way's core cluster.

Contribution

It introduces a physics-informed neural network approach combined with scattering theory to estimate the star density in the galactic core.

Findings

Critical star density for observed precession is approximately 8.3×10^6 pc^-3.

Higher star densities would cause orbit perturbations exceeding observations.

Precession analysis constrains the core star density within a specific confidence interval.

Abstract

The star cluster surrounding the supermassive black hole in the center of Milky Way is probed using the data on the S2 star. The value of precession found at the physics-informed neural networks (PINN) analysis of the S2 data is used to consider the role of the scattering of S2 star on stars of the cluster, described by a random force given by the Holtsmark distribution. The critical value for the star density of the core cluster for which the observed precession value by PINN lies inside 70% confidence interval (between 15% and 85% quantiles) around the median of precession due to scattering, is obtained as n_crit \approx 8.3 10^6 pc^-3, that is at higher star densities the perturbation of the orbit of S2 would exceed the observed one.