The search for the lost attractor
Abstract
N-body systems characterized by inverse square attractive forces may display a self similar collapse known as the gravo-thermal catastrophe. In star clusters, collapse is halted by binary stars, and a large fraction of Milky Way clusters may have already reached this phase. It has been speculated -- with guidance from simulations -- that macroscopic variables such as central density and velocity dispersion are governed post-collapse by an effective, low-dimensional system of ODEs. It is still hard to distinguish chaotic, low dimensional motion, from high dimensional stochastic noise. Here we apply three machine learning tools to state-of-the-art dynamical simulations to constrain the post collapse dynamics: topological data analysis (TDA) on a lag embedding of the relevant time series, Sparse Identification of Nonlinear Dynamics (SINDY), and Tests of Accuracy with Random Points (TARP).
Cite
@article{arxiv.2311.16306,
title = {The search for the lost attractor},
author = {Mario Pasquato and Syphax Haddad and Pierfrancesco Di Cintio and Alexandre Adam and Pablo Lemos and Noé Dia and Mircea Petrache and Ugo Niccolò Di Carlo and Alessandro Alberto Trani and Laurence Perreault-Levasseur and Yashar Hezaveh},
journal= {arXiv preprint arXiv:2311.16306},
year = {2023}
}
Comments
Accepted by ML4PS workshop at NeurIPS 2023