Dynamical Data Mining Captures Disc-Halo Couplings that Structure Galaxies
Alexander Johnson, Michael S. Petersen, Kathryn V. Johnston, Martin D., Weinberg

TL;DR
This paper introduces a novel dynamical data mining method combining basis function expansions and multichannel singular spectrum analysis to detect and analyze disc-halo coupling modes in simulated galaxies, revealing insights into galactic structure evolution.
Contribution
The study demonstrates the effectiveness of BFE+mSSA in uncovering multi-component disc-halo modes and disequilibrium signals in galaxy simulations, advancing analysis techniques in galactic dynamics.
Findings
Detected two multi-component disc-halo dipole modes in a simulated galaxy.
Modes influence surface density features up to 10% of the stellar disc.
Identified persistent periodic signals from initial disequilibrium conditions.
Abstract
Studying coupling between different galactic components is a challenging problem in galactic dynamics. Using basis function expansions (BFEs) and multichannel singular spectrum analysis (mSSA) as a means of dynamical data mining, we discover evidence for two multi-component disc-halo dipole modes in a Milky-Way-like simulated galaxy. One of the modes grows throughout the simulation, while the other decays throughout the simulation. The multi-component disc-halo modes are driven primarily by the halo, and have implications for the structural evolution of galaxies, including observations of lopsidedness and other non-axisymmetric structure. In our simulation, the modes create surface density features up to 10 per cent relative to the equilibrium model stellar disc. While the simulated galaxy was constructed to be in equilibrium, BFE+mSSA also uncovered evidence of persistent periodic…
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Taxonomy
TopicsSpectroscopy and Chemometric Analyses · Statistical and numerical algorithms · Blind Source Separation Techniques
