Capturing the short-term characteristics of a barred galaxy from a single snapshot

TL;DR

This paper introduces a novel method using topological data analysis to identify key structures and measure the pattern speed of a barred galaxy from a single snapshot, validated through simulations.

Contribution

It presents a new approach combining combinatorial and topological techniques to analyze star data for galaxy structure identification and pattern speed measurement from minimal observational data.

Findings

Method accurately identifies galaxy structures from single snapshots.

Results are consistent across different simulation scenarios.

Calibrated models match observed spiral arm features.

Abstract

Using a dataset of stars from a barred galaxy that provides instantaneous positions and velocities in the sky, we propose a method to identify its key structures, such as the central bar and spiral arms, and to determine the bar pattern speed in the short term. This is accomplished by applying combinatorial and topological data analysis techniques to the available star-state information set. To validate the methodology, we apply it to two scenarios: a test particle simulation and a N-body simulation, both evaluated when the bar is fully formed. In both cases, the results are robust and consistent. We then use these outcomes to calibrate a classical dynamical model and compute related structures, such as equilibrium points and invariant manifolds, which we verify align with the galaxy's spiral arms.