commensurability: a Python package for classifying astronomical orbits based on their toroid volume

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Hauptverfasser: Sarkar, Subhadeep, Petersen, Michael S.
Format: Preprint
Veröffentlicht: 2025
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author Sarkar, Subhadeep
Petersen, Michael S.
author_facet Sarkar, Subhadeep
Petersen, Michael S.
contents As a star orbits the center of its host galaxy, the trajectory is encompassed within a 3D toroid. The orbit probes all points in this toroid, unless its orbital frequencies exhibit integer ratios (commensurate frequencies), in which case a small sub-volume is traversed. commensurability is a Python package that implements a tessellation-based algorithm for identifying orbital families that satisfy commensurabilities by measuring the toroid volume traversed over orbit integration. Compared to standard orbit classification methods such as frequency analysis, tessellation analysis relies on configuration space properties alone, making classification results more robust to frequency instabilities or limited integration times. The package provides a framework for analyzing phase-space coordinates using tessellation analysis, including a subpackage for the implementation of the general tessellation algorithm. The package is to be used with a galactic dynamics library; it currently supports AGAMA, gala, and galpy.
format Preprint
id arxiv_https___arxiv_org_abs_2505_10617
institution arXiv
publishDate 2025
record_format arxiv
spellingShingle commensurability: a Python package for classifying astronomical orbits based on their toroid volume
Sarkar, Subhadeep
Petersen, Michael S.
Astrophysics of Galaxies
As a star orbits the center of its host galaxy, the trajectory is encompassed within a 3D toroid. The orbit probes all points in this toroid, unless its orbital frequencies exhibit integer ratios (commensurate frequencies), in which case a small sub-volume is traversed. commensurability is a Python package that implements a tessellation-based algorithm for identifying orbital families that satisfy commensurabilities by measuring the toroid volume traversed over orbit integration. Compared to standard orbit classification methods such as frequency analysis, tessellation analysis relies on configuration space properties alone, making classification results more robust to frequency instabilities or limited integration times. The package provides a framework for analyzing phase-space coordinates using tessellation analysis, including a subpackage for the implementation of the general tessellation algorithm. The package is to be used with a galactic dynamics library; it currently supports AGAMA, gala, and galpy.
title commensurability: a Python package for classifying astronomical orbits based on their toroid volume
topic Astrophysics of Galaxies
url https://arxiv.org/abs/2505.10617