Comparing phylogenetic trees of stars with spectral graph distances
Abstract
Phylogenetic trees offer a hierarchical representation of chemical similarities among stars, from which their evolutionary histories can, in principle, be reconstructed. Simulation-based work suggests that phylogenetic trees built under different chemical evolution scenarios carry distinguishable structural imprints, but whether existing methods can detect this signal in practice is unclear. We evaluate distance measures, both classical tree-based and graph-theoretical, for comparing phylogenetic trees, seeking measures robust to observational noise that separate trees built from populations with distinct chemical enrichment histories. We construct Neighbor-Joining trees from chemical abundance vectors of solar twins and of stars associated with the Milky Way (MW) disk, Gaia-Sausage-Enceladus (GSE), and the Sagittarius dwarf spheroidal galaxy (Sgr). Two benchmark tests assess stability under input perturbations within the same evolutionary history and discriminative power between distinct stellar populations used as proxies for different evolutionary histories. Tree metrics rapidly saturate under perturbations of order the typical uncertainty (≈2σ, or ≈0.05 dex per element) and fail to distinguish trees when leaf sets differ. In contrast, spectral distances vary smoothly with perturbation amplitude and provide a label-invariant method for comparing trees built from disjoint sets of stars. Among the spectral measures evaluated, the Laplacian spectral distance shows the most consistent separation across population pairs, while the normalized variant is weakest. Applied to MW, GSE, and Sgr stars, spectral measures recover a distance ordering consistent with their known chemical enrichment histories. This framework also provides a route to comparing observed enrichment histories against simulations to identify those that best reproduce the observed tree structure.
Related
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BibTeX
@misc{signor2026comparing,
title = {{Comparing phylogenetic trees of stars with spectral graph distances}},
author = {Theosamuele Signor and Matias Neto and Paula Jofré and Sara Vitali and Xia Hua and Patricia B. Tissera and Claudia Aguilera-Gómez and Payel Das and Brian Tapia-Contreras and Robert M. Yates and Luis Martí and Nayat Sánchez-Pi},
howpublished = {arXiv},
year = {2026},
month = sep,
doi = {10.48550/arxiv.2609.26782},
eprint = {2609.26782},
archivePrefix = {arXiv},
url = {https://arxiv.org/abs/2609.26782},
}
RIS
TY - UNPB
TI - Comparing phylogenetic trees of stars with spectral graph distances
AU - Theosamuele Signor
AU - Matias Neto
AU - Paula Jofré
AU - Sara Vitali
AU - Xia Hua
AU - Patricia B. Tissera
AU - Claudia Aguilera-Gómez
AU - Payel Das
AU - Brian Tapia-Contreras
AU - Robert M. Yates
AU - Luis Martí
AU - Nayat Sánchez-Pi
PY - 2026
DA - 2026/09/22
PB - arXiv
DO - 10.48550/arxiv.2609.26782
UR - https://arxiv.org/abs/2609.26782
AB - Phylogenetic trees offer a hierarchical representation of chemical similarities among stars, from which their evolutionary histories can, in principle, be reconstructed. Simulation-based work suggests that phylogenetic trees built under different chemical evolution scenarios carry distinguishable structural imprints, but whether existing methods can detect this signal in practice is unclear. We evaluate distance measures, both classical tree-based and graph-theoretical, for comparing phylogenetic trees, seeking measures robust to observational noise that separate trees built from populations with distinct chemical enrichment histories. We construct Neighbor-Joining trees from chemical abundance vectors of solar twins and of stars associated with the Milky Way (MW) disk, Gaia-Sausage-Enceladus (GSE), and the Sagittarius dwarf spheroidal galaxy (Sgr). Two benchmark tests assess stability under input perturbations within the same evolutionary history and discriminative power between distinct stellar populations used as proxies for different evolutionary histories. Tree metrics rapidly saturate under perturbations of order the typical uncertainty (≈2σ, or ≈0.05 dex per element) and fail to distinguish trees when leaf sets differ. In contrast, spectral distances vary smoothly with perturbation amplitude and provide a label-invariant method for comparing trees built from disjoint sets of stars. Among the spectral measures evaluated, the Laplacian spectral distance shows the most consistent separation across population pairs, while the normalized variant is weakest. Applied to MW, GSE, and Sgr stars, spectral measures recover a distance ordering consistent with their known chemical enrichment histories. This framework also provides a route to comparing observed enrichment histories against simulations to identify those that best reproduce the observed tree structure.
ER -