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ELISa: A new tool for fast modelling of eclipsing binaries

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arxiv 2106.10116 v1 pith:SWJGN56B submitted 2021-06-18 astro-ph.IM astro-ph.SR

classification astro-ph.IMastro-ph.SR
keywords eclipsingelisasurfacebinarieslightbinarymodellingradial
verification ladder T0 review T1 audit T2 compute T3 formal
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We present a new, fast, and easy to use tool for modelling light and radial velocity curves of close eclipsing binaries with built-in methods for solving an inverse problem. The main goal of ELISa (Eclipsing binary Learning and Interactive System) is to provide an acceptable compromise between computational speed and precision during the fitting of light curves and radial velocities of eclipsing binaries. The package is entirely written in the Python programming language in a modular fashion, making it easy to install, modify, and run on various operating systems. ELISa implements Roche geometry and the triangulation process to model a surface of the eclipsing binary components, where the surface parameters of each surface element are treated separately. Surface symmetries and approximations based on the similarity between surface geometries were used to reduce the runtime during light curve calculation significantly. ELISa implements the least square trust region reflective algorithm and Markov-chain Monte Carlo optimisation methods to provide the built-in capability to determine parameters of the binary system from photometric observations and radial velocities. The precision and speed of the light curve generator were evaluated using various benchmarks. We conclude that ELISa maintains an acceptable level of accuracy to analyse data from ground-based and space-based observations, and it provides a significant reduction in computational time compared to the current widely used tools for modelling eclipsing binaries.

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Cited by 2 Pith papers

Reviewed papers in the Pith corpus that reference this work. Sorted by Pith novelty score. OpenAlex reports about 19 citations worldwide. Full citation record

  1. Morphological classification of eclipsing binary stars using computer vision methods

    cs.CV 2025-08 unverdicted novelty 6.0 of 10

    Fine-tuned ResNet50 and vision transformers on polar-hexbin images classify eclipsing binaries as detached or overcontact with high accuracy on real data, but cannot reliably detect starspots.

  2. RedDots: Magnetic field of the nearby active M dwarf GJ 729, and a search for companions

    astro-ph.SR 2026-07 conditional novelty 4.0 of 10

    GJ 729 exhibits a weak, evolving large-scale magnetic field (50-145 G) and a persistent ~7 d radial velocity signal that could be a ~1.5-2 Earth-mass planet or residual stellar activity.

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