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Star Log-extended eMulation: A method for efficient computation of the Tolman-Oppenheimer-Volkoff equations

Sudhanva Lalit1,*, Alexandra C. Semposki2,†, and Joshua M. Maldonado2,‡

  • *Contact author: lalit@frib.msu.edu
  • †Contact author: as727414@ohio.edu
  • ‡Contact author: jm998521@ohio.edu
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Phys. Rev. Research 7, 043037 – Published 10 October, 2025

DOI: https://doi.org/10.1103/5p3h-b8rf

Abstract

We emulate the Tolman-Oppenheimer-Volkoff (TOV) equations, including tidal deformability, for neutron stars using a method based upon the Dynamic Mode Decomposition. This method, which we call Star Log-extended eMulation (SLM), utilizes the underlying logarithmic behavior of the differential equations to enable accurate emulation of the nonlinear system. We show predictions for well-known equations of state (EOSs) with fixed parameters using the SLM, accurately recreating high-fidelity results while achieving a computational speedup of ≈2.4×104. We test our parametric SLM method for a two-parameter quarkyonic EOS against high-fidelity RK4 TOV calculations and find a computational speedup of ≈7.0×104. Hence, SLM is an efficient emulator for the numerous TOV evaluations required by multimessenger astrophysical frameworks that infer constraints on the EOS. The ability of the SLM algorithm to learn a mapping between parameters of the EOS and subsequent neutron star properties also opens up potential extensions for assisting in computationally prohibitive uncertainty quantification for any type of EOS. The source code for the methods employed in this work is openly available in a public GitHub repository for community modification and use.

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Phys. Rev. Research 7, 043037– Published 10 October, 2025
  • Received 22 November 2024
  • Accepted 9 September 2025
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Published by the American Physical Society under the terms of the Creative Commons Attribution 4.0 International license. Further distribution of this work must maintain attribution to the author(s) and the published article's title, journal citation, and DOI.

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