Towards an agnostic algorithm for sampling empirical structure models: The case of Uranus and Neptune

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Main Authors: Wirth, Stefano, Morf, Luca, Helled, Ravit
Format: Preprint
Published: 2025
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author Wirth, Stefano
Morf, Luca
Helled, Ravit
author_facet Wirth, Stefano
Morf, Luca
Helled, Ravit
contents We present an algorithm to efficiently sample the full space of planetary interior density profiles. Our approach uses as few assumptions as possible to pursue an agnostic algorithm. The algorithm avoids the common Markov Chain Monte Carlo method and instead uses an optimisation-based gradient-descent approach designed for computational efficiency. In this work, we use Uranus and Neptune as test cases and obtain empirical models that provide density and pressure profiles consistent with the observed physical properties (total mass, radius, and gravitational moments). We compare our findings to other work and find that while other studies are generally in line with our findings, they do not cover the entire space of solutions faithfully. Furthermore, we present guidance for modellers that construct Uranus or Neptune interior models with a fixed number of layers. We provide a statistical relation between the steepness classifying a density discontinuity and the resulting number of discontinuities to be expected. For example, if one classifies a discontinuity as a density gradient larger than 0.02 kg$\,$m$^{-4}$, then most solutions should have at most one such discontinuity. Finally, we find that discontinuities, if present, are concentrated around a planetary normalised radius of 0.65 for Uranus and 0.7 for Neptune. Our algorithm to efficiently and faithfully investigate the full space of possible interior density profiles can be used to study all planetary objects with gravitational field data.
format Preprint
id arxiv_https___arxiv_org_abs_2512_16995
institution arXiv
publishDate 2025
record_format arxiv
spellingShingle Towards an agnostic algorithm for sampling empirical structure models: The case of Uranus and Neptune
Wirth, Stefano
Morf, Luca
Helled, Ravit
Earth and Planetary Astrophysics
Instrumentation and Methods for Astrophysics
We present an algorithm to efficiently sample the full space of planetary interior density profiles. Our approach uses as few assumptions as possible to pursue an agnostic algorithm. The algorithm avoids the common Markov Chain Monte Carlo method and instead uses an optimisation-based gradient-descent approach designed for computational efficiency. In this work, we use Uranus and Neptune as test cases and obtain empirical models that provide density and pressure profiles consistent with the observed physical properties (total mass, radius, and gravitational moments). We compare our findings to other work and find that while other studies are generally in line with our findings, they do not cover the entire space of solutions faithfully. Furthermore, we present guidance for modellers that construct Uranus or Neptune interior models with a fixed number of layers. We provide a statistical relation between the steepness classifying a density discontinuity and the resulting number of discontinuities to be expected. For example, if one classifies a discontinuity as a density gradient larger than 0.02 kg$\,$m$^{-4}$, then most solutions should have at most one such discontinuity. Finally, we find that discontinuities, if present, are concentrated around a planetary normalised radius of 0.65 for Uranus and 0.7 for Neptune. Our algorithm to efficiently and faithfully investigate the full space of possible interior density profiles can be used to study all planetary objects with gravitational field data.
title Towards an agnostic algorithm for sampling empirical structure models: The case of Uranus and Neptune
topic Earth and Planetary Astrophysics
Instrumentation and Methods for Astrophysics
url https://arxiv.org/abs/2512.16995