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Main Authors: Brennan, John, Balu, Sreedhar, Qin, Yuxiang, Regan, John, Power, Chris
Format: Preprint
Published: 2025
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Online Access:https://arxiv.org/abs/2501.13056
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author Brennan, John
Balu, Sreedhar
Qin, Yuxiang
Regan, John
Power, Chris
author_facet Brennan, John
Balu, Sreedhar
Qin, Yuxiang
Regan, John
Power, Chris
contents Super-resolution techniques have the potential to reduce the computational cost of cosmological and astrophysical simulations. This can be achieved by enabling traditional simulation methods to run at lower resolution and then efficiently computing high-resolution data corresponding to the simulated low-resolution data. In this work, we investigate the application of a Wasserstein Generative Adversarial Network (WGAN) model, previously proposed in the literature, to increase the particle resolution of dark-matter-only simulations. We reproduce prior results, showing the WGAN model successfully generates high-resolution data with summary statistics, including the power spectrum and halo mass function, that closely match those of true high-resolution simulations. However, we also identify a limitation of the WGAN model in the form of smeared features in generated high-resolution data, particularly in the shapes of dark-matter halos and filaments. This limitation points to a potential weakness of the proposed WGAN-based super-resolution method in capturing the detailed structure of halos, and underscores the need for further development in applying such models to cosmological data.
format Preprint
id arxiv_https___arxiv_org_abs_2501_13056
institution arXiv
publishDate 2025
record_format arxiv
spellingShingle On the Use of WGANs for Super-Resolution in Dark-Matter Simulations
Brennan, John
Balu, Sreedhar
Qin, Yuxiang
Regan, John
Power, Chris
Astrophysics of Galaxies
Super-resolution techniques have the potential to reduce the computational cost of cosmological and astrophysical simulations. This can be achieved by enabling traditional simulation methods to run at lower resolution and then efficiently computing high-resolution data corresponding to the simulated low-resolution data. In this work, we investigate the application of a Wasserstein Generative Adversarial Network (WGAN) model, previously proposed in the literature, to increase the particle resolution of dark-matter-only simulations. We reproduce prior results, showing the WGAN model successfully generates high-resolution data with summary statistics, including the power spectrum and halo mass function, that closely match those of true high-resolution simulations. However, we also identify a limitation of the WGAN model in the form of smeared features in generated high-resolution data, particularly in the shapes of dark-matter halos and filaments. This limitation points to a potential weakness of the proposed WGAN-based super-resolution method in capturing the detailed structure of halos, and underscores the need for further development in applying such models to cosmological data.
title On the Use of WGANs for Super-Resolution in Dark-Matter Simulations
topic Astrophysics of Galaxies
url https://arxiv.org/abs/2501.13056