Differentiable Cosmological Simulation with the Adjoint Method

Differentiable Cosmological Simulation with the Adjoint Method

Rapid advances in deep learning have brought not only a myriad of powerful neural networks, but also breakthroughs that benefit established scientific research. In particular, automatic differentiation (AD) tools and computational accelerators like GPUs have facilitated forward modeling of the Unive...

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Bibliographic Details
Main Authors: Yin Li, Chirag Modi, Drew Jamieson, Yucheng Zhang, Libin Lu, Yu Feng, François Lanusse, Leslie Greengard
Format: Article
Language:English
Published: IOP Publishing 2024-01-01
Series:The Astrophysical Journal Supplement Series
Subjects:
Cosmology
Large-scale structure of the universe
N-body simulations
Astronomy software
Computational methods
Algorithms
Online Access:https://doi.org/10.3847/1538-4365/ad0ce7

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