Bridging Machine Learning and Cosmological Simulations: Using Neural Operators to emulate Chemical Evolution
The computational expense of solving non-equilibrium chemistry equations in astrophysical simulations poses a significant challenge, particularly in high-resolution, large-scale cosmological models. In this work, we explore the potential of machine learning, specifically Neural Operators, to emulate...
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| Main Authors: | , , , |
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| Format: | Article |
| Language: | English |
| Published: |
Maynooth Academic Publishing
2025-07-01
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| Series: | The Open Journal of Astrophysics |
| Online Access: | https://doi.org/10.33232/001c.142225 |
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