2 papers
astro-ph.IM2025
Bridging Machine Learning and Cosmological Simulations: Using Neural Operators to emulate Chemical Evolution
Pelle van de Bor, John Brennan, John A. Regan +1
The computational expense of solving non-equilibrium chemistry equations in astrophysical simulations poses a significant challenge, particularly in high-resolution, large-scale co…
astro-ph.GA2025
On the Use of WGANs for Super-Resolution in Dark-Matter Simulations
John Brennan, Sreedhar Balu, Yuxiang Qin +2
Super-resolution techniques have the potential to reduce the computational cost of cosmological and astrophysical simulations. This can be achieved by enabling traditional simulati…