5 papers
The ASTRID Simulation at z=0: From Massive Black Holes to Large-scale Structure
Yihao Zhou, Tiziana Di Matteo, Simeon Bird +7
We present the results for the cosmological simulation ASTRID. Hosting 0.33 trillion particles in a box of per side, ASTRID is one o…
FlowForge: A Staged Local Rollout Engine for Flow-Field Prediction
Xiaowen Zhang, Ziming Zhou, Fengnian Zhao +1
Deep learning surrogates for CFD flow-field prediction often rely on large, complex models, which can be slow and fragile when data are noisy or incomplete. We introduce FlowForge,…
An AI super-resolution field emulator for cosmological hydrodynamics: the Lyman-α forest
Fatemeh Hafezianzadeh, Xiaowen Zhang, Yueying Ni +4
We extend our super-resolution and emulation framework for cosmological dark matter simulations to include hydrodynamics. We present a two-stage deep learning model to emulate high…
Bridging Literature and the Universe Via A Multi-Agent Large Language Model System
Xiaowen Zhang, Zhenyu Bi, Patrick Lachance +3
As cosmological simulations and their associated software become increasingly complex, physicists face the challenge of searching through vast amounts of literature and user manual…
AI-assisted super-resolution cosmological simulations IV: An emulator for deterministic realizations
Xiaowen Zhang, Patrick Lachance, Ankita Dasgupta +5
Super-resolution (SR) models in cosmological simulations use deep learning (DL) to rapidly enhance low-resolution (LR) runs with statistically correct fine details. These models pr…