AI-assisted super-resolution cosmological simulations IV: An emulator for deterministic realizations
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 preserves large-scale structures by conditioning on an LR version of the simulation. On smaller scales, the generative pro...
Saved in:
Main Authors: | Xiaowen Zhang, Patrick Lachance, Ankita Dasgupta, Rupert A. C. Croft, Tiziana Di Matteo, Yueying Ni, Simeon Bird, Yin Li |
---|---|
Format: | Article |
Language: | English |
Published: |
Maynooth Academic Publishing
2025-02-01
|
Series: | The Open Journal of Astrophysics |
Online Access: | https://doi.org/10.33232/001c.129471 |
Tags: |
Add Tag
No Tags, Be the first to tag this record!
|
Similar Items
-
Peningkatan Performa Pengenalan Wajah pada Gambar Low-Resolution Menggunakan Metode Super-Resolution
by: Muhammad Imaduddin Abdur Rohim, et al.
Published: (2024-02-01) -
Efficient Image Super-Resolution with Multi-Branch Mixer Transformer
by: Long Zhang, et al.
Published: (2025-02-01) -
XTNSR: Xception-based transformer network for single image super resolution
by: Jagrati Talreja, et al.
Published: (2025-01-01) -
Gradient pooling distillation network for lightweight single image super-resolution reconstruction
by: Zhiyong Hong, et al.
Published: (2025-02-01) -
Extensive composable entropy for the analysis of cosmological data
by: Constantino Tsallis, et al.
Published: (2025-02-01)