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20212026
most citedNeural network reconstruction of the dense matter equation of state from neutron star observables

49 citations · 123 across the 15 of their papers we have counts for

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5 papers · 1 filter

nucl-th2026

Ultra-Peripheral Collisions as a Nuclear-Structure Interferometer with Interpretable Multitask Deep Learning

Jing-Zong Zhang, Wang-Mei Zha, Lingxiao Wang +1

Precise knowledge of nuclear structure is essential across fundamental physics, yet probing these structures is notoriously difficult. To address this challenge, ultra-peripheral c…

cs.LG2026

Generative Criticality in Large Language Model Temperature Scaling

Huajian Ruan, Jinyang Li, Xingyu Guo +1

We propose a statistical-field framework for text generated by large language models (LLMs), treating token embeddings as continuous spin variables on a one-dimensional chain. Defi…

astro-ph.HE2026

Reconstruction of fast-rotating neutron star observables with the neural network

Wen Liu, Lingxiao Wang, Zhenyu Zhu

Rotation can significantly affect neutron-star (NS) properties, but accurate modeling of rapidly rotating NSs requires solving a two-dimensional, axially symmetric system, making t…

quant-ph2026

Learning Quantum Operator Dynamics from Short-Time Data

Jinyang Li, Satoshi Iso, Shunji Matsuura +2

Real-time dynamics of quantum observables provide direct access to excitation spectra and correlation functions in quantum many-body systems, but currently available quantum device…

hep-ph2026

Solving Functional Renormalization Group Equations with Neural Networks

Yang-yang Tan, Wei-jie Fu, Lianyi He +1

We employ deep neural networks to represent the field derivative of the scale-dependent effective potential in the functional renormalization group (fRG) framework for nonperturbat…