collaborators

9 papers

cond-mat.stat-mech2026

Equilibrium Distributions for Strongly Nonlinear Many-Body Systems

Jialin Zhang, Yong Zhang, Hong Zhao

Obtaining equilibrium distributions of nonlinear systems is essential for accurately computing macroscopic observables. Conventional theoretical corrections are typically limited t…

cond-mat.stat-mech2026

Exact Resonances Are Not Sufficient for Phonon Energy Diffusion

Wei Lin, Yong Zhang, Hong Zhao

Multi-phonon resonance conditions underpin kinetic theories of phonon transport and lattice thermalization. We show that exact resonance matching, nonzero interaction coefficients,…

cs.LG2026

Network Dynamics-Based Framework for Understanding Deep Neural Networks

Yuchen Lin, Yong Zhang, Sihan Feng +1

Advancements in artificial intelligence call for a deeper understanding of the fundamental mechanisms underlying deep learning. In this work, we propose a theoretical framework to…

cs.LG2026

Minimum Description Length based Granular-Ball Tree Regularization for Spectral Clustering

Zeqiang Xian, Caihui Liu, Yong Zhang +1

Spectral clustering largely depends on the affinity graph, yet constructing a graph that preserves reliable local connectivity while adapting to heterogeneous data structures remai…

cond-mat.stat-mech2026

Boltzmann Distribution from Invariance of Coarse-Graining-Scale and Energy-Shift

Weicheng Fu, Yisen Wang, Yong Zhang +1

We present a concise derivation of the Boltzmann form for single-particle energy distributions in classical many-body Hamiltonian systems. The derivation relies on two physical fac…

cond-mat.stat-mech2025

The equilibrium distribution function for strongly nonlinear systems

Jialin Zhang, Yong Zhang, Hong Zhao

The equilibrium distribution function determines macroscopic observables in statistical physics. While conventional methods correct equilibrium distributions in weakly nonlinear or…