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hep-lat2024
Graph Attention Hamiltonian Neural Networks: A Lattice System Analysis Model Based on Structural Learning
Ru Geng, Yixian Gao, Jian Zu +1
A deep understanding of the intricate interactions between particles within a system is a key approach to revealing the essential characteristics of the system, whether it is an in…
math-ph2024
Vertex Weight Reconstruction in the Gel'fand's Inverse Problem on Connected Weighted Graphs
Songshuo Li, Yixian Gao, Ru Geng +1
We consider the reconstruction of the vertex weight in the discrete Gel'fand's inverse boundary spectral problem for the graph Laplacian. Given the boundary vertex weight and the e…
math.DS2024
-SGHN: A Robust Model for Learning Particle Interactions in Lattice Systems
Yixian Gao, Ru Geng, Panayotis Kevrekidis +2
We propose an -separable graph Hamiltonian network (-SGHN) that reveals complex interaction patterns between particles in lattice systems. Utilizing trajectory data, -SGHN…