5 papers
Neural Network Perturbation Theory (NNPT): Learning Residual Corrections from Exact Solutions
Zhenhao Chen, Mutian Shen, Boris Fain +1
Many complex physical systems naturally decompose into an exactly solvable component augmented by a perturbative correction. Rather than directly employing neural networks to analy…
Pattern Expansion of Spin Glasses
Mutian Shen, Zohar Nussinov, Yang-Yu Liu
We introduce a systematic method for expanding general spin-glass Hamiltonians in terms of Mattis interactions, providing a novel perspective for understanding the fundamental diff…
The Eggbox Ising Model
Mutian Shen, Yichen Xu, Zohar Nussinov
We introduce the Eggbox Ising model, a tunable construction of rugged energy landscapes defined by distances to a prescribed set of patterns. Correlated pattern ensembles realize a…
Optimizing p-spin models through hypergraph neural networks and deep reinforcement learning
Li Zeng, Mutian Shen, Tianle Pu +5
p-spin glasses, characterized by frustrated many-body interactions beyond the conventional pairwise case (p>2), are prototypical disordered systems whose ground-state search is NP-…
The Physics of Local Optimization in Complex Disordered Systems
Mutian Shen, Gerardo Ortiz, Zhiqiao Dong +2
Limited resources motivate decomposing large-scale problems into smaller,``local" subsystems and stitching together the so-found solutions. We explore the physics underlying this a…