Machine Learning the Strong Disorder Renormalization Group Method for Disordered Quantum Spin Chains

arXiv:2603.05164 · cond-mat.dis-nn, cond-mat.stat-mech, quant-ph · Submitted 2026-03-05 · Read on arXiv

cond-mat.dis-nn, cond-mat.stat-mech, quant-ph

Submitted: 2026-03-05

Updated: 2026-03-05

Terminology

• Entanglement — 57× in this paper · explained in 3 episodes
• Entanglement Entropy — 31× in this paper · explained in 2 episodes
• Random Forest — 15× in this paper
• Accuracy — 8× in this paper · explained in 1 episode
• Fidelity — 3× in this paper · explained in 2 episodes
• Graph Neural Network (GNN) — 3× in this paper · explained in 2 episodes
• Action Space — 2× in this paper · explained in 1 episode
• Generalization — 2× in this paper · explained in 13 episodes
• Phase Transitions — 2× in this paper · explained in 2 episodes
• Transfer Learning — 2× in this paper · explained in 10 episodes
• Adam — 1× in this paper · explained in 2 episodes
• Benchmarking — 1× in this paper · explained in 3 episodes
• Clustering — 1× in this paper · explained in 2 episodes
• Deep Reinforcement Learning — 1× in this paper · explained in 2 episodes
• Frustration — 1× in this paper · explained in 2 episodes
• Generative Model — 1× in this paper · explained in 2 episodes
• Hilbert Space — 1× in this paper · explained in 2 episodes
• Optimal Transport — 1× in this paper · explained in 5 episodes
• Reinforcement Learning — 1× in this paper · explained in 4 episodes
• Representation Learning — 1× in this paper · explained in 2 episodes
• Transformer — 1× in this paper · explained in 2 episodes
• alpha — 1× in this paper · explained in 1 episode

Sources

• Multifractal and Glassy Signatures of Non-Ergodic 2D Quantum Dynamics
• Strong Disorder Renormalization Group Method for Bond Disordered Antiferromagnetic Quantum Spin Chains with Long Range Interactions: Excited States and Finite Temperature Properties
• Machine Learning Renormalization Group for Statistical Physics
• Quantum Spin Glass in the Two-Dimensional Disordered Heisenberg Model via Foundation Neural-Network Quantum States
• Renormalization Group flow, Optimal Transport and Diffusion-based Generative Model
• An exact mapping between the Variational Renormalization Group and Deep Learning
• Operator Learning Renormalization Group
• Wavelet Conditional Renormalization Group
• Application of deep neural networks for computing the renormalization group flow of the two-dimensional phi^4 field theory
• Neural Networks as Universal Probes of Many-Body Localization in Quantum Graphs
• Predicting the von Neumann Entanglement Entropy Using a Graph Neural Network
• Tensor-network strong-disorder renormalization groups for random quantum spin systems in two dimensions
• Entanglement-based tensor-network strong-disorder renormalization group

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