Autonomous phase discovery

arXiv:2609.33802 · quant-ph, cond-mat.str-el, cs.LG · Submitted 2026-09-27 · Read on arXiv

quant-ph, cond-mat.str-el, cs.LG

Submitted: 2026-09-27

Updated: 2026-09-27

Comments: 10 pages, 5 figures, https://github.com/shiyu-zhou-7/diff_phase

License: http://arxiv.org/licenses/nonexclusive-distrib/1.0/

Terminology

• Latent Space — 27× in this paper · explained in 7 episodes
• Benchmark — 23× in this paper · explained in 2 episodes
• Chern Number — 22× in this paper · explained in 4 episodes
• Latent Representation — 19× in this paper · explained in 2 episodes
• Phase Transitions — 11× in this paper · explained in 2 episodes
• Latent Representations — 8× in this paper · explained in 3 episodes
• Inverse Problem — 7× in this paper · explained in 2 episodes
• Fidelity — 6× in this paper · explained in 2 episodes
• Active Learning — 5× in this paper · explained in 6 episodes
• Entanglement — 5× in this paper · explained in 3 episodes
• Topological Order — 5× in this paper · explained in 2 episodes
• Loss Function — 3× in this paper · explained in 2 episodes
• Steering — 3× in this paper · explained in 2 episodes
• Embeddings — 2× in this paper · explained in 2 episodes
• Spectral Gap — 2× in this paper · explained in 5 episodes
• Adam — 1× in this paper · explained in 2 episodes
• Anisotropy — 1× in this paper · explained in 3 episodes
• Anyons — 1× in this paper · explained in 2 episodes
• Bayesian Optimization — 1× in this paper · explained in 3 episodes
• Contrastive Learning — 1× in this paper · explained in 5 episodes
• Hubbard Model — 1× in this paper · explained in 3 episodes
• Quantization — 1× in this paper · explained in 12 episodes
• Quantum Physics — 1× in this paper · explained in 10 episodes
• Reconstruction Error — 1× in this paper · explained in 2 episodes
• Reinforcement Learning — 1× in this paper · explained in 4 episodes
• Representation Learning — 1× in this paper · explained in 2 episodes
• Robustness — 1× in this paper · explained in 5 episodes
• Symmetry Breaking — 1× in this paper · explained in 3 episodes

Sources

• Doping a Mott Insulator: Physics of High Temperature Superconductivity
• Backpropagation-Friendly Eigendecomposition
• RydbergGPT
• From Architectures to Applications: A Review of Neural Quantum States

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