Research
From Classical to Quantum: Extending Prometheus for Unsupervised Discovery of Phase Transitions in Three Dimensions and Quantum Systems
arXiv:2602.14928v4 Announce Type: replace-cross Abstract: We extend the Prometheus framework for unsupervised phase transition discovery from two-dimensional classical systems to three-dimensional cla
arXiv:2602.14928v4 Announce Type: replace-cross Abstract: We extend the Prometheus framework for unsupervised phase transition discovery from two-dimensional classical systems to three-dimensional classical systems and quantum many-body systems. Building upon preliminary observations from a 2D Ising model student abstract [Yee et al., 2026], we address two fundamental questions: (1) Does the framework scale to higher dimensions where exact solutions are unavailable? (2) Can it generalize to quantum phase transitions driven by quantum fluctuations rather than thermal fluctuations? For the 3D Ising model on lattices up to L{=}32, we achieve critical temperature detection within 0.01% of literature values (Tc/J = 4.511 pm 0.005) and extract critical exponents with {geq}70% accuracy, with statistical analysis correctly identifying the 3D Ising universality class (p = 0.72). For quantum systems, we develop quantum-aware VAE (Q-VAE) architectures operating on complex-valued wavefunctions with fidelity-based loss functions, achieving 2% accuracy in quantum critical point detection for the transverse field Ising model. For the disordered TFIM, we perform a consistency check of activated dynamical scaling ln xi sim |h - hc|^{-psi}, extracting tunneling exponent psi = 0.48 pm 0.08 consistent with theoretical predictions (psi = 0.5, Deltahi^2 = 12.3, p < 0.001). This demonstrates that unsupervised learning can identify qualitatively different types of critical behavior, serving as a consistency check on known IRFP physics.
Related
- Physics and causally constrained discrete-time neural models of turbulent dynamical systems
- Dimensional Criticality at Grokking Across MLPs and Transformers
- Theory and interpretability of Quantum Extreme Learning Machines: a Pauli-transfer matrix approach
- Spectral Kernel Dynamics via Maximum Caliber: Fixed Points, Geodesics, and Phase Transitions
Source: arXiv cs.LG | 2026-04-21