Neural ODEs reproduce 2RDM dynamics from data only when three-particle cumulant correlations are strong, mapping the validity regime of cumulant expansions.
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Case study applies SAE probing with enstrophy triage to a continuum-dynamics foundation model and reports intermittent feature consistency that does not align with standard physics while linking some output discrepancies to specific feature changes.
Explainability techniques applied to LundNet show that assigned node importance correlates with classical jet substructure observables such as N-subjettiness ratios and energy correlation functions, with shifts across transverse-momentum regimes.
A VAE learns a minimal latent representation from noisy quantum simulator snapshots that correlates with the sine-Gordon equilibrium parameter and detects anomalous post-quench dynamics including frozen-in solitons.
citing papers explorer
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Capturing reduced-order quantum many-body dynamics out of equilibrium via neural ordinary differential equations
Neural ODEs reproduce 2RDM dynamics from data only when three-particle cumulant correlations are strong, mapping the validity regime of cumulant expansions.
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Sparse probes and murky physics: a case study of interpretability challenges in a foundation model for continuum dynamics
Case study applies SAE probing with enstrophy triage to a continuum-dynamics foundation model and reports intermittent feature consistency that does not align with standard physics while linking some output discrepancies to specific feature changes.
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Explainable AI for Jet Tagging: A Comparative Study of GNNExplainer, GNNShap, and GradCAM for Jet Tagging in the Lund Jet Plane
Explainability techniques applied to LundNet show that assigned node importance correlates with classical jet substructure observables such as N-subjettiness ratios and energy correlation functions, with shifts across transverse-momentum regimes.
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Learning Minimal Representations of Many-Body Physics from Snapshots of a Quantum Simulator
A VAE learns a minimal latent representation from noisy quantum simulator snapshots that correlates with the sine-Gordon equilibrium parameter and detects anomalous post-quench dynamics including frozen-in solitons.
- KIGNet: Physics-Motivated Multi-Graph Representation Learning for Explainable Jet Tagging