Symmetry-Constrained Multi-Scale Physics-Informed Neural Networks for Graphene Electronic Band Structure Prediction

arXiv:2508.10718 · cond-mat.mtrl-sci, cs.LG, physics.comp-ph · Submitted 2025-08-14 · Read on arXiv

cond-mat.mtrl-sci, cs.LG, physics.comp-ph

Submitted: 2025-08-14

Updated: 2025-08-14

Terminology

• Accuracy — 53× in this paper · explained in 1 episode
• Gradient Flow — 6× in this paper · explained in 2 episodes
• Loss Function — 6× in this paper · explained in 2 episodes
• Generalization — 5× in this paper · explained in 13 episodes
• Feature Extraction — 4× in this paper · explained in 2 episodes
• Physical Constraints — 3× in this paper · explained in 7 episodes
• Robustness — 3× in this paper · explained in 5 episodes
• Alignment — 2× in this paper · explained in 1 episode
• Transfer Learning — 2× in this paper · explained in 10 episodes
• Transferability — 2× in this paper · explained in 4 episodes
• Uncertainty Quantification — 2× in this paper · explained in 8 episodes
• Verification — 2× in this paper · explained in 2 episodes
• Adam — 1× in this paper · explained in 2 episodes
• Adaptation — 1× in this paper · explained in 1 episode
• Approximation Bound — 1× in this paper · explained in 1 episode
• Attention Mechanism — 1× in this paper · explained in 3 episodes
• Clustering — 1× in this paper · explained in 2 episodes
• Computational Tractability — 1× in this paper · explained in 2 episodes
• Conservation Laws — 1× in this paper · explained in 3 episodes
• Consistency — 1× in this paper · explained in 3 episodes
• Convergence Guarantees — 1× in this paper · explained in 3 episodes
• Core — 1× in this paper · explained in 2 episodes
• DFT Calculations — 1× in this paper · explained in 2 episodes
• Density Functional Theory (DFT) — 1× in this paper · explained in 2 episodes
• Fidelity — 1× in this paper · explained in 2 episodes
• Interpretability — 1× in this paper · explained in 15 episodes
• Inverse Design — 1× in this paper · explained in 2 episodes
• Inverse Problem — 1× in this paper · explained in 2 episodes
• Many-Body Effects — 1× in this paper · explained in 2 episodes
• Model Context Protocol (MCP) — 1× in this paper · explained in 8 episodes
• Phase Transitions — 1× in this paper · explained in 2 episodes
• Physics-Informed Neural Networks (PINNs) — 1× in this paper · explained in 6 episodes
• Predictive Modeling — 1× in this paper · explained in 2 episodes
• Regularization — 1× in this paper · explained in 3 episodes

Sources

• Geometric Deep Learning: Grids, Groups, Graphs, Geodesics, and Gauges

Related papers

• AES-Debye: an Accurate, Efficient, and Scalable Engine for Debye Scattering Calculations
• Cooperative Quantum Optical Effects of Moir'e Exciton Superlattices
• Imaging Surface Magnetization in Altermagnetic MnTe Films
• Accidental accuracy and formal consistency in GW +BSE: Exact benchmarks and regime-dependent error cancellation
• Modifying van der Waals Materials via Cavity Vacuum Fluctuations
• Linear dichroic soft X-ray microscopy of ferroelectric stripe domains in epitaxial K 0.6 Na 0.4 NbO 3