Development of a Physics-Informed Neural Framework, MEOWN, for Rapid Prediction of Muon Stopping Sites in Crystalline Materials, for understanding Quantum Magnet employing Muon Spectroscopy

arXiv:2609.17063 · cond-mat.mtrl-sci, cond-mat.str-el, math-ph, math.MP, physics.data-an, quant-ph · Submitted 2026-09-15 · Read on arXiv

cond-mat.mtrl-sci, cond-mat.str-el, math-ph, math.MP, physics.data-an, quant-ph

Submitted: 2026-09-15

Updated: 2026-09-15

Terminology

Benchmark — 10× in this paper · explained in 2 episodes
Accuracy — 6× in this paper · explained in 1 episode
Core — 4× in this paper · explained in 2 episodes
DFT Calculations — 3× in this paper · explained in 2 episodes
Interpretability — 2× in this paper · explained in 15 episodes
Transferability — 2× in this paper · explained in 4 episodes
Adam — 1× in this paper · explained in 2 episodes
Composite Loss Function — 1× in this paper · explained in 2 episodes
Consistency — 1× in this paper · explained in 3 episodes
Density Functional Theory (DFT) — 1× in this paper · explained in 2 episodes
Generalization — 1× in this paper · explained in 13 episodes
Local Optimization — 1× in this paper · explained in 2 episodes
Loss Function — 1× in this paper · explained in 2 episodes
Muon Engine for Optimized Weighted Networks — 1× in this paper
Robustness — 1× in this paper · explained in 5 episodes
Uncertainty Quantification — 1× in this paper · explained in 8 episodes

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