Native implementation of the machine-learned Skala exchange-correlation functional in CP2K: Unified one-centre reconstruction for molecular and condensed-phase calculations

arXiv:2609.34055 · cond-mat.mtrl-sci, cond-mat.dis-nn, physics.chem-ph, physics.comp-ph, quant-ph · Submitted 2026-09-28 · Read on arXiv

cond-mat.mtrl-sci, cond-mat.dis-nn, physics.chem-ph, physics.comp-ph, quant-ph

Submitted: 2026-09-28

Updated: 2026-09-28

Code: https://github.com/DCM-Uni-Paderborn/nativ

Terminology

• Core — 36× in this paper · explained in 2 episodes
• Benchmark — 20× in this paper · explained in 2 episodes
• Accuracy — 19× in this paper · explained in 1 episode
• Consistency — 8× in this paper · explained in 3 episodes
• Trace — 2× in this paper · explained in 2 episodes
• Transferability — 2× in this paper · explained in 4 episodes
• Alignment — 1× in this paper · explained in 1 episode
• Degeneracy — 1× in this paper · explained in 3 episodes
• Provenance — 1× in this paper · explained in 4 episodes
• Systematic Bias — 1× in this paper · explained in 3 episodes

Sources

• Accurate and scalable exchange-correlation with deep learning
• CP2K: An electronic structure and molecular dynamics software package - Dynamics, Transport, and Spectroscopic Response
• Molecular Implementation of the Machine-Learned Skala Exchange-Correlation Functional in CP2K through GauXC

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