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arXiv research

A locally-built, LLM-digested index of recent arXiv papers in quant finance, geometry/topology, and statistical ML — keyword search served straight from SQLite on this machine.

168,695 papers · 148 categories

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5 results for “Kohn-Sham”

Dynamic Learning of Correlation Potentials for a Time-Dependent Kohn-Sham Systemstat.ML

Develops methods to learn correlation potentials for time-dependent Kohn-Sham systems.

problem Learning the correlation potential for time-dependent Kohn-Sham systems.

method Optimizing a least-squares objective subject to the TDKS equation using adjoints.

result Learned correlation potential models match ground truth electron densities and can have memory.

Kohn-Sham systems time-dependent Schrödinger equation least-squares optimization adjoint methods electron densities

2021-12-14abs ↗pdf ↗

By-passing the Kohn-Sham equations with machine learningphysics.comp-ph

Last year, at least 30,000 scientific papers used the Kohn-Sham scheme of density functional theory to solve electronic structure problems in a wide variety of scientific fields, ranging from materials science to biochemistry to astrophysics. Machine learning holds the promise of learning the kinetic energy functional …

2016-09-09abs ↗pdf ↗

Machine learning-guided construction of an analytic kinetic energy functional for orbital free density functional theorycond-mat.mtrl-sci

Researchers created an accurate kinetic energy functional for materials modeling.

problem Lack of accurate analytic kinetic energy functionals for large-scale ab initio materials modeling.

method Interpretative machine learning of crystal cell-averaged kinetic energy densities guided by a hybrid Gaussian process regression - neural network (GPR-NN) method.

result Constructed an analytic kinetic energy functional that reproduces Kohn-Sham DFT energy-volume curves with sufficient accuracy.

machine learning kinetic energy functional orbital-free density functional theory materials modeling ab initio

2025-02-08abs ↗pdf ↗

Overcoming the Barrier of Orbital-Free Density Functional Theory for Molecular Systems Using Deep Learningstat.ML

Deep learning improves OFDFT for molecular systems.

problem Limited accuracy of OFDFT for non-periodic molecular systems.

method M-OFDFT using deep learning to approximate kinetic energy density.

result Achieves comparable accuracy to Kohn-Sham DFT on large molecules.

Deep Learning Density Functional Theory Molecular Systems Quantum Chemistry Accuracy

2023-09-28abs ↗pdf ↗

Electronic-structure properties from atom-centered predictions of the electron densityphysics.chem-ph

A new method predicts electron density accurately from atom-centered models.

problem Predicting electron density accurately from atom-centered models.

method Gradient-based approach to minimize loss function in an optimized sparse feature space.

result Extremely accurate predictions of electron density and total energies.

electron density machine learning density fitting Kohn-Sham total energy

2022-06-28abs ↗pdf ↗