Author

Kyle Bystrom

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Preprint Sep 2026

Near Chemical Accuracy From Size-Consistent Pad\'e Resummed M{\o}ller-Plesset Perturbation Theory

Pad\'e resummation of the correlation energy from M{\o}ller-Plesset (MP) perturbation theory is not size-consistent and is therefore seldom used. We present an orbital-based Pad\'e resummation of the MP2 and MP3 self-energy operators, whose trace yields a size-consistent correlation energy. We find that damping the thi...

Kyle Bystrom, Timothy C. Berkelbach, D. Hait · 0 citations

Preprint Sep 2026

RS-CIDER: A non-local machine learning model for approximating screened hybrid functionals

RS-CIDER is presented, a machine-learned non-local exchange functional that approximates the short-range Hartree-Fock exchange term in HSE06 by explicitly fitting both ground-state energies and single-particle energy levels and is established as an efficient self-consistent machine-learned surrogate for HSE06.

Zhuo-Tao Jin, M. S. Abdallah, Boris Kozinsky et al. · 0 citations

Preprint Aug 2026

Machine-learned exchange-correlation functionals for molecules, solids, and reactive surfaces

The application of density functional theory to heterogeneous catalysis is hindered by the shortcomings of conventional density functional approximations. We combine machine learning with explicitly non-local physically informed descriptors and introduce an exchange-correlation functional (CIDER26SS) framework regulari...

M. S. Abdallah, Zhuo-Tao Jin, Boris Kozinsky et al. · 1 citation · ⚡1