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Feature Transformation (FT) crafts new features from original ones via mathematical operations to enhance dataset expressiveness for downstream models. However, existing FT methods exhibit critical limitations: discrete search struggles…

Machine Learning · Computer Science 2025-05-22 Nanxu Gong , Zijun Li , Sixun Dong , Haoyue Bai , Wangyang Ying , Xinyuan Wang , Yanjie Fu

We propose a new iterative optimization method for the {\bf Data-Fitting} (DF) problem in Machine Learning, e.g. Neural Network (NN) training. The approach relies on {\bf Graphical Model} (GM) representation of the DF problem, where…

Machine Learning · Computer Science 2021-02-17 Francesco Concetti , Michael Chertkov

Classical density functional theory (DFT) provides an exact variational framework for determining the equilibrium properties of inhomogeneous fluids. We report a generalization of DFT to treat the non-equilibrium dynamics of classical…

Soft Condensed Matter · Physics 2013-09-06 Matthias Schmidt , Joseph M. Brader

Standard density functional theory (DFT) routinely misclassifies the electronic ground state of correlated and structurally complex compounds, predicting metallic behaviour for materials that experiments report as semiconductors. Each such…

Materials Science · Physics 2026-04-30 Yue Li , Bijun Tang

Deep learning electronic structures from ab initio calculations holds great potential to revolutionize computational materials studies. While existing methods proved success in deep-learning density functional theory (DFT) Hamiltonian…

Efficient numerical characterization is a key problem in composite material analysis. To follow accuracy improvement in image tomography, memory efficient methods of numerical characterization have been developed. Among them, an FFT based…

Numerical Analysis · Mathematics 2022-07-27 Felix Givois , Matthias Kabel , Nicolas Gauger

We describe a massively parallel implementation of the recently developed discontinuous Galerkin density functional theory (DGDFT) [J. Comput. Phys. 2012, 231, 2140] method, for efficient large-scale Kohn-Sham DFT based electronic structure…

Computational Physics · Physics 2015-10-01 Wei Hu , Lin Lin , Chao Yang

We develop a method in which the electronic densities of small fragments determined by Kohn-Sham density functional theory (DFT) are embedded using stochastic DFT to form the exact density of the full system. The new method preserves the…

Chemical Physics · Physics 2015-06-19 Daniel Neuhauser , Roi Baer , Eran Rabani

Although robotic applications increasingly demand versatile and dynamic object handling, most existing techniques are predominantly focused on grasp-based manipulation, limiting their applicability in non-prehensile tasks. To address this…

Robotics · Computer Science 2025-02-25 Hamidreza Raei , Elena De Momi , Arash Ajoudani

In this study, a fast multipole method (FMM) is used to decrease the computational time of a fully-coupled poroelastic hydraulic fracture model with a controllable effect on its accuracy. The hydraulic fracture model is based on the…

Numerical Analysis · Computer Science 2019-10-23 Ali Rezaei , Fahd Siddiqui , Giorgio Bornia , Mohamed Y. Soliman

We present an efficient ab initio dynamical mean-field theory (DMFT) implementation for quantitative simulations in solids. Our DMFT scheme employs ab initio Hamiltonians defined for impurities comprising the full unit cell or a supercell…

Strongly Correlated Electrons · Physics 2020-03-05 Tianyu Zhu , Zhi-Hao Cui , Garnet Kin-Lic Chan

We introduce an efficient finite-element approach for large-scale real-space pseudopotential density functional theory (DFT) calculations incorporating noncollinear magnetism and spin-orbit coupling. The approach, implemented within the…

Materials Science · Physics 2025-06-11 Nikhil Kodali , Phani Motamarri

We present a novel approach to address the challenges of variable occupation numbers in direct optimization of density functional theory (DFT). By parameterizing both the eigenfunctions and the occupation matrix, our method minimizes the…

Density functional theory (DFT) is an indispensable ab initio method in both quantum chemistry and condensed matter physics. Based on recent advancements in reduced density matrix functional theory (RDMFT), a variant of DFT that is believed…

Quantum Physics · Physics 2026-04-02 Chih-Chun Wang

We present an approach to the DFT+U method (Density Functional Theory + Hubbard model) within which the computational effort for calculation of ground state energies and forces scales linearly with system size. We employ a formulation of…

Strongly Correlated Electrons · Physics 2012-02-14 David D. O'Regan , Nicholas D. M. Hine , Mike C. Payne , Arash A. Mostofi

In this work, we analyze an unfitted discontinuous Galerkin discretization for the numerical solution of the Stokes system based on equal higher-order discontinuous velocities and pressures. This approach combines the best from both worlds,…

Numerical Analysis · Mathematics 2022-04-06 Aikaterini Aretaki , Efthymios N. Karatzas , Georgios Katsouleas

Finite-element (FE) discretisations have emerged as a powerful real-space alternative to large-scale Kohn-Sham density functional theory (DFT) calculations, offering systematic convergence, excellent parallel scalability, while…

Computational Physics · Physics 2025-12-11 Gourab Panigrahi , Phani Motamarri

A simplified density functional theory (DFT) method for charged adsorbates on an ultrathin, insulating film supported by a metal substrate is developed and presented. This new method is based on a previous DFT development that uses a…

Materials Science · Physics 2017-03-27 Ivan Scivetti , Mats Persson

We introduce the fermionized time-dependent Hartree-Fock (fTDHF), a real-time quantum dynamics method for spin-1/2 Hamiltonians following their mapping to fermions via the Jordan-Wigner transformation. fTDHF is formally equivalent to exact…

Strongly Correlated Electrons · Physics 2026-05-25 Rishab Dutta , Marc Illa , Niranjan Govind , Karol Kowalski

Dynamical mean-field theory (DMFT) is a cornerstone technique for studying strongly correlated electronic systems. However, each DMFT step is computationally demanding, and many iterations can be required to achieve convergence. Here, we…

Strongly Correlated Electrons · Physics 2026-01-26 E. M. Makaresz , O. Gingras , Tsung-Han Lee , Nicola Lanatà , B. J. Powell , Henry L. Nourse