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We present a global hybrid meta-generalized gradient approximation (meta-GGA) with three empirical parameters, as well as its underlying semilocal meta-GGA and a meta-GGA with only one empirical parameter. All of them are based on the new…

In this paper we propose and analyze a (temporally) third order accurate exponential time differencing (ETD) numerical scheme for the no-slope-selection (NSS) equation of the epitaxial thin film growth model, with Fourier pseudo-spectral…

Numerical Analysis · Mathematics 2019-03-11 Kelong Cheng , Zhonghua Qiao , Cheng Wang

We investigate fundamental properties of meta-generalized-gradient approximations (meta-GGAs) to the exchange-correlation energy functional, which have an implicit density dependence via the Kohn-Sham kinetic-energy density. To this…

Chemical Physics · Physics 2014-12-10 F. G. Eich , Maria Hellgren

To apply the latest computer vision techniques that require a large computational cost in real industrial applications, knowledge distillation methods (KDs) are essential. Existing logit-based KDs apply the constant temperature scaling to…

Computer Vision and Pattern Recognition · Computer Science 2025-05-23 Seonghak Kim , Gyeongdo Ham , Suin Lee , Donggon Jang , Daeshik Kim

The recently developed Deep Potential [Phys. Rev. Lett. 120, 143001, 2018] is a powerful method to represent general inter-atomic potentials using deep neural networks. The success of Deep Potential rests on the proper treatment of locality…

Computational Physics · Physics 2019-12-05 Leonardo Zepeda-Núñez , Yixiao Chen , Jiefu Zhang , Weile Jia , Linfeng Zhang , Lin Lin

We report a direct scheme calculation of kinetic energy functional derivative using Machine Learning. Support Vector Regression and Kernel Ridge Regression techniques were independently employed to estimate the kinetic energy functional and…

Computational Physics · Physics 2021-03-16 H. Saidaoui , S. Kais , S. Rashkeev , FH. Alharbi

In this paper we develop a kernel density estimation (KDE) approach to modeling and forecasting recurrent trajectories on a compact manifold. For the purposes of this paper, a trajectory is a sequence of coordinates in a phase space defined…

Machine Learning · Computer Science 2019-11-06 Trevor K. Karn , Steven Petrone , Christopher Griffin

Density estimation is a fundamental task in statistics and machine learning applications. Kernel density estimation is a powerful tool for non-parametric density estimation in low dimensions; however, its performance is poor in higher…

Machine Learning · Computer Science 2022-08-08 Joseph A. Gallego , Fabio A. González

Kohn-Sham spin-density functional theory provides an efficient and accurate model to study electron-electron interaction effects in quantum dots, but its application to large systems is a challenge. An efficient algorithm for the…

Mesoscale and Nanoscale Physics · Physics 2007-05-23 Hong Jiang , Harold U. Baranger , Weitao Yang

Recent works have shown the superior robustness of four-dimensional (4D) Radar-based three-dimensional (3D) object detection in adverse weather conditions. However, processing 4D Radar data remains a challenge due to the large data size,…

Computer Vision and Pattern Recognition · Computer Science 2023-03-14 Dong-Hee Paek , Seung-Hyun Kong , Kevin Tirta Wijaya

We propose a nonlinear reduced basis method for the efficient approximation of parametrized partial differential equations (PDEs), exploiting kernel proper orthogonal decomposition (KPOD) for the generation of a reduced-order space and…

Numerical Analysis · Mathematics 2021-04-01 Matteo Salvador , Luca Dede' , Andrea Manzoni

We improve on the Thomas-Fermi approximation for the single-particle density of fermions by introducing inhomogeneity corrections. Rather than invoking a gradient expansion, we relate the density to the unitary evolution operator for the…

Quantum Gases · Physics 2019-03-04 Thanh Tri Chau , Jun Hao Hue , Martin-Isbjörn Trappe , Berthold-Georg Englert

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

We construct and study several semilocal density functional approximations for the positive Kohn-Sham kinetic energy density. These functionals fit the kinetic energy density of the Airy gas and they can be accurate for integrated kinetic…

Materials Science · Physics 2015-05-13 Lucian A. Constantin , Adrienn Ruzsinszky

Recent studies of gradient descent with large step sizes have shown that there is often a regime with an initial increase in the largest eigenvalue of the loss Hessian (progressive sharpening), followed by a stabilization of the eigenvalue…

Machine Learning · Computer Science 2022-10-11 Atish Agarwala , Fabian Pedregosa , Jeffrey Pennington

Density functional theory (DFT) offers a desirable balance between quantitative accuracy and computational efficiency in practical many-electron calculations. Its central component, the exchange-correlation energy functional, has been…

Using an end-to-end differentiable implementation of the Kohn-Sham self-consistent field equations, we obtain an accurate neural network-based exchange and correlation (XC) functional of the electronic density. The functional is optimized…

Chemical Physics · Physics 2021-06-09 Sebastian Dick , Marivi Fernandez-Serra

By introducing the self-energy density functionals for the dissipative interactions between the reduced system and its environment, we develop a time-dependent density-functional theory formalism based on an equation of motion for the…

Quantum Physics · Physics 2009-11-13 Xiao Zheng , Fan Wang , Chi Yung Yam , Yan Mo , GuanHua Chen

This study reports a general scenario for the out-of-equilibrium features of collapsing polymeric architectures. We use molecular dynamics simulations to characterize the coarsening kinetics, in bad solvent, for several macromolecular…

Soft Condensed Matter · Physics 2019-12-10 Mariarita Paciolla , Daniel J. Arismendi-Arrieta , Angel J. Moreno

Orbital-free density functional theory as an extension of traditional Thomas-Fermi theory has attracted a lot of interest in the past decade because of developments in both more accurate kinetic energy functionals and highly efficient…

Materials Science · Physics 2009-11-10 Hong Jiang , Weitao Yang
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