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Foundation models have transformed language, vision, and time series data analysis, yet progress on dynamic predictions for physical systems remains limited. Given the complexity of physical constraints, two challenges stand out. $(i)$…

Machine Learning · Computer Science 2026-02-05 Haoran Li , Chenhan Xiao , Lihao Mai , Yang Weng , Erik Blasch

Deploying a deep learning model on mobile/IoT devices is a challenging task. The difficulty lies in the trade-off between computation speed and accuracy. A complex deep learning model with high accuracy runs slowly on resource-limited…

Computer Vision and Pattern Recognition · Computer Science 2018-12-31 Xin Li , Shuai Zhang , Bolan Jiang , Yingyong Qi , Mooi Choo Chuah , Ning Bi

Cluster analysis, or clustering, plays a crucial role across numerous scientific and engineering domains. Despite the wealth of clustering methods proposed over the past decades, each method is typically designed for specific scenarios and…

Methodology · Statistics 2026-01-22 Siyi Wang , Alexandre Leblanc , Paul D. McNicholas

The reduced basis method is used to construct a "universal" basis of Dirac orbitals that may be applicable throughout the nuclear chart to calibrate covariant energy density functionals. Relative to our earlier work using the…

Nuclear Theory · Physics 2024-06-05 Amy L. Anderson , J. Piekarewicz

We investigate the high-dimensional data clustering problem by proposing a novel and unsupervised representation learning model called Robust Flexible Auto-weighted Local-coordinate Concept Factorization (RFA-LCF). RFA-LCF integrates the…

Computer Vision and Pattern Recognition · Computer Science 2019-05-28 Zhao Zhang , Yan Zhang , Sheng Li , Guangcan Liu , Meng Wang , Shuicheng Yan

We propose localized functional principal component analysis (LFPCA), looking for orthogonal basis functions with localized support regions that explain most of the variability of a random process. The LFPCA is formulated as a convex…

Methodology · Statistics 2015-01-21 Kehui Chen , Jing Lei

A critical challenge for density functional theory (DFT) in practice is its limited ability to treat static electron correlation, leading to errors in its prediction of charges, multiradicals, and reaction barriers. Recently, we combined…

Chemical Physics · Physics 2024-11-05 Daniel Gibney , Jan-Niklas Boyn , David A. Mazziotti

This chapter presents controlled approximations of Kohn-Sham density functional theory (DFT) that enable very large scale simulations. The work is motivated by the study of defects in crystalline solids, though the ideas can be used in…

Materials Science · Physics 2021-12-14 Kaushik Bhattacharya , Vikram Gavini , Michael Ortiz , Mauricio Ponga , Phanish Suryanarayana

We conduct a detailed investigation of the polaron self-interaction (pSI) error in standard approximations to the exchange-correlation (XC) functional within density-functional theory (DFT). The pSI leads to delocalization error in the…

Materials Science · Physics 2020-08-03 Babak Sadigh , Paul Erhart , Daniel Åberg

The strongly constrained and appropriately normed (SCAN) semilocal density functional [J. Sun, A. Ruzsinszky, J. P. Perdew \textit{Phys. Rev. Lett.} {\bf 115}, 036402 (2015)] obeys all 17 known exact constraints for…

Materials Science · Physics 2016-09-28 J. G. Brandenburg , J. E. Bates , A. Ruzsinszky , J. Sun , J. P. Perdew

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

This paper introduces an abstract framework for randomized subspace correction methods for convex optimization, which unifies and generalizes a broad class of existing algorithms, including domain decomposition, multigrid, and block…

Optimization and Control · Mathematics 2026-04-28 Boou Jiang , Jongho Park , Jinchao Xu

Localized orbital coupled cluster theory has recently emerged as an nonempirical alternative to DFT for large systems. Intuitively, one might expect such methods to perform less well for highly delocalized systems. In the present work, we…

Chemical Physics · Physics 2020-10-16 Nitai Sylvetsky , Ambar Banerjee , Mercedes Alonso , Jan M. L. Martin

We consider a noninteracting disordered system designed to model particle diffusion, relaxation in glasses, and impurity bands of semiconductors. Disorder originates in the random spatial distribution of sites. We find strong numerical…

Disordered Systems and Neural Networks · Physics 2015-03-17 Jacob J. Krich , Alán Aspuru-Guzik

Inter-satellite-link-enabled low-Earth-orbit (LEO) satellite constellations are evolving toward networked architectures that support constellation-level cooperation, enabling multiple satellites to jointly serve user terminals through…

Signal Processing · Electrical Eng. & Systems 2026-05-04 Yuchen Zhang , Eva Lagunas , Xue Xian Zheng , Symeon Chatzinotas , Tareq Y. Al-Naffouri

Noncollinear (NC) magnetism and spin-orbit coupling (SOC) are indispensable for predictive ab initio materials simulations with pronounced relativistic effects and magnetic frustration, yet they significantly increase the cost of…

Strongly correlated systems containing d/f-electrons present a challenge to conventional density functional theory (DFT), such as the widely used local density approximation (LDA) or generalized gradient approximation (GGA). In this work,…

Strongly Correlated Electrons · Physics 2024-01-19 Bei-Lei Liu , Yue-Chao Wang , Yu Liu , Hai-Feng Liu , Hai-Feng Song

We study the uniform electron gas with a gap model in the context of density functional theory. Based on this analysis, we construct two local gap models that realize generalized gradient approximation (GGA) correlation functionals…

Other Condensed Matter · Physics 2015-01-22 E. Fabiano , P. E. Trevisanutto , A. Terentjevs , L. A. Constantin

Plane-wave electronic-structure predictions based upon orbital-dependent density-functional theory (OD-DFT) approximations, such as hybrid density-functional methods and self-interaction density-functional corrections, are severely affected…

Materials Science · Physics 2011-10-19 Yanli Li , Ismaila Dabo

In this chapter, we show how the use of differential coding and the presence of phase slips in the transmission channel affect the total achievable information rates and capacity of a system. By means of the commonly used QPSK modulation,…

Information Theory · Computer Science 2017-04-18 Laurent Schmalen , Stephan ten Brink , Andreas Leven
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