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A general polarizable embedded (PE) quantum mechanics/molecular mechanics scheme for periodic systems is presented, describing mutual polarization of the two subsystems. The QM system, described with density functional theory (DFT), is…

We have compared the performance of Grimme style DH/DSD and Zhang-Xu-Goddard type xDH/xDSD forms for double hybrids. In the DH and DSD forms, KS orbitals with elevated HF exchange and damped DFT correlation are used, while in the xDH and…

Chemical Physics · Physics 2015-11-12 Manoj Kumar Kesharwani , Sebastian Kozuch , Jan M. L. Martin

Time-dependent density functional theory (TDDFT) is a standard approach for calculating optical excitations of molecules and solids, while ensemble DFT (EDFT) is a promising alternative under development. We introduce ensemble TDDFT…

Chemical Physics · Physics 2026-05-22 Kimberly J. Daas , Steven Crisostomo , Kieron Burke

Various methods going beyond density-functional theory (DFT), such as DFT+U, hybrid functionals, meta-GGAs, GW, and DFT-embedded dynamical mean field theory (eDMFT), have been developed to describe the electronic structure of correlated…

Strongly Correlated Electrons · Physics 2020-07-16 Subhasish Mandal , Kristjan Haule , Karin M. Rabe , David Vanderbilt

Density functional theory (DFT), the most widely adopted method in modern computational chemistry, fails to describe accurately the electronic structure of strongly correlated systems. Here we show that DFT can be formally and practically…

Chemical Physics · Physics 2022-04-18 Daniel Gibney , Jan-Niklas Boyn , David A. Mazziotti

The DMD (Dynamic Mode Decomposition) method has attracted widespread attention as a representative modal-decomposition method and can build a predictive model. However, the DMD may give predicted results that deviate from physical reality…

Computational Physics · Physics 2023-11-29 Yuhui Yin , Chenhui Kou , Shengkun Jia , Lu Lu , Xigang Yuan , Yiqing Luo

Molecular dynamics (MD) has long been the de facto choice for simulating complex atomistic systems from first principles. Recently deep learning models become a popular way to accelerate MD. Notwithstanding, existing models depend on…

Computational Engineering, Finance, and Science · Computer Science 2023-01-10 Fang Wu , Stan Z. Li

We introduce a Cascaded Diffusion Model (Cas-DM) that improves a Denoising Diffusion Probabilistic Model (DDPM) by effectively incorporating additional metric functions in training. Metric functions such as the LPIPS loss have been proven…

Computer Vision and Pattern Recognition · Computer Science 2024-01-05 Jie An , Zhengyuan Yang , Jianfeng Wang , Linjie Li , Zicheng Liu , Lijuan Wang , Jiebo Luo

The exact exchange-correlation (XC) potential in time-dependent density-functional theory (TDDFT) is known to develop steps and discontinuities upon change of the particle number in spatially confined regions or isolated subsystems. We…

Mesoscale and Nanoscale Physics · Physics 2019-03-27 Daniel Vieira , K. Capelle , C. A. Ullrich

We formulate a rigorous method for calculating a nonadiabatic (frequency-dependent) exchange-correlation (XC) kernel required for correct description of both equilibrium and nonequilibrium properties of strongly correlated systems within…

Strongly Correlated Electrons · Physics 2014-10-13 Volodymyr Turkowski , Talat S. Rahman

The observation of electric dipole moments (EDMs) in atomic systems due to parity and time-reversal violating (P,T-odd) interactions can probe new physics beyond the standard model and also provide insights into the matter-antimatter…

Atomic Physics · Physics 2018-08-01 B. K. Sahoo , B. P. Das

Theoretical simulation to phase change materials such as Ge-Sb-Te has suffered from two methodology issues. On the one hand, there is a lack of efficient band gap correction method for density functional theory, which is suitable for these…

Materials Science · Physics 2025-03-19 Shanzhong Xie , Kan-Hao Xue , Shaojie Yuan , Shengxin Yang , Heng Yu , Rongchuan Gu , Ming Xu , Xiangshui Miao

We investigate the impact of choosing regressors and molecular representations for the construction of fast machine learning (ML) models of thirteen electronic ground-state properties of organic molecules. The performance of each…

The predominance of Kohn-Sham density functional theory (KS-DFT) for the theoretical treatment of large experimentally relevant systems in molecular chemistry and materials science relies primarily on the existence of efficient software…

Computational Physics · Physics 2020-07-08 David B. Williams-Young , Wibe A. de Jong , Hubertus J. J. van Dam , Chao Yang

This paper proposes a novel multi-carrier modulation framework for high-mobility communication scenarios. Our key idea lies in spreading data symbols across the delay-Doppler (DD) domain through orthogonal chirp-Zak transform (CZT). To…

Signal Processing · Electrical Eng. & Systems 2025-11-25 Chaoyuan Bai , Pingzhi Fan , Zhengchun Zhou , Zilong Liu

We study the accuracy of Kohn-Sham density functional theory (DFT) for warm- and hot-dense matter (WDM and HDM). Specifically, considering a wide range of systems, we perform accurate ab initio molecular dynamics simulations with…

Computational Physics · Physics 2024-11-21 Phanish Suryanarayana , Arpit Bhardwaj , Xin Jing , Shashikant Kumar , John E. Pask

A review of the approximations in any time-dependent density functional calculation of excitation energies is given. The single-pole approximation for the susceptibility is used to understand errors in popular approximations for the…

Materials Science · Physics 2007-05-23 Kieron Burke , Martin Petersilka , E. K. U. Gross

The Extended Discrete Element Method (XDEM) is an innovative numerical simulation technique that extends the dynamics of granular materials known as Discrete Element Method (DEM) by additional properties such as the thermodynamic state,…

Computational Engineering, Finance, and Science · Computer Science 2022-08-31 Abdoul Wahid Mainassara Checkaraou , Xavier Besseron , Alban Rousset , Fenglei Qi , Bernhard Peters

The idea of using fragment embedding to circumvent the high computational scaling of accurate electronic structure methods while retaining high accuracy has been a long-standing goal for quantum chemists. Traditional fragment embedding…

Chemical Physics · Physics 2022-10-11 Hong-Zhou Ye , Matthew Welborn , Nathan D. Ricke , Troy Van Voorhis

Deep learning-based techniques for the analysis of multimodal remote sensing data have become popular due to their ability to effectively integrate complementary spatial, spectral, and structural information from different sensors.…

Computer Vision and Pattern Recognition · Computer Science 2026-04-10 Hao Liu , Yongjie Zheng , Yuhan Kang , Mingyang Zhang , Maoguo Gong , Lorenzo Bruzzone
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