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Related papers: Dynamical Kernels for Optical Excitations

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We identify the key property that the exchange-correlation (XC) kernel of time-dependent density functional theory must have in order to describe long-range charge-transfer excitations. We show that the discontinuity of the XC potential as…

Mesoscale and Nanoscale Physics · Physics 2015-05-30 M. Hellgren , E. K. U. Gross

The interplay of nuclear and electronic dynamics characterizes the multi-dimensional electronic spectra of various molecular and solid-state systems. Theoretically, the observable effect of such interplay can be accounted for by response…

Quantum Physics · Physics 2023-02-07 Filippo Troiani

We discuss the calculation of collective excitations in atomic clusters using the time-dependent local density approximation. In principle there are many formulations of the TDLDA, but we have found that a particularly efficient method for…

Atomic and Molecular Clusters · Physics 2009-10-30 G. F. Bertsch , K. Yabana

Alternative machine learning approaches that are computationally light with low latency and can work with only a small training dataset are needed for applications where the insatiable demand of deep learning methods for computing power and…

Optics · Physics 2021-07-29 Tingyi Zhou , Fabien Scalzo , Bahram Jalali

Multi-configuration range-separated density-functional theory is extended to the time-dependent regime. An exact variational formulation is derived. The approximation, which consists in combining a long-range…

Chemical Physics · Physics 2013-02-27 Emmanuel Fromager , Stefan Knecht , Hans Jørgen Aa. Jensen

We consider the dynamical electronic response function in theoretical frameworks that include nonlocal exchange interactions, such as the Bethe-Salpeter equation with the frequency independent approximation of the screened interaction,…

Materials Science · Physics 2025-06-10 Giovanni Caldarelli , Alberto Guandalini , Francesco Macheda , Francesco Mauri

This paper studies random operator-valued positive definite (p.d.) kernels and their connection to moment dilations. A class of random p.d. kernels is introduced in which the positivity requirement is imposed only in expectation, extending…

Functional Analysis · Mathematics 2025-08-15 James Tian

Optical kernel machines offer high throughput and low latency. A nonlinear optical kernel can handle complex nonlinear data, but power consumption is typically high with the conventional nonlinear optical approach. To overcome this issue,…

Optics · Physics 2025-11-25 SeungYun Han , Fei Xia , Sylvain Gigan , Bruno Loureiro , Hui Cao

We report a novel experimental technique to investigate ultrafast dynamics in photoexcited molecules by probing the third-order nonlinear optical susceptibility. A non-colinear 3-pulse scheme is developed to probe the ultrafast dynamics of…

It has been observed experimentally [H.R. Xia, C.Y. Ye, and S.Y. Zhu, Phys. Rev. Lett. {\bf 77}, 1032 (1996)] that quantum interference between two molecular transitions can lead to a suppression or enhancement of spontaneous emission. This…

Quantum Physics · Physics 2009-10-31 Jin Wang , H. M. Wiseman , Z. Ficek

The dynamical nucleus-nucleus potentials for some fusion reactions are investigated by using the improved quantum molecular dynamics (ImQMD) model with different sets of parameters in which the corresponding incompressibility coefficient of…

Nuclear Theory · Physics 2013-03-28 V. Zanganeh , N. Wang , O. N. Ghodsi

A microscopic model for thermal excitation of vibrational ground state of a molecule interacting with a condensed medium is developed. The master equation for evolution of occupancies of the vibrational levels is derived. The rate constant…

Statistical Mechanics · Physics 2011-03-04 V. I. Teslenko , D. Y. Iatsenko

We study linear-response time-dependent density-functional theory (DFT) based on the single-determinant range-separated hybrid (RSH) scheme, i.e. combining a long-range Hartree-Fock exchange kernel with a short-range DFT…

Chemical Physics · Physics 2015-06-15 Elisa Rebolini , Andreas Savin , Julien Toulouse

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

Gross--Oliveira--Kohn (GOK) ensemble density-functional theory (GOK-DFT) is a time-\textit{independent} extension of density-functional theory (DFT) which allows to compute excited-state energies via the derivatives of the ensemble energy…

Chemical Physics · Physics 2020-06-18 Clotilde Marut , Bruno Senjean , Emmanuel Fromager , Pierre-François Loos

We use effective field theory and thermal field theory to study the dynamical screening effect in the QED plasma on the $\alpha$-$\alpha$ scattering at the $^8$Be resonance. Dynamical screening leads to an imaginary part of the potential…

Nuclear Theory · Physics 2017-06-14 Xiaojun Yao , Thomas Mehen , Berndt Müller

Learning with kernels is an important concept in machine learning. Standard approaches for kernel methods often use predefined kernels that require careful selection of hyperparameters. To mitigate this burden, we propose in this paper a…

Machine Learning · Computer Science 2020-06-26 Yufan Zhou , Changyou Chen , Jinhui Xu

The formation of binary correlations in plasma is studied from the quantum kinetic equation. It is shown that this formation is much faster than dissipation due to collisions, in hot (dense) plasma the correlations form on the timescale of…

Strongly Correlated Electrons · Physics 2007-05-23 Klaus Morawetz , Václav Špička , Pavel Lipavský

The so-called tuned-correlated kernel (sometimes also called the first-order stable spline kernel) is one of the most widely used kernels for the regularized impulse response estimation. This kernel can be derived by applying an exponential…

Systems and Control · Electrical Eng. & Systems 2024-12-20 Yusuke Fujimoto , Tianchi Chen

Quantum embedding schemes have the potential to significantly reduce the computational cost of first principles calculations, whilst maintaining accuracy, particularly for calculations of electronic excitations in complex systems. In this…

Materials Science · Physics 2022-03-10 Joseph C. A. Prentice