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Related papers: Dynamical Kernels for Optical Excitations

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To explore the applicability of orbital-free density functional theory (OF-DFT) in nuclear physics, we perform a systematic benchmark of 36 one-point kinetic energy density functionals, which are originally developed for electron systems in…

Nuclear Theory · Physics 2026-05-20 Tian Shuai Shang , Jian Li , Haozhao Liang , Xinhui Wu , Cheng Ma , Wenhui Mi , Xuecheng Shao , Yanchao Wang

We calculate the correlation energy of a two-dimensional homogeneous electron gas using several available approximations for the exchange-correlation kernel $f_{\rm xc}(q,\omega)$ entering the linear dielectric response of the system. As in…

Mesoscale and Nanoscale Physics · Physics 2009-11-10 R. Asgari , M. Polini , B. Davoudi , M. P. Tosi

Solving the Bethe-Salpeter equation (BSE) for the optical polarization functions is a first principles means to model optical properties of materials including excitonic effects. One almost ubiquitously used approximation neglects the…

Materials Science · Physics 2023-07-11 Xiao Zhang , Joshua A. Leveillee , André Schleife

Impedance of all oxygen transport processes in PEM fuel cell has negative real part in some frequency domain. A model function (kernel) for calculation of distribution of relaxation times (DRT) of a PEM fuel cell is suggested. The kernel is…

Chemical Physics · Physics 2021-09-30 Andrei Kulikovsky

The coherent two-dimensional (2D) electronic spectra with respect to the singlet fission (SF) process in organic molecular aggregates are simulated by the Davydov ansatz combined with the Frenkel-Dirac time-dependent variational algorithm.…

Mesoscale and Nanoscale Physics · Physics 2018-01-17 Ke-Wei Sun , Yao Yao

We propose a simple dynamic exchange-correlation kernel of the uniform electron gas. We model the reduction of the electron-electron interaction due to short-range exchange-correlation effects by introducing a frequency-dependent…

Materials Science · Physics 2009-11-13 Lucian A. Constantin , J. M. Pitarke

Model inference for dynamical systems aims to estimate the future behaviour of a system from observations. Purely model-free statistical methods, such as Artificial Neural Networks, tend to perform poorly for such tasks. They are therefore…

Machine Learning · Computer Science 2019-08-07 David K. E. Green , Filip Rindler

A striking example of the need to accurately capture states of double-excitation character in molecules is seen in predicting photo-induced dynamics in small polyenes. Due to the coupling of electronic and nuclear motions,the dark 2$^1$Ag…

Chemical Physics · Physics 2024-12-25 Davood B. Dar , Neepa T. Maitra

A quantum kinetic theory is used to compute excitation induced dephasing in semiconductor quantum dots due to the Coulomb interaction with a continuum of states, such as a quantum well or a wetting layer. It is shown that a frequency…

Materials Science · Physics 2009-11-10 H. C. Schneider , W. W. Chow , S. W. Koch

A time-dependent formulation for electron-hole excitations in extended finite systems, based on the Bethe-Salpeter equation (BSE), is developed using a stochastic wave function approach. The time-dependent formulation builds on the…

Materials Science · Physics 2015-02-11 Eran Rabani , Roi Baer , Daniel Neuhauser

We consider a diffusion in $\mathbb{R}^n$ whose coordinates each behave as one-dimensional Brownian motions, that behave independently when apart, but have a sticky interaction when they meet. The diffusion in $\mathbb{R}^n$ can be viewed…

Probability · Mathematics 2021-04-15 Dom Brockington , Jon Warren

Femtosecond core-level transient absorption spectroscopy is utilized to investigate photoinduced dynamics of the charge density wave in 1T-TiSe2 at the Ti M2,3 edge (30-50 eV). Photoexcited carriers and phonons are found to primarily induce…

Materials Science · Physics 2022-11-08 Tobias Heinrich , Hung-Tzu Chang , Sergey Zayko , Kai Rossnagel , Murat Sivis , Claus Ropers

Working within the framework of the covariant perturbation theory, we obtain the coincidence limit of the heat kernel of an elliptic second order differential operator that is applicable to a large class of quantum field theories. The basis…

High Energy Physics - Theory · Physics 2008-12-18 Yuri V. Gusev

We present recent investigations on dipole and quadrupole excitations in spherical skin nuclei, particular exploring their connection to the thickness of the neutron skin. Our theoretical method relies on density functional theory, which…

Nuclear Theory · Physics 2009-11-13 N. Tsoneva , H. Lenske

Electromagnetic interactions serve as essential probes for studying and testing our understanding of the atomic nucleus, as they reveal emergent properties across the nuclear chart. We analyse their corresponding observables, which relate…

Nuclear Theory · Physics 2026-05-13 J. Dobaczewski , B. C. Backes , R. P. de Groote , A. Restrepo-Giraldo , X. Sun , H. Wibowo

Ensemble density functional theory (eDFT) is an exact time-independent alternative to time-dependent DFT (TD-DFT) for the calculation of excitation energies. Despite its formal simplicity and advantages in contrast to TD-DFT (multiple…

Strongly Correlated Electrons · Physics 2017-01-19 Killian Deur , Laurent Mazouin , Emmanuel Fromager

We propose a nonadiabatic time-dependent spin-density functional theory (TDSDFT) approach for studying the single-electron excited states and the ultrafast response of systems with strong electron correlations. The correlations are…

Strongly Correlated Electrons · Physics 2013-11-27 Volodymyr Turkowski , Talat S. Rahman

The dynamic membrane potential threshold, as one of the essential properties of a biological neuron, is a spontaneous regulation mechanism that maintains neuronal homeostasis, i.e., the constant overall spiking firing rate of a neuron. As…

Robotics · Computer Science 2023-06-21 Jianchuan Ding , Bo Dong , Felix Heide , Yufei Ding , Yunduo Zhou , Baocai Yin , Xin Yang

This survey is an introduction to positive definite kernels and the set of methods they have inspired in the machine learning literature, namely kernel methods. We first discuss some properties of positive definite kernels as well as…

Machine Learning · Statistics 2009-12-04 Marco Cuturi

Change-point analysis plays a significant role in various fields to reveal discrepancies in distribution in a sequence of observations. While a number of algorithms have been proposed for high-dimensional data, kernel-based methods have not…

Methodology · Statistics 2023-01-10 Hoseung Song , Hao Chen