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Using Kubo's linear response theory, we derive expressions for the frequency-dependent electrical conductivity (Kubo-Greenwood formula), thermopower, and thermal conductivity in a strongly correlated electron system. These are evaluated…

Plasma Physics · Physics 2012-05-04 Bastian Holst , Martin French , Ronald Redmer

Aiming at the dilemma that most laboratory data-driven diagnostic and prognostic methods cannot be applied to field batteries in passenger cars and energy storage systems, this paper proposes a method to bridge field data and laboratory…

Applications · Statistics 2025-05-15 Yanbin Zhao , Hao Liu , Zhihua Deng , Tong Li , Haoyi Jiang , Zhenfei Ling , Xingkai Wang , Lei Zhang , Xiaoping Ouyang

This work presents a new approach to efficiently model the cathode in the moving boundary value problem of electrochemical machining. Until recently, the process simulation with finite elements had the drawback of remeshing required by the…

Computational Engineering, Finance, and Science · Computer Science 2023-01-12 Tim van der Velden , Stephan Ritzert , Stefanie Reese , Johanna Waimann

Frequency-domain electromagnetic (FDEM) data of the subsurface are determined by electrical conductivity and magnetic susceptibility. We apply a Kalman Ensemble generator (KEG) to one-dimensional probabilistic multi-layer inversion of FDEM…

Charge transport in QD solids is typically understood as thermally activated tunneling or hopping between states that are localized on individual QDs. Here, we show that the slow relaxation that is associated with the disorder-broadened…

Disordered Systems and Neural Networks · Physics 2025-11-19 Morteza Shokrani , Xinlu Wu , Ebbo Krahmer , Martijn Kemerink

Un-gated thermionic cathode RF guns are well known as a robust source of electrons for many accelerator applications. These sources are in principle scalable to high currents without degradation of the transverse emittance due to control…

Accelerator Physics · Physics 2017-05-04 J. P. Edelen , J. R. Harris

A precise understanding of the radio emission from extensive air showers is of fundamental importance for the design of cosmic ray radio detectors as well as the analysis and interpretation of their data. In recent years, tremendous…

High Energy Astrophysical Phenomena · Physics 2015-06-12 T. Huege

Machine learning (ML) applications to time series energy utilization forecasting problems are a challenging assignment due to a variety of factors. Chief among these is the non-homogeneity of the energy utilization datasets and the…

Machine Learning · Computer Science 2023-09-06 Jiacong Xu , Riley Kilfoyle , Zixiang Xiong , Ligang Lu

This Paper outlines study behaviour of rotating shaft with high speed under thermal effects. The method of obtaining the frequency response functions of a rotor system with study whirl effect in this revision the raw data obtained from the…

Applications · Statistics 2012-08-20 Hisham A. H. Al-Khazali , Mohamad R. Askari

We present a set of neural network models that reproduce the dynamics of electron fluxes in the range of 50 keV $\sim$ 1 MeV in the outer radiation belt. The Outer Radiation belt Electron Neural net model for Medium energy…

The spectral conductivity, i.e., the electrical conductivity as a function of the Fermi energy, is a cornerstone in determining the thermoelectric transport properties of electrons. However, the spectral conductivity depends on…

Statistical Mechanics · Physics 2022-11-02 Tomoki Hirosawa , Frank Schäfer , Hideaki Maebashi , Hiroyasu Matsuura , Masao Ogata

The proximity of the anode to a curved field electron emitter alters the electric field at the apex and its neighbourhood. A formula for the apex field enhancement factor, $\gamma_a(D)$, for generic smooth emitters is derived using the line…

Applied Physics · Physics 2022-01-06 Debabrata Biswas

Accurate prediction of hypersonic flow fields over a compression ramp is critical for aerodynamic design but remains challenging due to the scarcity of experimental measurements such as velocity. This study systematically develops a data…

Fluid Dynamics · Physics 2025-11-26 Yuan Jia , Guoqin Zhao , Hao Ma , Xin Li , Chi Zhang , Chih-Yung Wen

Determining the electric field (E-field) distribution on the Sun's photosphere is essential for quantitative studies of how energy flows from the Sun's photosphere, through the corona, and into the heliosphere. This E-field also provides…

Solar and Stellar Astrophysics · Physics 2014-11-20 G. H. Fisher , B. T. Welsch , W. P. Abbett , D. J. Bercik

Deep learning applications at the network edge lead to a significant growth in AI-related carbon emissions, presenting a critical sustainability challenge. The existing edge computing frameworks optimize for latency and throughput, but they…

Distributed, Parallel, and Cluster Computing · Computer Science 2026-04-02 Guilin Zhang , Wulan Guo , Ziqi Tan , Chuanyi Sun , Hailong Jiang

Within the framework of Classical Electrodynamics (CED) it is common practice to choose freely an arbitrary gauge condition with respect to a gauge transformation of the electromagnetic potentials. The Lorenz gauge condition allows for the…

Classical Physics · Physics 2007-05-23 Koen J. van Vlaenderen

Recently several works have appeared in the literature in which authors try to describe Freeze Out (FO) in energetic heavy ion collisions based on the Boltzmann Transport Equation (BTE). The aim of this work is to point out the limitations…

High Energy Physics - Phenomenology · Physics 2009-11-11 V. K. Magas , L. P. Csernai , E. Molnar , A. Nyiri , K. Tamosiunas

Effective field theories (EFT) parameterize the long-distance effects of short-distance dynamics whose details may or may not be known. It is known that EFT coefficients must obey certain positivity constraints if causality and unitarity…

High Energy Physics - Theory · Physics 2021-06-16 Simon Caron-Huot , Vincent Van Duong

The joint prediction of continuous fields and statistical estimation of the underlying discrete parameters is a common problem for many physical systems, governed by PDEs. Hitherto, it has been separately addressed by employing operator…

Machine Learning · Computer Science 2024-11-06 Levi E. Lingsch , Dana Grund , Siddhartha Mishra , Georgios Kissas

Partial differential equations (PDEs) that fit scientific data can represent physical laws with explainable mechanisms for various mathematically-oriented subjects, such as physics and finance. The data-driven discovery of PDEs from…

Machine Learning · Computer Science 2023-05-29 Yingtao Luo , Qiang Liu , Yuntian Chen , Wenbo Hu , Tian Tian , Jun Zhu
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