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Ultra-fast electronic phenomena originating from finite temperature, such as nonlinear optical excitation, can be simulated with high fidelity via real-time time dependent density functional theory (rt-TDDFT) calculations with hybrid…

Materials Science · Physics 2025-01-07 Rongrong Liu , Zhuoqiang Guo , Qiuchen Sha , Tong Zhao , Haibo Li , Wei Hu , Lijun Liu , Guangming Tan , Weile Jia

The Particle-In-Cell (PIC) method is widely used in relativistic particle beam and laser plasma modeling. However, the PIC method exhibits numerical instabilities that can render unphysical simulation results or even destroy the simulation.…

Plasma Physics · Physics 2016-05-04 M. D. Meyers , C. -K. Huang , Y. Zeng , S. A. Yi , B. J. Albright

The electron-electron pair distribution functions (PDF) of the 2-D electron fluid (2DEF) in the quantum regime (at T=0) are calculated using a classical-map-hyper-netted-chain (CHNC) scheme and compared with currently available Quantum…

Materials Science · Physics 2010-10-26 M. W. C. Dharma-wardana

Understanding the coolant thermal hydraulics in rod bundles is essential to the design of nuclear reactors. However, flows with low Reynolds numbers present serious modeling challenges, especially in heat transfer and natural convection.…

Fluid Dynamics · Physics 2023-08-31 Carolina Bourdot Dutra , Elia Merzari

It has been found in recent heavy-ion experiments that the second and the third flow harmonics of direct photons are larger than most theoretical predictions. In this study, I construct effective parton phase-space distributions with…

Nuclear Theory · Physics 2015-07-22 Akihiko Monnai

We consider the description of a Fermi gas of free electrons given by the Boltzmann--Fermi--Dirac equation, and aim at providing a precise mathematical understanding of the Fermi ground state and its first-order approximation of excited…

Analysis of PDEs · Mathematics 2025-10-14 Benjamin Anwasia , Diogo Arsénio

Modeling of fluid flows requires corresponding adequate and effective approaches that would account for multiscale nature of the considered physics. Despite the tremendous growth of computational power in the past decades, modeling of fluid…

Fluid Dynamics · Physics 2025-06-24 Arsen S. Iskhakov , Nam T. Dinh

Non-Fermi liquids in $d=2$ spatial dimensions can arise from coupling a Fermi surface to a gapless boson. At finite temperature, however, the perturbative quantum field theory description breaks down due to infrared divergences. These are…

Strongly Correlated Electrons · Physics 2020-08-05 Jeremias Aguilera Damia , Mario Solis , Gonzalo Torroba

Diffusion models are a class of probabilistic generative models that have been widely used as a prior for image processing tasks like text conditional generation and inpainting. We demonstrate that these models can be adapted to make…

Machine Learning · Computer Science 2023-06-14 Marc Finzi , Anudhyan Boral , Andrew Gordon Wilson , Fei Sha , Leonardo Zepeda-Núñez

Multi-scale computational approaches are important for studies of novel, low-dimensional electronic devices since they are able to capture the different length-scales involved in the device operation, and at the same time describe critical…

Mesoscale and Nanoscale Physics · Physics 2019-04-04 Gaetano Calogero , Nick R. Papior , Mohammad Koleini , Matthew Helmi Leth Larsen , Mads Brandbyge

Convection-diffusion problems arise in the modelling of many physical processes. Their typical solutions exhibit boundary and/or interior layers. Despite the linear nature of the differential operator, these problems pose still-unanswered…

Numerical Analysis · Mathematics 2013-06-24 Martin Stynes

Classical paradigms for distributed learning, such as federated or decentralized gradient descent, employ consensus mechanisms to enforce homogeneity among agents. While these strategies have proven effective in i.i.d. scenarios, they can…

Machine Learning · Computer Science 2023-04-18 Shreya Wadehra , Roula Nassif , Stefan Vlaski

The DFN (Doyle-Fuller-Newman) model is well know for being accurate and computationally expensive. In situations where temperature gradients are important (eg fast charging) it is desirable to couple the temperature dynamics within a…

Chemical Physics · Physics 2022-08-11 Matthew Hunt , Florian Theil , Ferran Brosa Planella , W. Dhammika Widanage

We theoretically investigate the stochastic decay of persistent currents in a toroidal ultracold atomic superfluid caused by a perturbing barrier. Specifically, we perform detailed three-dimensional simulations to model the experiment of…

Quantum Gases · Physics 2021-11-02 Zain Mehdi , Ashton S. Bradley , Joseph J. Hope , Stuart S. Szigeti

The accurate and robust simulation of transcritical real-fluid effects is crucial for many engineering applications, such as fuel injection in internal combustion engines, rocket engines and gas turbines. For example, in diesel engines, the…

Fluid Dynamics · Physics 2017-05-31 Peter C. Ma , Yu Lv , Matthias Ihme

We establish a fundamental connection between score-based diffusion models and non-equilibrium thermodynamics by deriving performance limits based on entropy rates. Our main theoretical contribution is a lower bound on the negative…

Machine Learning · Computer Science 2025-10-08 Nathan X. Kodama , Michael Hinczewski

Flow and heat transfer in a compressor rotating disc cavity with axial throughflow is investigated using wall-modelled large-eddy simulations (WMLES). These are compared to measurements from recently published experiments and used to…

Fluid Dynamics · Physics 2024-05-24 Ruonan Wang , John W. Chew , Feng Gao , Olaf Marxen

Photo-excited carriers, distributed among the localized states of self-assembled quantum dots, often show very anomalous temperature dependent photoluminescence characteristics. The temperature dependence of the peak emission energy may be…

Other Condensed Matter · Physics 2009-11-11 Bhavtosh Bansal

Near a quantum critical point (QCP) in a metal, strong Fermion-Fermion interactions mediated by soft collective bosons give rise to two competing phenomena: non-Fermi liquid behavior and superconductivity that deviates from conventional BCS…

Superconductivity · Physics 2025-12-24 Ahmed Elezaby , Artem Abanov

Neuro-dynamic programming is a class of powerful techniques for approximating the solution to dynamic programming equations. In their most computationally attractive formulations, these techniques provide the approximate solution only…

Machine Learning · Computer Science 2016-04-18 Wei Chen , Dayu Huang , Ankur A. Kulkarni , Jayakrishnan Unnikrishnan , Quanyan Zhu , Prashant Mehta , Sean Meyn , Adam Wierman