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In this study, we explore the application of an artificial recurrent neural network (RNN) called Long Short-Term Memory (LSTM) as an alternative to a turbulent Reynolds-Averaged Navier-Stokes (RANS) model. The LSTM models are utilized to…

Fluid Dynamics · Physics 2023-07-27 Hugo D. Pasinato , Nicólas F. Moguilner Reh

A most important aspect in the field of traffic modeling is the simulation of bottleneck situations. For their realistic description a macroscopic multi-lane model for uni-directional freeways including acceleration, deceleration, velocity…

Statistical Mechanics · Physics 2009-10-31 Dirk Helbing

We introduce a latent 3D representation that models 3D surfaces as probability density functions in 3D, i.e., p(x,y,z), with flow-matching. Our representation is specifically designed for consumption by machine learning models, offering…

Computer Vision and Pattern Recognition · Computer Science 2025-03-26 Jen-Hao Rick Chang , Yuyang Wang , Miguel Angel Bautista Martin , Jiatao Gu , Xiaoming Zhao , Josh Susskind , Oncel Tuzel

Mass-conserving reaction-diffusion systems with bistable nonlinearity are useful models for studying cell polarity formation, which is a key process in cell division and differentiation. We rigorously show the existence and stability of…

Analysis of PDEs · Mathematics 2025-05-23 Masataka Kuwamura , Takashi Teramoto , Hideo Ikeda

Liquid scintillator detectors are playing an increasingly important role in low-energy neutrino experiments. In this article, we describe a generic energy response model of liquid scintillator detectors that provides energy estimations of…

Instrumentation and Detectors · Physics 2019-02-18 Logan Lebanowski , Linyan Wan , Xiangpan Ji , Zhe Wang , Shaomin Chen

Flow models have recently made great progress at modeling ordinal discrete data such as images and audio. Due to the continuous nature of flow models, dequantization is typically applied when using them for such discrete data, resulting in…

Machine Learning · Computer Science 2020-11-02 Didrik Nielsen , Ole Winther

Machine Learning (ML) models have, in contrast to their usefulness in molecular dynamics studies, had limited success as surrogate potentials for reaction barrier search. It is due to the scarcity of training data in relevant transition…

Chemical Physics · Physics 2022-09-02 Mathias Schreiner , Arghya Bhowmik , Tejs Vegge , Jonas Busk , Ole Winther

We propose a new two-stage model for acceleration of electrons in solar flares. In the first stage, electrons are accelerated stochastically in a post-reconnection turbulent downflow. The second stage is the reprocessing of a subset of…

Astrophysics · Physics 2008-11-26 Robert Selkowitz , Eric G. Blackman

Predicting future states or actions of a given system remains a fundamental, yet unsolved challenge of intelligence, especially in the scope of complex and non-deterministic scenarios, such as modeling behavior of humans. Existing…

Machine Learning · Computer Science 2020-12-01 Maciej Zięba , Marcin Przewięźlikowski , Marek Śmieja , Jacek Tabor , Tomasz Trzcinski , Przemysław Spurek

Representation Engineering analyses often characterize refusal using static directions extracted from terminal or pooled representations. We ask whether this view misses how refusal is constructed across layer-token positions. Using causal…

Cryptography and Security · Computer Science 2026-05-27 Xulin Hu , Che Wang , Wei Yang Bryan Lim , Jianbo Gao , Zhong Chen

This paper presents a novel methodology for the direct numerical modeling and simulation of turbulent flows. The kinetic model equation is firstly extended to turbulent flow with the account of coupled evolution of kinetic, thermal, and…

Computational Physics · Physics 2025-03-11 Xiaojian Yang , Kun Xu

A part of non-Newtonian fluids are yield stress fluids. They require a minimum stress to flow. Below this minimum value, yield stress fluids remain solid. To date, 1D and 2D numerical models have been used predominantly to study free…

Fluid Dynamics · Physics 2018-08-03 N Schaer , J. Vazquez , M. Dufresne , G Isenmann , J. Wertel

A normalizing flow models a complex probability density as an invertible transformation of a simple density. The invertibility means that we can evaluate densities and generate samples from a flow. In practice, autoregressive flow-based…

Machine Learning · Statistics 2019-06-06 Conor Durkan , Artur Bekasov , Iain Murray , George Papamakarios

In the framework of a final state interaction model, we show that the so-called radial flow, i.e. the almost linear increase of the inverse slope $T$ with the mass of the produced particle, is already contained in the initial condition --…

High Energy Physics - Phenomenology · Physics 2007-05-23 A. Capella , E. G. Ferreiro

Reconstructing near-wall turbulence from wall-based measurements is a critical yet inherently ill-posed problem in wall-bounded flows, where limited sensing and spatially heterogeneous flow-wall coupling challenge deterministic estimation…

Fluid Dynamics · Physics 2025-04-22 Meet Hemant Parikh , Xiantao Fan , Jian-Xun Wang

Estimating the heat loads on re-entry vehicles is a crucial part of preparing for atmospheric re-entry manoeuvres. Re-entry flows at high altitudes are in the rarefied regime and are governed by high enthalpies and thermodynamic…

Computational Physics · Physics 2020-07-14 Wladimir Reschke , Marcel Pfeiffer , Stefanos Fasoulas

We propose an efficient method to compute reaction rate constants of thermally activated processes occurring in many-body systems at finite temperature. The method consists in two steps: first, paths are sampled using a transition path…

Statistical Mechanics · Physics 2011-12-22 Massimiliano Picciani

A model for ionization and recombination collisions in a multifluid plasma is formulated using the framework introduced in previous work [{Phys. Plasmas} \textbf{22}, 093512 (2015)]. The exchange source terms for density, momentum and…

Plasma Physics · Physics 2016-06-22 H. P. Le , J. -L. Cambier

In traditional models only an order one fraction of energy is transferred from the inflaton to radiation through nonperturbative resonance production in preheating immediately after inflation, due to backreaction effects. We propose a…

High Energy Physics - Phenomenology · Physics 2021-05-25 JiJi Fan , Kaloian D. Lozanov , Qianshu Lu

A renormalization group flow equation with a scale-dependent transformation of field variables gives a unified description of fundamental and composite degrees of freedom. In the context of the effective average action, we study the…

High Energy Physics - Theory · Physics 2009-11-07 Holger Gies , Christof Wetterich