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Driven by the need for describing and understanding wave propagation in structural materials and components, several analytical, numerical, and experimental techniques have been developed to obtain dispersion curves. Accurate…

Signal Processing · Electrical Eng. & Systems 2020-02-26 Mohammad I. Albakri , Vijaya V. N. Sriram Malladi , Serkan Gugercin , Pablo A. Tarazaga

This paper introduces STRIPE (Simulated Transport of RF Impurity Production and Emission), an advanced modeling framework designed to analyze material erosion and the global transport of eroded impurities originating from radio-frequency…

Orbital angular momentum (OAM) can enhance the spectral efficiency by multiplying a set of orthogonal modes on the same frequency channel. To maintain the orthogonal among different OAM modes, perfect alignments between transmitters and…

Signal Processing · Electrical Eng. & Systems 2025-01-27 Xiaoyan Ma , Yufei Zhao , Haixia Zhang , Yong Liang Guan , Chau Yuen

Machine-learning (ML) techniques provide a new and encouraging perspective for constructing turbulence models for Reynolds-averaged Navier--Stokes (RANS) simulations. In this study, an iterative ML-RANS computational framework is proposed…

Fluid Dynamics · Physics 2021-07-27 Weishuo Liu , Jian Fang , Stefano Rolfo , Charles Moulinec , David R Emerson

Image super-resolution (SR) has attracted increasing attention due to its wide applications. However, current SR methods generally suffer from over-smoothing and artifacts, and most work only with fixed magnifications. This paper introduces…

Computer Vision and Pattern Recognition · Computer Science 2023-09-06 Sicheng Gao , Xuhui Liu , Bohan Zeng , Sheng Xu , Yanjing Li , Xiaoyan Luo , Jianzhuang Liu , Xiantong Zhen , Baochang Zhang

Many biochemical applications such as molecular property prediction require models to generalize beyond their training domains (environments). Moreover, natural environments in these tasks are structured, defined by complex descriptors such…

Machine Learning · Computer Science 2020-10-08 Wengong Jin , Regina Barzilay , Tommi Jaakkola

Numerous applications require the simultaneous redistribution of the irradiance and phase of a laser beam. The beam shape is thereby determined by the respective application. An elegant way to control the irradiance and phase at the same…

Optics · Physics 2017-04-25 Christoph Bösel , Norman G. Worku , Herbert Gross

A set of boundary conditions called the Transpiration-Resistance Model (TRM) are investigated in altering near-wall turbulence. The TRM has been previously proposed by \citet{Lacis2020} as a means of representing the net effect of surface…

The problem of the resolution of turbulent flows in adaptive mesh refinement (AMR) simulations is investigated by means of 3D hydrodynamical simulations in an idealised setup, representing a moving subcluster during a merger event. AMR…

Astrophysics · Physics 2009-11-13 L. Iapichino , J. Adamek , W. Schmidt , J. C. Niemeyer

The exponential computational cost of describing strongly correlated electrons can be mitigated by adopting a reduced density-matrix (RDM)-based description of the electronic structure. While variational two-electron RDM (v2RDM) methods can…

Chemical Physics · Physics 2026-01-06 Grier M. Jones , Run. R. Li , A. Eugene DePrince , Konstantinos D. Vogiatzis

A structure-preserving kernel ridge regression method is presented that allows the recovery of nonlinear Hamiltonian functions out of datasets made of noisy observations of Hamiltonian vector fields. The method proposes a closed-form…

Machine Learning · Statistics 2025-04-07 Jianyu Hu , Juan-Pablo Ortega , Daiying Yin

We describe a method for recovering the irradiance underlying a collection of images corrupted by atmospheric turbulence. Since supervised data is often technically impossible to obtain, assumptions and biases have to be imposed to solve…

Computer Vision and Pattern Recognition · Computer Science 2024-06-25 Dong Lao , Congli Wang , Alex Wong , Stefano Soatto

Precipitation of fine particles into the base material of a metal is a potent strengthening mechanism. This is numerically analyzed within a continuum framework based on a higher order strain gradient plasticity theory and by use of an…

Materials Science · Physics 2021-06-17 Mohammadali Asgharzadeh , Jonas Faleskog

This study investigates the efficacy of Conditional Restricted Boltzmann Machines (CRBMs) for modeling high-dimensional financial time series and detecting systemic risk regimes. We extend the classical application of static Restricted…

Statistical Finance · Quantitative Finance 2026-01-01 Siddhartha Srinivas Rentala

A closure theory is developed for inhomogeneous turbulent flow, which enables a systematic derivation of the turbulence constitutive relations without relying on any empirical parameters. Renormalized-perturbation approximation is performed…

Fluid Dynamics · Physics 2019-06-26 Taketo Ariki

We present a machine learning approach to the inversion of Fredholm integrals of the first kind. The approach provides a natural regularization in cases where the inverse of the Fredholm kernel is ill-conditioned. It also provides an…

Strongly Correlated Electrons · Physics 2016-12-16 Louis-Francois Arsenault , Richard Neuberg , Lauren A. Hannah , Andrew J. Millis

In a recent paper by Cabrera et al (Chaos, Solitons and Fractals 2021 146 110876), a linearization of DRM differences equation, (Delayed Regulation Model), has been proposed as a scheme to explain transfer of energy through different scales…

Statistical Mechanics · Physics 2023-09-07 Juan S. Medina-Alvarez

The spectral properties associated with laminar, anti-parallel reconnection are examined using a 2.5D kinetic particle in cell (PIC) simulation. Both the reconnection rate and the energy spectrum exhibit three distinct phases: an initiation…

We rigorously determine the scale-independent short range elastic parameters in the relaxed micromorphic generalized continuum model for a given periodic microstructure. This is done using both classical periodic homogenization and a new…

Applied Physics · Physics 2019-10-01 Patrizio Neff , Bernhard Eidel , Marco Valerio d'Agostino , Angela Madeo

Random Phase Approximation (RPA) provides a very convenient tool to study the ensembles of weakly interacting waves, commonly called Wave Turbulence. In its traditional formulation, RPA assumes that phases of interacting waves are random…

Mathematical Physics · Physics 2009-11-10 Yeontaek Choi , Yuri V. Lvov , Sergey Nazarenko