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This paper is concerned with the inverse time-harmonic elastic scattering problem of recovering unbounded rough surfaces in two dimensions. We assume that elastic plane waves with different directions are incident onto a rigid rough surface…

Numerical Analysis · Mathematics 2018-04-09 Guanghui Hu , Xiaoli Liu , Bo Zhang , Haiwen Zhang

The Material Point Method (MPM) is a hybrid Eulerian Lagrangian simulation technique for solid mechanics with significant deformation. Structured background grids are commonly employed in the standard MPM, but they may give rise to several…

Computational Engineering, Finance, and Science · Computer Science 2024-08-02 Yadi Cao , Yidong Zhao , Minchen Li , Yin Yang , Jinhyun Choo , Demetri Terzopoulos , Chenfanfu Jiang

Sampling-based algorithms are classical approaches to perform Bayesian inference in inverse problems. They provide estimators with the associated credibility intervals to quantify the uncertainty on the estimators. Although these methods…

Methodology · Statistics 2023-11-28 Pierre-Antoine Thouvenin , Audrey Repetti , Pierre Chainais

In this paper, we propose a novel numerical method for modeling nanostructures containing dispersive and nonlinear two-dimensional (2D) materials, by incorporating a nonlinear generalized source (GS) into the finite-difference time-domain…

In this paper, we present the linear decomposition method (LDM), which we developed to detect and analyze pulsar profile variations and mode changing behaviour. We developed LDM utilizing the likelihood function approach assuming the…

High Energy Astrophysical Phenomena · Physics 2025-03-07 Longfei Hao , Zhixuan Li , Faxin Shen , Yonghua Xu , Yuxiang Huang , Kejia Lee , Qingzheng Yu , Hongguang Wang

We apply a mass reconstruction technique to simulated large-scale structure gravitational distortion maps, from 2.5' to 10 degree scales, for different cosmological scenarii. The projected mass is reconstructed using a non-parametric least…

Astrophysics · Physics 2007-05-23 L. Van Waerbeke , F. Bernardeau , Y. Mellier

The 3D Gaussian splatting methods are getting popular. However, they work directly on the signal, leading to a dense representation of the signal. Even with some techniques such as pruning or distillation, the results are still dense. In…

Computer Vision and Pattern Recognition · Computer Science 2024-05-10 Yuanhao Gong

This paper considers an inverse shape problem for recovering an unknown clamped obstacle in two dimensions from far--field measurements generated by a single incident wave or just a few incident waves for the biharmonic (flexural) wave…

Analysis of PDEs · Mathematics 2026-05-13 Isaac Harris , General Ozochiawaeze

In this paper, a linear model based on multiple measurement vectors model is proposed to formulate the inverse scattering problem of highly conductive objects at one single frequency. Considering the induced currents which are mostly…

Signal Processing · Electrical Eng. & Systems 2019-06-27 Shilong Sun , Bert Jan Kooij , Alexander G. Yarovoy

Achieving real-time Simultaneous Localization and Mapping (SLAM) based on 3D Gaussian splatting (3DGS) in large-scale real-world environments remains challenging, as existing methods still struggle to jointly achieve low-latency pose…

Objective - Shear wave elastography has enriched ultrasound medical imaging with quantitative measurements of tissue stiffness. However, this method still suffers from some limitations due to viscoelasticity, guiding geometry or static…

Soft Condensed Matter · Physics 2023-12-25 Alexandre Delory , Daniel A. Kiefer , Claire Prada , Fabrice Lemoult

We describe a self calibrating optical technique that allows to perform absolute measurements of scattering cross sections for the light scattered at extremely small angles. Very good performances are obtained by using a very simple optical…

Optics · Physics 2009-11-10 Doriano Brogioli , Alberto Vailati , Marzio Giglio

Knowing the stress within a soft material is of fundamental interest to basic research and practical applications, such as soft matter devices, biomaterial engineering, and medical sciences. However, it is challenging to measure stress…

Soft Condensed Matter · Physics 2022-01-07 Guo-Yang Li , Artur L. Gower , Michel Destrade , Seok-Hyun Yun

Bayesian statistical inference for Generalized Linear Models (GLMs) with parameters lying on a constrained space is of general interest (e.g., in monotonic or convex regression), but often constructing valid prior distributions supported on…

Methodology · Statistics 2021-09-02 Rahul Ghosal , Sujit K. Ghosh

The technique of low-temperature Laser Scanning Microscopy (LSM) has been applied to the investigation of local microwave properties in operating YBa2Cu3O7/LaAlO3 thin-film resonators patterned into a meandering strip transmission line. By…

Superconductivity · Physics 2009-09-14 Alexander P. Zhuravel , Steven M. Anlage , Alexey V. Ustinov

This paper is concerned with the inverse problem of time-harmonic acoustic scattering by an unbounded, locally rough interface which is assumed to be a local perturbation of a plane. The purpose of this paper is to recover the local…

Analysis of PDEs · Mathematics 2020-08-05 Jianliang Li , Jiaqing Yang , Bo Zhang

In the automatic reassembly of fragments acquired using laser scanners to reconstruct objects, a crucial step is the matching of fractured surfaces. In this paper, we propose a novel local descriptor that uses the Gaussian Mixture Model…

Computer Vision and Pattern Recognition · Computer Science 2026-04-24 Meijun Xiong , Zhenguo Shi , Xinyu Zhou , Yuhe Zhang , Shunli Zhang

We present a perturbative technique for modeling the scattering of light by a nonlinear material. This approach eliminates the need for an iterative algorithm to solve the fully coupled nonlinear problem. We demonstrate its effectiveness in…

Optics · Physics 2026-04-01 Jérémy Itier , Gilles Renversez , Frédéric Zolla

Over the past twenty years, the field of plasmonics has been revolutionized with the isolation and utilization of two--dimensional materials, particularly graphene. Consequently there is significant interest in rapid, robust, and highly…

Numerical Analysis · Mathematics 2024-10-10 David Nicholls , Tianyu Zhu

The Gaussian process latent variable model (GP-LVM) is a popular approach to non-linear probabilistic dimensionality reduction. One design choice for the model is the number of latent variables. We present a spike and slab prior for the…

Machine Learning · Statistics 2015-05-12 Zhenwen Dai , James Hensman , Neil Lawrence