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This article is devoted to studying the inverse scattering for the fractional Schr\"{o}dinger equation, and in particular we solve the Born approximation problem. Based on the ($p$,$q$)-type resolvent estimate for the fractional Laplacian,…

Analysis of PDEs · Mathematics 2025-09-17 Saumyajit Das , Tuhin Ghosh , Shiqi Ma

In many modern imaging applications the desire to reconstruct high resolution images, coupled with the abundance of data from acquisition using ultra-fast detectors, have led to new challenges in image reconstruction. A main challenge is…

Numerical Analysis · Mathematics 2020-06-24 Julianne Chung , Matthias Chung , J. Tanner Slagel , Luis Tenorio

The reverse space-time (RST) Sine-Gordon, Sinh-Gordon and nonlinear Schr\"odinger equations were recently introduced and shown to be integrable infinite-dimensional dynamical systems. The inverse scattering transform (IST) for rapidly…

Mathematical Physics · Physics 2017-03-08 Mark J. Ablowitz , Bao-Feng Feng , Xu-Dan Luo , Ziad H. Musslimani

Consider the inverse random source scattering problem for the two-dimensional time-harmonic elastic wave equation with an inhomogeneous, anisotropic mass density. The source is modeled as a microlocally isotropic generalized Gaussian random…

Analysis of PDEs · Mathematics 2018-12-27 Jianliang Li , Peijun Li

Electromagnetic inverse scattering problems (ISPs) aim to retrieve permittivities of dielectric scatterers from the scattering measurement. It is often highly nonlinear, caus-ing the problem to be very difficult to solve. To alleviate the…

Image and Video Processing · Electrical Eng. & Systems 2023-07-19 Huilin Zhou , Tao Ouyang , Yadan Li , Jian Liu , Qiegen Liu

In this paper, a reduced-order model (ROM) based on the proper orthogonal decomposition and the discrete empirical interpolation method is proposed for efficiently simulating time-fractional partial differential equations (TFPDEs). Both…

Numerical Analysis · Mathematics 2024-02-07 Hongfei Fu , Hong Wang , Zhu Wang

We propose a new method in which a generative network (GN) integrate into a reduced-order model (ROM) framework is used to solve inverse problems for partial differential equations (PDE). The aim is to match available measurements and…

Machine Learning · Computer Science 2025-06-17 Vinicius L. S. Silva , Claire E. Heaney , Nenko Nenov , Christopher C. Pain

A class of negative order Ablowitz--Kaup--Newell--Segur nonlinear evolution equations are obtained by applying the Lax hierarchy of the first order linear system of three equations. The inverse scattering problem on the whole axis are…

Exactly Solvable and Integrable Systems · Physics 2024-08-08 Mansur I. Ismailov , Cihan Sabaz

We investigate the effect of the breaking of integrability in the integrals of motion of a sine-Gordon-like system. The class of quasi-integrable models, discussed in the literature, inherits some of the integrable properties they are…

Exactly Solvable and Integrable Systems · Physics 2024-08-20 P. H. S. Palheta , P. E. G. Assis , T. M. N. Gonçalves

This work studies the direct and inverse fixed energy scattering problem for two-dimensional Schroedinger equation with rather general nonlinear index of refraction. In particular, using the Born approximation we prove that all…

Mathematical Physics · Physics 2014-12-02 Georgios Fotopoulos , Valery Serov

In this study, we present and analyze a novel variant of the stochastic gradient descent method, referred as Stochastic data-driven Bouligand Landweber iteration tailored for addressing the system of non-smooth ill-posed inverse problems.…

Functional Analysis · Mathematics 2024-02-08 Harshit Bajpai , Gaurav Mittal , Ankik Kumar Giri

Reduced-order models (ROMs) remain generally unreliable for convection-dominated problems, such as those encountered in hypersonic flows, due to the slowly decaying Kolmogorov $n$-width of linear subspace approximations, known as the…

Numerical Analysis · Mathematics 2025-03-25 Victor Zucatti , Matthew J. Zahr

The image reconstruction of chromophore concentrations using Diffuse Optical Tomography (DOT) data can be described mathematically as an ill-posed inverse problem. Recent work has shown that the use of hyperspectral DOT data, as opposed to…

Numerical Analysis · Mathematics 2014-10-16 Arvind K. Saibaba , Misha Kilmer , Eric Miller , Sergio Fantini

Direct and inverse scattering problem for an operator with non-local potential is solved in the paper. The method is based on the Riemann boundary value problem on a bundle of three straight lines. Description of scattering problem data is…

Classical Analysis and ODEs · Mathematics 2022-01-27 V. A. Zolotarev

This work introduces a reduced order modeling (ROM) framework for the solution of parameterized second-order linear elliptic partial differential equations formulated on unfitted geometries. The goal is to construct efficient…

Numerical Analysis · Mathematics 2025-10-14 Margarita Chasapi , Pablo Antolin , Annalisa Buffa

Inverse problems have many applications in science and engineering. In Computer vision, several image restoration tasks such as inpainting, deblurring, and super-resolution can be formally modeled as inverse problems. Recently, methods have…

Computer Vision and Pattern Recognition · Computer Science 2024-09-19 Sai Bharath Chandra Gutha , Ricardo Vinuesa , Hossein Azizpour

A comprehensive approach for real-time computations using a database of parameterized linear reduced-order models (ROMs) is proposed. The method proceeds by sampling offline ROMs for specific values of the parameters and interpolating…

Numerical Analysis · Mathematics 2015-06-24 David Amsallem , Radek Tezaur , Charbel Farhat

The spectral transformation Lanczos method for the sparse symmetric definite generalized eigenvalue problem for matrices $A$ and $B$ is an iterative method that addresses the case of semidefinite or ill conditioned $B$ using a shifted and…

Numerical Analysis · Mathematics 2024-11-07 Michael Stewart

Highly accurate simulations of complex phenomena governed by partial differential equations (PDEs) typically require intrusive methods and entail expensive computational costs, which might become prohibitive when approximating steady-state…

Machine Learning · Computer Science 2023-05-17 Paolo Conti , Giorgio Gobat , Stefania Fresca , Andrea Manzoni , Attilio Frangi

Reduced-order modeling (ROM) commonly refers to the construction, based on a few solutions (referred to as snapshots) of an expensive discretized partial differential equation (PDE), and the subsequent application of low-dimensional…

Numerical Analysis · Mathematics 2019-05-22 Martin Hess , Alessandro Alla , Annalisa Quaini , Gianluigi Rozza , Max Gunzburger