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Neural operators have emerged as a powerful tool for solving partial differential equations in the context of scientific machine learning. Here, we implement and train a modified Fourier neural operator as a surrogate solver for…

Computational Physics · Physics 2023-03-29 Yannick Augenstein , Taavi Repän , Carsten Rockstuhl

Pseudodifferential parabolic equations with an operator square root arise in wave propagation problems as a one-way counterpart of the Helmholtz equation. The expression under the square root usually involves a differential operator and a…

Atmospheric and Oceanic Physics · Physics 2025-11-21 Matthias Ehrhardt , Jochen Glück , Pavel Petrov , Stefan Tappe

Full-waveform inversion (FWI) is an advanced technique for reconstructing high-resolution subsurface physical parameters by progressively minimizing the discrepancy between observed and predicted seismic data. However, conventional FWI…

Geophysics · Physics 2025-03-04 Chao Song , Tariq Alkhalifah , Umair Bin Waheed , Silin Wang , Cai Liu

The problem of imaging extended targets (sources or scatterers) is formulated in the framework of compressed sensing with emphasis on subwavelength resolution. The proposed formulation of the problems of inverse source/scattering is…

Optics · Physics 2009-09-15 Albert C. Fannjiang

Full waveform inversion (FWI) is a process in which seismic numerical simulations are fit to observed data by changing the wave velocity model of the medium under investigation. The problem is non-linear, and therefore optimization…

Computational Engineering, Finance, and Science · Computer Science 2017-06-06 Eran Treister , Eldad Haber

Recent years have seen a surge in data-driven surrogates for dynamical systems that can be orders of magnitude faster than numerical solvers. However, many machine learning-based models such as neural operators exhibit spectral bias,…

Machine Learning · Computer Science 2026-05-07 Xuesong Wang , Michael Groom , Rafael Oliveira , He Zhao , Terence O'Kane , Edwin V. Bonilla

A novel approach to improving the performances of confocal scanning imaging is proposed. We experimentally demonstrate its feasibility using acoustic waves. It relies on a new way to encode spatial information using the temporal dimension.…

We derive spectral width estimates for traces of tempered solutions of a large class of multiplier equations in $\mathbf{R}^n$. The estimates are uniform for solutions up to a given order. In the process, we find a rather explicit…

Analysis of PDEs · Mathematics 2021-08-03 Mirza Karamehmedović , David Winterrose

We present a novel neural network architecture for the efficient prediction of sound fields in two and three dimensions. The network is designed to automatically satisfy the Helmholtz equation, ensuring that the outputs are physically…

Sound · Computer Science 2025-10-29 Matteo Calafà , Yuanxin Xia , Cheol-Ho Jeong

The inhomogeneous wave equation, triggered by point sources, forms the basis for the most modern computational techniques of seismic inversion. In this work, we propose to transfer the inhomogeneous wave equation into a homogeneous…

Computational Physics · Physics 2022-09-30 Marcos Vinícius Cândido Henriques

This paper is concerned with a nonlinear imaging problem, which aims to reconstruct a locally perturbed, perfectly reflecting, infinite plane from intensity-only (or phaseless) far-field or near-field data. A recursive Newton iteration…

Numerical Analysis · Mathematics 2017-06-06 Bo Zhang , Haiwen Zhang

Partial differential equation (PDE) constrained optimization problems such as seismic full waveform inversion (FWI) frequently arise in the geoscience and related fields. For such problems, many observations are usually gathered by multiple…

Geophysics · Physics 2022-05-04 Kamal Aghazade , Hossein S. Aghamiry , Ali Gholami , Stephane Operto

Neural networks have emerged as a tool for solving differential equations in many branches of engineering and science. But their progress in frequency domain acoustics is limited by the vanishing gradient problem that occurs at higher…

Computational Engineering, Finance, and Science · Computer Science 2024-05-09 D. Veerababu , Prasanta K. Ghosh

We study the time-harmonic scattering by a heterogeneous object covered with a thin layer of randomly distributed sound-soft nanoparticles. The size of the particles, their distance between each other and the layer's thickness are all of…

Analysis of PDEs · Mathematics 2026-01-13 Amandine Boucart , Sonia Fliss , Laure Giovangigli

This paper concerns the inverse scattering problem to reconstruct a locally perturbed periodic surface. Different from scattering problems with quasi-periodic incident fields and periodic surfaces, the scattered fields are no longer…

Numerical Analysis · Mathematics 2024-12-20 Xiaoli Liu , Ruming Zhang

We consider the convected Helmholtz equation modeling linear acoustic propagation at a fixed frequency in a subsonic flow around a scattering object. The flow is supposed to be uniform in the exterior domain far from the object, and…

Numerical Analysis · Mathematics 2014-05-16 Fabien Casenave , Alexandre Ern , Guillaume Sylvand

Precise modeling of extended sources is a central challenge in modern optical engineering, laser physics, and computational lithography. Unlike ideal point sources or completely incoherent thermal radiation sources, real-world light sources…

Optics · Physics 2025-12-09 Rongqi Shang , Donglin Ma

The Helmholtz equation has been used for modelling the sound pressure field under a harmonic load. Computing harmonic sound pressure fields by means of solving Helmholtz equation can quickly become unfeasible if one wants to study many…

Machine Learning · Computer Science 2021-11-10 Klas Pettersson , Andrey Karzhou , Irina Pettersson

Seismic full-waveform inversion (FWI), which uses iterative methods to estimate high-resolution subsurface models from seismograms, is a powerful imaging technique in exploration geophysics. In recent years, the computational cost of FWI…

Geophysics · Physics 2023-11-28 Shihang Feng , Youzuo Lin , Brendt Wohlberg

Nuclear reactor buildings must be designed to withstand the dynamic load induced by strong ground motion earthquakes. For this reason, their structural behavior must be assessed in multiple realistic ground shaking scenarios (e.g., the…

Machine Learning · Computer Science 2026-02-02 Niccolò Perrone , Fanny Lehmann , Hugo Gabrielidis , Stefania Fresca , Filippo Gatti
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