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The behaviour is investigated of solutions to a diffusion equation on the real line with nonlocal and singular reaction term, i.e., given by a Dirac source or sink at the origin. It gives a simplified representation of for example a control…

Analysis of PDEs · Mathematics 2026-05-19 Xiao Yang , Qiyao Peng , Sander C. Hille

We propose a novel indicator function for reconstructing acoustic sources from multi-frequency near-field measurements. The theoretical basis is established by a formula relating the scattered field to the source function through the Radon…

Mathematical Physics · Physics 2026-03-12 Xiaodong Liu , Jing Wang

Langevin diffusion (LD) is one of the main workhorses for sampling problems. However, its convergence rate can be significantly reduced if the target distribution is a mixture of multiple densities, especially when each component…

Probability · Mathematics 2020-07-14 Jing Dong , Xin T. Tong

We investigate the inverse source problem for the wave equation, arising in photo- and thermoacoustic tomography. There exist quite a few theoretically exact inversion formulas explicitly expressing solution of this problem in terms of the…

Analysis of PDEs · Mathematics 2018-08-01 Ngoc Do , Leonid Kunyansky

Physics-guided sampling with diffusion model priors has shown promise for solving partial differential equation (PDE) governed problems, but applications to chemically meaningful reaction-transport systems remain limited. We apply…

Chemical Physics · Physics 2026-03-06 Andrew Millard , Henrik Pedersen

We consider the problem of identifying a sparse initial source condition to achieve a given state distribution of a diffusion-advection partial differential equation after a given final time. The initial condition is assumed to be a finite…

Optimization and Control · Mathematics 2023-08-09 Umberto Biccari , Yongcun Song , Xiaoming Yuan , Enrique Zuazua

Diffusion models have become emerging generative models. Their sampling process involves multiple steps, and in each step the models predict the noise from a noisy sample. When the models make prediction, the output deviates from the ground…

Machine Learning · Computer Science 2025-10-28 Shifeng Xu , Yanzhu Liu , Adams Wai-Kin Kong

We establish a complete Widder Theory for the fractional fast diffusion equation. Our work focuses on nonnegative solutions satisfying a certain integral size condition at infinity. We prove that these solutions possess a Radon measure as…

Analysis of PDEs · Mathematics 2025-05-20 Jorge Ruiz-Cases

The background caused by radon and its daughters is an important background in the low background liquid scintillator (LS) detectors. The study of the diffusion behaviour of radon in the LS contributes to the analysis of the related…

Instrumentation and Detectors · Physics 2023-04-19 Z. F. Xu , C. Guo , J. C. Liu , Y. P. Zhang , P. Zhang , C. G. Yang , Q. Tang , Y. Liu , C. Li , T. Y. Guan

In this paper, we propose a data-driven leak localization method for water distribution networks (WDNs) which combines two complementary approaches: graph-based interpolation and dictionary classification. The former estimates the complete…

Machine Learning · Computer Science 2021-10-14 Paul Irofti , Luis Romero-Ben , Florin Stoican , Vicenç Puig

The paper presents an approach to olfactory search for a diffusive emitting source of tracer (e.g. aerosol, gas) in an environment with unknown map of randomly placed and shaped obstacles. The measurements of tracer concentration are…

Artificial Intelligence · Computer Science 2015-06-16 Branko Ristic , Alex Skvortsov , Andrew Walker

In this paper, we consider a novel and robust maximum likelihood approach to localizing radiation sources with unknown statistics of the source signal strength. The result utilizes the smallest number of sensors required theoretically to…

Optimization and Control · Mathematics 2016-10-11 Henry E. Baidoo-Williams

Inverse design problems are common in engineering and materials science. The forward direction, i.e., computing output quantities from design parameters, typically requires running a numerical simulation, such as a FEM, as an intermediate…

Machine Learning · Computer Science 2026-02-18 Jens U. Kreber , Christian Weißenfels , Joerg Stueckler

We present recent finite element numerical results on a model convection-diffusion problem in the singular perturbed case when the convection term dominates the problem. We compare the standard Galerkin discretization using the linear…

Numerical Analysis · Mathematics 2023-02-16 Constantin Bacuta , Daniel Hayes , Tyler O'Grady

Exciton diffusion length plays a vital role in the function of opto-electronic devices. Oftentimes, the domain occupied by an organic semiconductor is subject to surface measurement error. In many experiments, photoluminescence over the…

Numerical Analysis · Mathematics 2017-12-15 Jingrun Chen , Ling Lin , Zhiwen Zhang , Xiang Zhou

In this article we consider the numerical approximation of the convection-diffusion-reaction equation. One of the main challenges of designing a numerical method for this problem is that boundary layers occurring in the convection-dominated…

Numerical Analysis · Mathematics 2022-02-09 Paul Houston , Sarah Roggendorf , Kristoffer G. van der Zee

Convection-diffusion equations provide the basis for describing heat and mass transfer phenomena as well as processes of continuum mechanics. To handle flows in porous media, the fundamental issue is to model correctly the convective…

Numerical Analysis · Computer Science 2012-08-29 A. Churbanov , P. Vabishchevich

We investigate the problem of optimal transport in the so-called Beckmann form, i.e. given two Radon measures on a compact set, we seek an optimal flow field which is a vector valued Radon measure on the same set that describes a flow…

Optimization and Control · Mathematics 2022-01-19 Dirk Lorenz , Hinrich Mahler , Christian Meyer

Inverse source problems are central to many applications in acoustics, geophysics, non-destructive testing, and more. Traditional imaging methods suffer from the resolution limit, preventing distinction of sources separated by less than the…

Machine Learning · Computer Science 2022-08-11 Adar Kahana , Symeon Papadimitropoulos , Eli Turkel , Dmitry Batenkov

We study zero-shot conditional sampling with pretrained diffusion models for linear inverse problems, including inpainting and super-resolution. In these problems, the observation determines only part of the unknown signal. The remaining…

Machine Learning · Computer Science 2026-05-08 Ahmad Aghapour , Erhan Bayraktar , Asaf Cohen
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