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We demonstrate a neutron tomography technique with sub-micrometer spatial resolution. Our method consists of measuring neutron diffraction spectra using a double crystal diffractometer as a function of sample rotation and then using a phase…

Instrumentation and Detectors · Physics 2020-11-13 B. Heacock , D. Sarenac , D. G. Cory , M. G. Huber , J. P. W. MacLean , H. Miao , H. Wen , D. A. Pushin

Total variation (TV) regularization is a popular reconstruction method for ill-posed imaging problems, and particularly useful for applications with piecewise constant targets. However, using TV for medical cone-beam computed X-ray…

Medical Physics · Physics 2024-12-11 Alexander Meaney , Mikael A. K. Brix , Miika T. Nieminen , Samuli Siltanen

In this paper we construct and theoretically analyse group equivariant convolutional kernel networks (CKNs) which are useful in understanding the geometry of (equivariant) CNNs through the lens of reproducing kernel Hilbert spaces (RKHSs).…

Machine Learning · Computer Science 2024-08-09 Soutrik Roy Chowdhury

We study the recovery of a spatially dependent source in a one-dimensional space-time fractional wave equation using boundary measurement data collected at a single endpoint. The main challenge arises from the fact that the eigenfunctions…

Analysis of PDEs · Mathematics 2025-09-05 Kuang Huang , Zhiyuan Li , Zhidong Zhang , Zhi Zhou

We consider the small-angle multiple neutron scattering and a possibility of its model-free analysis by the inverse problem method. We show that the ill-defined problem is essentially regularized by use of a planar detector without a…

Materials Science · Physics 2007-05-23 D. N. Aristov

In the paper, we study the convergence analysis of Tikhonov regularization in finding a zero of a maximal monotone operator using the notion of R-continuity. Applications to convex minimization and DC programming are provided.

Optimization and Control · Mathematics 2023-11-23 Ba Khiet Le

Flash X-ray computed tomography (CT) is an important imaging modality for characterization of high-speed dynamic events, such as Kolsky bar impact experiments for the study of mechanical properties of materials subjected to impulsive…

Image and Video Processing · Electrical Eng. & Systems 2024-06-27 Maliha Hossain , Charles A. Bouman , Brendt Wohlberg

Convolutional neural networks (CNNs) can model complicated non-linear relations between images. However, they are notoriously sensitive to small changes in the input. Most CNNs trained to describe image-to-image mappings generate temporally…

Computer Vision and Pattern Recognition · Computer Science 2020-04-15 Gabriel Eilertsen , Rafał K. Mantiuk , Jonas Unger

The coherent elastic scattering of neutrinos on nuclei, also known as CEvNS, has been studied for several years by the COHERENT program of experiments using neutrinos from stopped-pion decays produced at the Spallation Neutron Source (SNS).…

Measurements of a well-characterised standard sample can verify the performance of an instrument. Typically, small-angle neutron scattering instruments are used to investigate a wide range of samples and may often be used in a number of…

We construct (modified) scattering operators for the Vlasov-Poisson system in three dimensions, mapping small asymptotic dynamics as $t\to -\infty$ to asymptotic dynamics as $t\to +\infty$. The main novelty is the construction of modified…

Analysis of PDEs · Mathematics 2021-01-06 Patrick Flynn , Zhimeng Ouyang , Benoit Pausader , Klaus Widmayer

We consider a statistical inverse learning problem, where the task is to estimate a function $f$ based on noisy point evaluations of $Af$, where $A$ is a linear operator. The function $Af$ is evaluated at i.i.d. random design points $u_n$,…

Machine Learning · Statistics 2021-11-02 Tatiana A. Bubba , Martin Burger , Tapio Helin , Luca Ratti

Many applications in science and engineering require the solution of large linear discrete ill-posed problems that are obtained by the discretization of a Fredholm integral equation of the first kind in several space-dimensions. The matrix…

Numerical Analysis · Mathematics 2017-05-19 Laura Dykes , Guangxin Huang , Silvia Noschese , Lothar Reichel

Conditional stability estimates allow us to characterize the degree of ill-posedness of many inverse problems, but without further assumptions they are not sufficient for the stable solution in the presence of data perturbations. We here…

Numerical Analysis · Mathematics 2018-10-17 Herbert Egger , Bernd Hofmann

We study kernel least-squares estimation under a norm constraint. This form of regularisation is known as Ivanov regularisation and it provides better control of the norm of the estimator than the well-established Tikhonov regularisation.…

Statistics Theory · Mathematics 2019-06-17 Stephen Page , Steffen Grünewälder

The technique of polarized neutron scattering is reviewed with emphasis on applications. Many examples of the usefulness of the method in various fields of physics are given like the determination of spin density maps, measurement of…

Strongly Correlated Electrons · Physics 2007-05-23 B. Roessli , P. Böni

The present paper is focused on the problem of recovering the Radon-Nikodym derivative under the big data assumption. To address the above problem, we design an algorithm that is a combination of the Nystr\"om subsampling and the standard…

Numerical Analysis · Mathematics 2025-11-13 Hanna Myleiko , Sergei Solodky

Calculations of neutral-current neutrino-nucleus scattering cross sections are important for interpreting low- and intermediate-energy neutrino data, where terrestrial measurements remain limited. The first observation of coherent elastic…

High Energy Physics - Phenomenology · Physics 2026-05-18 Muhammad Farooq , Shakeel Mahmood , Muhammad Faisal Khan

We study reconstruction of an unknown function from its $d$-plane Radon transform on the flat $n$-torus when $1 \leq d \leq n-1$. We prove new reconstruction formulas and stability results with respect to weighted Bessel potential norms. We…

Functional Analysis · Mathematics 2020-10-23 Jesse Railo

Variable projection methods prove highly efficient in solving separable nonlinear least squares problems by transforming them into a reduced nonlinear least squares problem, typically solvable via the Gauss-Newton method. When solving…

Numerical Analysis · Mathematics 2024-02-14 Malena I. Español , Gabriela Jeronimo