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This study concentrates on advancing mathematical and computational methodology for radar tomography imaging in which the unknown volumetric velocity distribution of a wave within a bounded domain is to be reconstructed. Our goal is to…

Instrumentation and Methods for Astrophysics · Physics 2018-04-04 Mika Takala , Defne Us , Sampsa Pursiainen

An algorithm for determining crystal structures from diffraction data is described which does not rely on the usual Fourier-space formulations of atomicity. The new algorithm implements atomicity constraints in real-space, as well as…

Condensed Matter · Physics 2007-05-23 Veit Elser

We study an inverse random obstacle scattering problems in $\mathbb{R}^2$ where the scatterer is formulated by a Gaussian process defined on the angular parameter domain. Equipped with a modified covariance function which is mathematically…

Numerical Analysis · Mathematics 2026-02-02 Zhiqi Sun , Xiang Xu , Yiwen Lin

Modern technology for producing extremely bright and coherent X-ray laser pulses provides the possibility to acquire a large number of diffraction patterns from individual biological nanoparticles, including proteins, viruses, and DNA.…

Methodology · Statistics 2018-07-11 Stefan Engblom , Carl Nettelblad , Jing Liu

Imaging changes in molecular geometries on their natural femtosecond timescale with sub-Angstrom spatial precision is one of the critical challenges in the chemical sciences, since the nuclear geometry changes determine the molecular…

Tailoring the functional properties of advanced organic/inorganic heterogeonous devices to their intended technological applications requires knowledge and control of the microscopic structure inside the device. Atomistic quantum mechanical…

Materials Science · Physics 2019-03-13 Milica Todorović , Michael U. Gutmann , Jukka Corander , Patrick Rinke

Inline holographic imaging presents an ill-posed inverse problem of reconstructing objects' complex amplitude from recorded diffraction patterns. Although recent deep learning approaches have shown promise over classical phase retrieval…

Optics · Physics 2025-07-02 Chanseok Lee , Fakhriyya Mammadova , Jiseong Barg , Mooseok Jang

We address the problem of signal reconstruction from intensity measurements with respect to a measurement frame. This non-convex inverse problem is known as phase retrieval. The case considered in this paper concerns phaseless measurements…

Functional Analysis · Mathematics 2019-02-13 Goetz E. Pfander , Palina Salanevich

The non-uniform surface temperature distribution of rotating active stars is routinely mapped with the Doppler Imaging technique. Inhomogeneities in the surface produce features in high-resolution spectroscopic observations that shift in…

Instrumentation and Methods for Astrophysics · Physics 2022-02-23 A. Asensio Ramos , C. Diaz Baso , O. Kochukhov

We discuss the implementation of Bayesian inversion methods in order to recover the properties of the intergalactic medium from observations of the neutral hydrogen Lyman-$\alpha$ absorptions observed in the spectra of high redshift quasars…

Astrophysics · Physics 2009-11-06 C. Pichon , J. L. Vergely , E. Rollinde , S. Colombi , P. Petitjean

The forward problems of pattern formation have been greatly empowered by extensive theoretical studies and simulations, however, the inverse problem is less well understood. It remains unclear how accurately one can use images of pattern…

Computational Physics · Physics 2021-04-07 Hongbo Zhao , Richard D. Braatz , Martin Z. Bazant

Quantitative morphologies, such as asymmetry and concentration, have long been used as an effective way to assess the distribution of galaxy starlight in large samples. Application of such quantitative indicators to other data products…

Diffusion models have demonstrated their utility as learned priors for solving various inverse problems. However, most existing approaches are limited to linear inverse problems. This paper exploits the efficient and unsupervised posterior…

Image and Video Processing · Electrical Eng. & Systems 2025-01-07 Mehmet Onurcan Kaya , Figen S. Oktem

We present Wideband Back-Projection Diffusion, an end-to-end probabilistic framework for approximating the posterior distribution induced by the inverse scattering map from wideband scattering data. This framework produces highly accurate…

Machine Learning · Computer Science 2025-05-20 Borong Zhang , Martín Guerra , Qin Li , Leonardo Zepeda-Núñez

This investigation is concerned with the 2D acoustic scattering problem of a plane wave propagating in a non-lossy fluid host and soliciting a linear, isotropic, macroscopically-homogeneous, lossy, flat-plane layer in which the mass density…

Applied Physics · Physics 2019-05-01 Armand Wirgin

Atmospheric aerosols have a major influence on the earths climate and public health. Hence, studying their properties and recovering them from light scattering measurements is of great importance. State of the art retrieval methods such as…

Atmospheric and Oceanic Physics · Physics 2021-11-16 Romana Boiger , Rob L. Modini , Alireza Moallemi , David Degen , Martin Gysel-Beer , Andreas Adelmann

We apply a linear Bayesian model to seismic tomography, a high-dimensional inverse problem in geophysics. The objective is to estimate the three-dimensional structure of the earth's interior from data measured at its surface. Since this…

Applications · Statistics 2013-12-11 Ran Zhang , Claudia Czado , Karin Sigloch

In this paper we consider the inverse problem of vibro-acoustography, a technique for enhancing ultrasound imaging by making use of nonlinear effects. It amounts to determining two spatially variable coefficients in a system of PDEs…

Numerical Analysis · Mathematics 2023-03-31 Barbara Kaltenbacher ans teresa Rauscher

X-ray Bragg coherent diffraction imaging has been demonstrated as a powerful three-dimensional (3D) microscopy approach for the investigation of sub-micrometer-scale crystalline particles. It is based on the measurement of a series of…

Based on a novel dynamic Whittle likelihood approximation for locally stationary processes, a Bayesian nonparametric approach to estimating the time-varying spectral density is proposed. This dynamic frequency-domain based likelihood…

Methodology · Statistics 2023-03-22 Yifu Tang , Claudia Kirch , Jeong Eun Lee , Renate Meyer