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Simulating a Gaussian process requires sampling from a high-dimensional Gaussian distribution, which scales cubically with the number of sample locations. Spectral methods address this challenge by exploiting the Fourier representation,…

Machine Learning · Statistics 2026-02-27 Arsalan Jawaid , Abdullah Karatas , Jörg Seewig

We report on a new algorithm for detection of crystallographic information in 3D, as retained in Atom Probe Tomography (APT), with improved robustness and signal detection performance. The algorithm is underpinned by 1D distribution…

Materials Science · Physics 2019-05-22 Daniel Haley , Paul A. J. Bagot , Michael P. Moody

Stable or metastable crystal structures of assembled atoms can be predicted by finding the global or local minima of the energy surface within a broad space of atomic configurations. Generally, this requires repeated first-principles energy…

The reader is informed about a method for the objective identification of the plane symmetry group of a "noisy" crystal pattern. Without giving numerical details, this information theory based method is applied to two beautiful pieces of…

Computational Physics · Physics 2023-05-03 Peter Moeck

Ladder polymers, known for their rigid, ladder-like structures, exhibit exceptional thermal stability and mechanical strength, positioning them as candidates for advanced applications. However, accurately determining their structure from…

Soft Condensed Matter · Physics 2025-05-23 Lijie Ding , Chi-Huan Tung , Zhiqiang Cao , Zekun Ye , Xiaodan Gu , Yan Xia , Wei-Ren Chen , Changwoo Do

Motivated by applications to acoustic imaging, the present work establishes a framework to analyze scattering for the one-dimensional wave, Helmholtz, Schr\"odinger and Riccati equations that allows for coefficients which are more singular…

Analysis of PDEs · Mathematics 2022-02-28 Peter C. Gibson

Spectra of parametric X-ray radiation (PXR) are considered in the range of anomalous dispersion for one of the atoms in a crystal elementary cell. The PXR spectra are calculated both for the ultra-relativistic and non-relativistic electrons…

Materials Science · Physics 2007-05-23 I. D. Feranchuk , A. P. Ulyanenkov

Stochastic parametrisations are used in weather and climate models to improve the representation of unpredictable unresolved processes. When compared to a deterministic model, a stochastic model represents `model uncertainty', i.e., sources…

Atmospheric and Oceanic Physics · Physics 2020-04-22 Hannah M. Christensen

Procedural material models have been gaining traction in many applications thanks to their flexibility, compactness, and easy editability. We explore the inverse rendering problem of procedural material parameter estimation from…

Graphics · Computer Science 2025-04-22 Yu Guo , Milos Hasan , Lingqi Yan , Shuang Zhao

Program behavior may depend on parameters, which are either configured before compilation time, or provided at run-time, e.g., by sensors or other input devices. Parametric program analysis explores how different parameter settings may…

Programming Languages · Computer Science 2014-06-23 Thomas M. Gawlitza , Martin D. Schwarz , Helmut Seidl

Crystal Structure Prediction (CSP) aims to discover solid crystalline materials by optimizing periodic arrangements of atoms, ions or molecules. CSP takes weeks of supercomputer time because of slow energy minimizations for millions of…

Materials Science · Physics 2021-08-17 Jakob Ropers , Marco M Mosca , Olga Anosova , Vitaliy Kurlin , Andrew I Cooper

Established x-ray diffraction methods allow for high-resolution structure determination of crystals, crystallized protein structures or even single molecules. While these techniques rely on coherent scattering, incoherent processes like…

Three-dimensional phase contrast imaging of multiply-scattering samples in X-ray and electron microscopy is extremely challenging, due to small numerical apertures, the unavailability of wavefront shaping optics, and the highly nonlinear…

Computational Physics · Physics 2021-06-02 Philipp M Pelz , Hamish G Brown , Jim Ciston , Scott D Findlay , Yaqian Zhang , Mary Scott , Colin Ophus

We present a novel Bayesian inference tool that uses a neural network to parameterise efficient Markov Chain Monte-Carlo (MCMC) proposals. The target distribution is first transformed into a diagonal, unit variance Gaussian by a series of…

Cosmology and Nongalactic Astrophysics · Physics 2020-06-03 Adam Moss

A new approach to the design of graded Photonic Crystals (GPCs) devices is proposed by exploiting the inverse scattering framework as a synthesis tool. The introduced general methodology can be applied to arbitrary far-field specifications,…

Persistent scatterer interferometry and Synthetic Aperture Radar (SAR) Tomography are powerful tools for the detection and time monitoring of persistent scatterers. They have been proven to be effective in urban scenarios, especially for…

Signal Processing · Electrical Eng. & Systems 2026-02-05 Pia Addabbo , Diego Reale , Antonio Pauciullo , Gianfranco Fornaro , Danilo Orlando

Crystal structure determines properties of materials. With the crystal structure of a chemical substance, many physical and chemical properties can be predicted by first-principles calculations or machine learning models. Since it is…

Materials Science · Physics 2021-09-22 Wenhui Yang , Edirisuriya M. Dilanga Siriwardane , Rongzhi Dong , Yuxin Li , Jianjun Hu

A new method for characterization of periodically poled crystals is developed based on spontaneous parametric down-conversion. The method is demonstrated on crystals of Y:LiNbO3, Mg:Y:LiNbO3 with non-uniform periodically poled structures,…

We present the implementation and use of algorithms for matching point-spread functions (PSFs) within the Pan-STARRS Image Processing Pipeline (IPP). PSF-matching is an essential part of the IPP for the detection of supernovae and…

Instrumentation and Methods for Astrophysics · Physics 2019-01-30 Paul A. Price , Eugene A. Magnier

The problem of estimating parameters of a deterministic jump or piecewise linear model is considered. A subspace technique referred to as spectral clustering on subspace (SCS) algorithm is proposed to estimate a set of linear model…

Methodology · Statistics 2013-07-02 Liang Li , Wei Dong , Yindong Ji , Lang Tong