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A thorough understanding of the issues surrounding the determination of parton distributions is crucial due to their importance to calculations of LHC observables. However, it is still not fully understood how much of an impact…

High Energy Physics - Phenomenology · Physics 2014-09-16 Christopher S. Deans

PySEMTools is a Python-based library for post-processing simulation data produced with high-order hexahedral elements in the context of the spectral element method in computational fluid dynamics. It aims to minimize intermediate steps…

Computational Physics · Physics 2025-04-18 Adalberto Perez , Siavash Toosi , Tim Felle Olsen , Stefano Markidis , Philipp Schlatter

Inversions of airborne EM data are often an iterative process, not only requiring that the researcher be able to explore the impact of changing components such as the choice of regularization functional or model parameterization, but also…

Geophysics · Physics 2022-03-29 Lindsey J. Heagy , Seogi Kang , Rowan Cockett , Douglas Oldenburg

Dynamic program analysis (also known as profiling) is well-known for its powerful capabilities of identifying performance inefficiencies in software packages. Although a large number of dynamic program analysis techniques are developed in…

Software Engineering · Computer Science 2023-12-29 Qidong Zhao , Milind Chabbi , Xu Liu

We present X-sifter, a software package designed for near-optimal detection of sources in X-ray images and other forms of photon images in the Poisson-noise regime. The code is based on the Poisson-noise-matched filter (Ofek & Zackay),…

Instrumentation and Methods for Astrophysics · Physics 2024-12-12 Maayane T. Soumagnac , Eran O. Ofek , Shachar S. Israeli , Guy Nir , Imri A. Dickstein

We consider big spatial data, which is typically produced in scientific areas such as geological or seismic interpretation. The spatial data can be produced by observation (e.g. using sensors or soil instrument) or numerical simulation…

Distributed, Parallel, and Cluster Computing · Computer Science 2018-05-09 Ji Liu , Noel Moreno Lemus , Esther Pacitti , Fabio Porto , Patrick Valduriez

Diffusion Models are probabilistic models that create realistic samples by simulating the diffusion process, gradually adding and removing noise from data. These models have gained popularity in domains such as image processing, speech…

Computer Vision and Pattern Recognition · Computer Science 2024-08-21 Md Manjurul Ahsan , Shivakumar Raman , Yingtao Liu , Zahed Siddique

The pair-angle distribution function (PADF) is a three- and four-atom correlation function that can characterise the local angular structure of disordered materials, particles or nanocrystalline materials. The PADF can be measured by x-ray…

Disordered Systems and Neural Networks · Physics 2023-09-04 Andrew V. Martin , Patrick Adams , Jack Binns

The spherically averaged structure function $\soq$ obtained from pulsed neutron powder diffraction contains both elastic and inelastic scattering via an integral over energy. The Fourier transformation of $\soq$ to real space, as is done in…

Materials Science · Physics 2016-08-31 D. A. Dimitrov , D. Louca , H. Röder

Research in ultrasound imaging is limited in reproducibility by two factors: First, many existing ultrasound pipelines are protected by intellectual property, rendering exchange of code difficult. Second, most pipelines are implemented in…

Computer Vision and Pattern Recognition · Computer Science 2018-05-11 Rüdiger Göbl , Nassir Navab , Christoph Hennersperger

As the LHC begins Run 2 at an even higher energy, one of the top priorities will be to search for new particles (possibly from SUSY) at the highest energy scales. In addition to direct production of new particles, they can mix with Standard…

High Energy Physics - Phenomenology · Physics 2015-10-21 Eric Godat

xFitter is an open-source package that provides a framework for the determination of the parton distribution functions (PDFs) of the proton for many different kinds of analyses in Quantum Chromodynamics (QCD). It incorporates experimental…

Phase transitions of solids and structural transformations of molecules are canonical examples of important photo-induced processes, whose underlying mechanisms largely elude our comprehension due to our inability to correlate electronic…

We present X-MDPT ($\underline{Cross}$-view $\underline{M}$asked $\underline{D}$iffusion $\underline{P}$rediction $\underline{T}$ransformers), a novel diffusion model designed for pose-guided human image generation. X-MDPT distinguishes…

Computer Vision and Pattern Recognition · Computer Science 2024-06-04 Trung X. Pham , Zhang Kang , Chang D. Yoo

We discuss a Bayesian methodology for the solution of the inverse problem underlying the determination of parton distribution functions (PDFs). In our approach, Gaussian Processes (GPs) are used to model the PDF prior, while Bayes theorem…

High Energy Physics - Phenomenology · Physics 2024-07-03 Alessandro Candido , Luigi Del Debbio , Tommaso Giani , Giacomo Petrillo

Probability density function (PDF) methods are a promising alternative to predicting the transport of solutes in groundwater under uncertainty. They make it possible to derive the evolution equations of the mean concentration and the…

Fluid Dynamics · Physics 2016-03-15 Lennart Schüler , Nicolae Suciu , Peter Knabner , Sabine Attinger

Image fusion is a fundamental and important task in computer vision, aiming to combine complementary information from different modalities to fuse images. In recent years, diffusion models have made significant developments in the field of…

Computer Vision and Pattern Recognition · Computer Science 2025-09-25 Zirui Wang , Jiayi Zhang , Tianwei Guan , Yuhan Zhou , Xingyuan Li , Minjing Dong , Jinyuan Liu

To characterise (inter)diffusion in materials, concentration profiles can be measured by EDX. It allows one to determine the chemical composition with a very good accuracy if measurement artefacts are accounted for. Standard phenomena (such…

Classical Physics · Physics 2007-12-24 Olivier Arnould , François Hild

Determining crystal structures from X-ray diffraction data is fundamental across diverse scientific fields, yet remains a significant challenge when data is limited to low resolution. While recent deep learning models have made…

Materials Science · Physics 2025-10-22 Jiale Zhao , Cong Liu , Yuxuan Zhang , Chengyue Gong , Zhenyi Zhang , Shifeng Jin , Zhenyu Liu

Random processes play a crucial role in scientific research, often characterized by distribution functions or probability density functions (PDFs). These PDFs serve as essential approximations of the actual and frequently undisclosed…

Methodology · Statistics 2023-06-06 Nico Schick
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