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Theoretical predictions for elastic neutrino-electron scattering have no hadronic or nuclear uncertainties at leading order making this process an important tool for normalizing neutrino flux. However, the process is subject to large…

High Energy Physics - Phenomenology · Physics 2020-02-26 Oleksandr Tomalak , Richard J Hill

We revisit the method of cumulants for analysing dynamic light scattering data in particle sizing applications. Here the data, in the form of the time correlation function of scattered light, is written as a series involving the first few…

Soft Condensed Matter · Physics 2015-04-27 Alastair G. Mailer , Paul S. Clegg , Peter N. Pusey

This study outlines a numerical methodology aimed at rectifying the neutron scattering cross-sections of fundamental elements across a range of low neutron energies typically employed in general neutron scattering experiments. By using the…

Data Analysis, Statistics and Probability · Physics 2023-09-28 Karrie E. An , Guan-Rong Huang , Changwoo Do , Wei-Ren Chen

Single crystal inelastic neutron scattering data contain rich information about the structure and dynamics of a material. Yet the challenge of matching sophisticated theoretical models with large data volumes is compounded by computational…

Neutron and X-ray scattering represent two state-of-the-art materials characterization techniques that measure materials' structural and dynamical properties with high precision. These techniques play critical roles in understanding a wide…

Nucleon-deuteron ($Nd$) scattering can be used to constrain three-nucleon forces in chiral effective field theory ($\chi$EFT). However, high-fidelity calculations, such as the Hyperspherical Harmonic (HH) method, are computationally…

As a simple cubic system with only one f electron per cerium ion, CeB6 is of model character to investigate the interplay of orbital phenomena with magnetism. It is also a textbook example of a compound that exhibits magnetically hidden…

Strongly Correlated Electrons · Physics 2021-08-13 P. Y. Portnichenko , A. S. Cameron , D. S. Inosov

Converting neutron scattering data to real-space time-dependent structures can only be achieved through suitable models, which is particularly challenging for geometrically disordered structures. We address this problem by introducing…

Chemical Physics · Physics 2021-07-28 Cedric J. Gommes , Reiner Zorn , Sebastian Jaksch , Henrich Frielinghaus , Olaf Holderer

Quantum materials research requires co-design of theory with experiments and involves demanding simulations and the analysis of vast quantities of data, usually including pattern recognition and clustering. Artificial intelligence is a…

Other Condensed Matter · Physics 2021-11-01 A. M. Samarakoon , D. Alan Tennant , Feng Ye , Qiang Zhang , S. A. Grigera

Currently, an excessive amount of event data is being obtained in four-dimensional inelastic neutron-scattering experiments. A method for automatic bin-width optimization of multidimensional histograms has been developed and recently…

Data Analysis, Statistics and Probability · Physics 2026-03-19 Kensuke Muto , Hirotaka Sakamoto , Kenji Nagata , Taka-hisa Arima , Masato Okada

Neutron scattering is a powerful probe of strongly correlated systems. It can directly detect common phenomena such as magnetic order, and can be used to determine the coupling between magnetic moments through measurements of the spin-wave…

Strongly Correlated Electrons · Physics 2014-10-02 Igor A. Zaliznyak , John M. Tranquada

A discrete-event simulation approach which provides a cause-and-effect description of many experiments with photons and neutrons exhibiting interference and entanglement is applied to a recent single-neutron experiment that tests…

Quantum Physics · Physics 2014-03-19 Hans De Raedt , Kristel Michielsen

In this work we present the development of small angle scattering components in McStas that describe the neutron interaction with 70 different form and structure factors. We describe the considerations taken into account for the generation…

Instrumentation and Detectors · Physics 2025-01-13 Jose Robledo , Klaus Lieutenant , Peter Willendrup

Machine learning promises to deliver powerful new approaches to neutron scattering from magnetic materials. Large scale simulations provide the means to realise this with approaches including spin-wave, Landau Lifshitz, and Monte Carlo…

Computational Physics · Physics 2020-11-12 Anjana M. Samarakoon , D. Alan Tennant

Precision tests of the standard model are essential for constraining models of new physics. Neutrino-electron elastic scattering offers a clean probe into many electroweak effects that are complimentary to the more canonical measurements…

High Energy Physics - Phenomenology · Physics 2008-11-26 Andre de Gouvea , James Jenkins

A discrete-event approach, which has already been shown to give a cause-and-effect explanation of many quantum optics experiments, is applied to single-neutron interferometry experiments. The simulation algorithm yields a logically…

Quantum Physics · Physics 2015-06-11 Hans De Raedt , Fengping Jin , Kristel Michielsen

We review exact formalisms for describing the dynamics of liquids in terms of static parameters. We discuss how these formalisms are prone to suffer from imposing restrictions that appear to adhere to common sense but which are overly…

Statistical Mechanics · Physics 2024-06-19 Wouter Montfrooij , Ubaldo Bafile , Eleonora Guarini

Electron scattering on liquid samples has been enabled recently by the development of ultrathin liquid sheet technologies. The data treatment of liquid-phase electron scattering has been mostly reliant on methodologies developed for gas…

We introduce a data analysis procedure for color transparency experiments which is considerably less model dependent than the transparency ratio method. The new method is based on fitting the shape of the A dependence of the nuclear cross…

High Energy Physics - Phenomenology · Physics 2008-11-26 Pankaj Jain , John P. Ralston

Statistical modeling of physical laws connects experiments with mathematical descriptions of natural phenomena. The modeling is based on the probability density of measured variables expressed by experimental data via a kernel estimator. As…

Information Theory · Computer Science 2007-07-13 Igor Grabec