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We calculate the differential scattering rate for thermal neutrinos in a hot and dilute gas of interacting neutrons using linear response theory. The dynamical structure factors for density and spin fluctuations of the strongly interacting…

Nuclear Theory · Physics 2018-08-08 Paulo F. Bedaque , Sanjay Reddy , Srimoyee Sen , Neill C. Warrington

Small-angle scattering (SAS) intensities observed experimentally are often characterized by the presence of successive power-law regimes with various scattering exponents whose values vary from -4 to -1. This usually indicates multiple…

Statistical Mechanics · Physics 2014-01-31 A. Yu. Cherny , E. M. Anitas , V. A. Osipov , A. I. Kuklin

We present a covariant ray tracing algorithm for computing high-resolution neutrino distributions in general relativistic numerical spacetimes with hydrodynamical sources. Our formulation treats the very important effect of elastic…

High Energy Astrophysical Phenomena · Physics 2018-11-21 M. Brett Deaton , Evan O'Connor , Y. L. Zhu , Andy Bohn , Jerred Jesse , Francois Foucart , Matthew D. Duez , G. C. McLaughlin

The inverse problem of statistical mechanics is an unsolved, century-old challenge to learn classical pair potentials directly from experimental scattering data. This problem was extensively investigated in the 20th century but was…

Statistical Mechanics · Physics 2024-12-18 Brennon L. Shanks , Harry W. Sullivan , Michael P. Hoepfner

The differential cross-sections for elastic and inelastic neutrino-deuteron scattering are calculated analytically using nucleon-nucleon effective field theory. For elastic scattering, the deuteron axial form factor and the deuteron strange…

Nuclear Theory · Physics 2009-10-31 Malcolm Butler , Jiunn-Wei 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…

Distance-dependent phase shifts, amplitude functions, and radial wave functions for neutron-alpha elastic scattering are studied using the Variable Phase Approach. The microscopic KKNN potential is employed to calculate scattering…

Nuclear Theory · Physics 2025-12-16 Anil Khachi

Physicists routinely need probabilistic models for a number of tasks such as parameter inference or the generation of new realizations of a field. Establishing such models for highly non-Gaussian fields is a challenge, especially when the…

Data Analysis, Statistics and Probability · Physics 2024-10-07 Sihao Cheng , Rudy Morel , Erwan Allys , Brice Ménard , Stéphane Mallat

We present a detailed analysis of the time series of time-stamped neutron counts obtained by single-neutron interferometry. The neutron counting statistics display the usual Poissonian behavior, but the variance of the neutron counts does…

Quantum Physics · Physics 2021-04-05 M. Willsch , D. Willsch , K. Michielsen , F. Jin , T. Denkmayr , S. Sponar , Y. Hasegawa , H. De Raedt

Elastic wave propagation is studied in a heterogeneous 2-D medium consisting of an elastic matrix containing randomly distributed circular elastic inclusions. The aim of this study is to determine the effective wavenumbers when the incident…

Classical Physics · Physics 2016-06-29 Mathieu Chekroun , Loïc Le Marrec , Bruno Lombard , Joël Piraux

This is the first of a series of articles showing how 4 dimensionally covariant analytical procedures developed in the context of General Relativity can be usefully adapted for application in a purely Newtonian framework where they provide…

Astrophysics · Physics 2009-11-07 Brandon Carter , Nicolas Chamel

Understanding nuclear effects is essential for improving the sensitivity of neutrino oscillation measurements. Validating nuclear models solely through neutrino scattering data is challenging due to limited statistics and the broad energy…

High Energy Physics - Phenomenology · Physics 2025-02-25 Seisho Abe

Parameter estimation with non-Gaussian stochastic fields is a common challenge in astrophysics and cosmology. In this paper, we advocate performing this task using the scattering transform, a statistical tool sharing ideas with…

Cosmology and Nongalactic Astrophysics · Physics 2024-10-07 Sihao Cheng , Yuan-Sen Ting , Brice Ménard , Joan Bruna

Circular data arise in many areas of application. Recently, there has been interest in looking at circular data collected separately over time and over space. Here, we extend some of this work to the spatio-temporal setting, introducing…

Methodology · Statistics 2017-04-18 Gianluca Mastrantonio , Giovanna Jona Lasinio , Alan E. Gelfand

We develop a new computational tool and framework for characterizing the scattering of photons by energy-nonconserving Hamiltonians into unidirectional (chiral) waveguides, for example, with coherent pulsed excitation. The temporal…

Quantum Physics · Physics 2018-05-30 Kevin A. Fischer , Rahul Trivedi , Vinay Ramasesh , Irfan Siddiqi , Jelena Vučković

It is generally known that counting statistics is not correctly described by a Gaussian approximation. Nevertheless, in neutron scattering, it is common practice to apply this approximation to the counting statistics; also at low counting…

Data Analysis, Statistics and Probability · Physics 2020-06-09 Jakob Lassa , Magnus Egede Bøggild , Per Hedegård , Kim Lefmann

We present the first numerical relativity simulations of the gravitational scattering of two neutron stars. Constraint-satisfying initial data for two equal-mass nonspinning sequences are constructed at fixed energy and various initial…

General Relativity and Quantum Cosmology · Physics 2025-12-03 Joan Fontbuté , Sebastiano Bernuzzi , Piero Rettegno , Simone Albanesi , Wolfgang Tichy

Beginning from the first neutron spin-echo study of the shape fluctuations of microemulsion droplets [J.S. Huang, S.T. Milner, B. Farago, and D. Richter, Phys. Rev. Lett. 59, 2600 (1987)] these experiments are incorrectly interpreted in the…

Soft Condensed Matter · Physics 2007-05-23 V. Lisy , B. Brutovsky

We argue that, in many situations, fits to elastic scattering data that were historically, and frequently still are, considered `good', are not justifiably so describable. Information about the dynamics of nucleon-nucleus and…

Nuclear Theory · Physics 2017-04-12 R. S. Mackintosh

Machine learning has emerged as a powerful tool in materials discovery, enabling the rapid design of novel materials with tailored properties for countless applications, including in the context of energy and sustainability. To ensure the…