English
Related papers

Related papers: Probabilistic Analysis of Event-Mode Experimental …

200 papers

Inelastic neutron and X-ray scattering experiments on surfaces and interfaces are a challenging topic in modern physics. Particular interest arises regarding surfaces and interfaces of soft matter and biological systems. We review both…

Biological Physics · Physics 2009-10-02 Maikel C. Rheinstädter , Tilo Seydel , Bela Farago , Tim Salditt

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

The current and upcoming generation of Very Large Volume Neutrino Telescopes---collecting unprecedented quantities of neutrino events---can be used to explore subtle effects in oscillation physics, such as (but not restricted to) the…

Data Analysis, Statistics and Probability · Physics 2019-12-05 IceCube Collaboration , M. G. Aartsen , M. Ackermann , J. Adams , J. A. Aguilar , M. Ahlers , M. Ahrens , I. Al Samarai , D. Altmann , K. Andeen , T. Anderson , I. Ansseau , G. Anton , C. Argüelles , T. C. Arlen , J. Auffenberg , S. Axani , H. Bagherpour , X. Bai , A. Balagopal V. , J. P. Barron , I. Bartos , S. W. Barwick , V. Baum , R. Bay , J. J. Beatty , J. Becker Tjus , K. -H. Becker , S. BenZvi , D. Berley , E. Bernardini , D. Z. Besson , G. Binder , D. Bindig , E. Blaufuss , S. Blot , C. Bohm , M. Bohmer , M. Börner , F. Bos , S. Böser , O. Botner , E. Bourbeau , J. Bourbeau , F. Bradascio , J. Braun , M. Brenzke , H. -P. Bretz , S. Bron , J. Brostean-Kaiser , A. Burgman , R. S. Busse , T. Carver , E. Cheung , D. Chirkin , A. Christov , K. Clark , L. Classen , G. H. Collin , J. M. Conrad , P. Coppin , P. Correa , D. F. Cowen , R. Cross , P. Dave , M. Day , J. P. A. M. de André , C. De Clercq , J. J. DeLaunay , H. Dembinski , S. De Ridder , P. Desiati , K. D. de Vries , G. de Wasseige , M. de With , T. DeYoung , J. C. Díaz-Vélez , V. di Lorenzo , H. Dujmovic , J. P. Dumm , M. Dunkman , M. A. DuVernois , E. Dvorak , B. Eberhardt , T. Ehrhardt , B. Eichmann , P. Eller , R. Engel , J. J. Evans , P. A. Evenson , S. Fahey , A. R. Fazely , J. Felde , K. Filimonov , C. Finley , S. Flis , A. Franckowiak , E. Friedman , A. Fritz , T. K. Gaisser , J. Gallagher , A. Gartner , L. Gerhardt , R. Gernhaeuser , K. Ghorbani , W. Giang , T. Glauch , T. Glüsenkamp , A. Goldschmidt , J. G. Gonzalez , D. Grant , Z. Griffith , C. Haack , A. Hallgren , F. Halzen , K. Hanson , J. Haugen , A. Haungs , D. Hebecker , D. Heereman , K. Helbing , R. Hellauer , F. Henningsen , S. Hickford , J. Hignight , G. C. Hill , K. D. Hoffman , B. Hoffmann , R. Hoffmann , T. Hoinka , B. Hokanson-Fasig , K. Holzapfel , K. Hoshina , F. Huang , M. Huber , T. Huber , T. Huege , K. Hultqvist , M. Hünnefeld , R. Hussain , S. In , N. Iovine , A. Ishihara , E. Jacobi , G. S. Japaridze , M. Jeong , K. Jero , B. J. P. Jones , P. Kalaczynski , O. Kalekin , W. Kang , D. Kang , A. Kappes , D. Kappesser , T. Karg , A. Karle , T. Katori , U. Katz , M. Kauer , A. Keivani , J. L. Kelley , A. Kheirandish , J. Kim , M. Kim , T. Kintscher , J. Kiryluk , T. Kittler , S. R. Klein , R. Koirala , H. Kolanoski , L. Köpke , C. Kopper , S. Kopper , J. P. Koschinsky , D. J. Koskinen , M. Kowalski , C. B. Krauss , K. Krings , M. Kroll , G. Krückl , S. Kunwar , N. Kurahashi , T. Kuwabara , A. Kyriacou , M. Labare , J. L. Lanfranchi , M. J. Larson , F. Lauber , D. Lennarz , K. Leonard , M. Lesiak-Bzdak , A. Leszczynska , M. Leuermann , Q. R. Liu , E. Lohfink , J. LoSecco , C. J. Lozano Mariscal , L. Lu , J. Lünemann , W. Luszczak , J. Madsen , G. Maggi , K. B. M. Mahn , S. Mancina , S. Mandalia , S. Marka , Z. Marka , R. Maruyama , K. Mase , R. Maunu , K. Meagher , M. Medici , M. Meier , T. Menne , G. Merino , T. Meures , S. Miarecki , J. Micallef , G. Momenté , T. Montaruli , R. W. Moore , M. Moulai , R. Nahnhauer , P. Nakarmi , U. Naumann , G. Neer , H. Niederhausen , S. C. Nowicki , D. R. Nygren , A. Obertacke Pollmann , M. Oehler , A. Olivas , A. O'Murchadha , E. O'Sullivan , A. Palazzo , T. Palczewski , H. Pandya , D. V. Pankova , L. Papp , P. Peiffer , J. A. Pepper , C. Pérez de los Heros , T. C. Petersen , D. Pieloth , E. Pinat , J. L. Pinfold , M. Plum , P. B. Price , G. T. Przybylski , C. Raab , L. Rädel , M. Rameez , L. Rauch , K. Rawlins , I. C. Rea , R. Reimann , B. Relethford , M. Relich , M. Renschler , E. Resconi , W. Rhode , M. Richman , M. Riegel , S. Robertson , M. Rongen , C. Rott , T. Ruhe , D. Ryckbosch , D. Rysewyk , I. Safa , T. Sälzer , S. E. Sanchez Herrera , A. Sandrock , J. Sandroos , P. Sandstrom , M. Santander , S. Sarkar , S. Sarkar , K. Satalecka , H. Schieler , P. Schlunder , T. Schmidt , A. Schneider , S. Schoenen , S. Schöneberg , F. G. Schröder , L. Schumacher , S. Sclafani , D. Seckel , S. Seunarine , M. H. Shaevitz , J. Soedingrekso , D. Soldin , S. Söldner-Rembold , M. Song , G. M. Spiczak , C. Spiering , J. Stachurska , M. Stamatikos , T. Stanev , A. Stasik , R. Stein , J. Stettner , A. Steuer , T. Stezelberger , R. G. Stokstad , A. Stößl , N. L. Strotjohann , T. Stuttard , G. W. Sullivan , M. Sutherland , I. Taboada , A. Taketa , H. K. M. Tanaka , J. Tatar , F. Tenholt , S. Ter-Antonyan , A. Terliuk , S. Tilav , P. A. Toale , M. N. Tobin , C. Tönnis , S. Toscano , D. Tosi , M. Tselengidou , C. F. Tung , A. Turcati , C. F. Turley , B. Ty , E. Unger , M. Usner , J. Vandenbroucke , W. Van Driessche , D. van Eijk , N. van Eijndhoven , S. Vanheule , J. van Santen , D. Veberic , E. Vogel , M. Vraeghe , C. Walck , A. Wallace , M. Wallraff , F. D. Wandler , N. Wandkowsky , A. Waza , C. Weaver , A. Weindl , M. J. Weiss , C. Wendt , J. Werthebach , S. Westerhoff , B. J. Whelan , K. Wiebe , C. H. Wiebusch , L. Wille , D. R. Williams , L. Wills , M. Wolf , J. Wood , T. R. Wood , E. Woolsey , K. Woschnagg , G. Wrede , S. Wren , D. L. Xu , X. W. Xu , Y. Xu , J. P. Yanez , G. Yodh , S. Yoshida , T. Yuan

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…

A new method is presented for the analysis of small angle neutron scattering data from quasi-2D systems such as flux lattices, Skyrmion lattices, and aligned liquid crystals. A significant increase in signal to noise ratio, and a natural…

Other Condensed Matter · Physics 2014-07-23 Alexander T. Holmes

Methods of analysis of nucleon-nucleus scattering data have progressed markedly over the past 50 years, yet many analyses of scattering data still use prescriptions specified at various stages of that progress. But the assumptions made or…

Nuclear Theory · Physics 2010-07-05 K. Amos , S. Karataglidis

We present a least squares method for estimating parameters from measurements of event yields in the presence of background and crossfeed. We adopt a unified approach to incorporating the statistical and systematic uncertainties on the…

Data Analysis, Statistics and Probability · Physics 2009-11-11 Werner M. Sun

The main purpose of scattering experiments is to unveil the underlying structure of the colliding particles and their interaction. Typically one measures scattering observables (cross sections and polarizations) at discrete angles and…

Nuclear Theory · Physics 2017-12-01 Enrique Ruiz Arriola , Jose Enrique Amaro , Rodrigo Navarro Perez

Small-angle neutron scattering (SANS) is a powerful technique for probing the nanoscale structure of materials. However, the fundamental limitations of neutron flux pose significant challenges for rapid, high-fidelity data acquisition…

Nucleon-Nucleon potentials are commonplace in nuclear physics and are determined from a finite number of experimental data with limited precision sampling the scattering process. We study the statistical assumptions implicit in the standard…

Nuclear Theory · Physics 2014-07-02 R. Navarro Perez , J. E. Amaro , E. Ruiz Arriola

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

A thorough understanding of neutrino-nucleus interactions physics is crucial to achieving precision goals in broader neutrino physics programs. The complexity of nuclei comprising the detectors and limited understanding of their weak…

High Energy Physics - Experiment · Physics 2023-06-12 V. Pandey

A universal numerical method is developed for the investigation of magnetic neutron scattering. By applying the pseudospectral-time-domain (PSTD) algorithm to the spinor version of the Schr\"odinger equation, the evolution of the spin-state…

Quantum Physics · Physics 2024-12-31 Kun Chen

Small-angle X-ray and neutron scattering are widely used to investigate soft matter and biophysical systems. The experimental errors are essential when assessing how well a hypothesized model fits the data. Likewise, they are important when…

Data Analysis, Statistics and Probability · Physics 2022-04-20 Andreas Haahr Larsen , Martin Cramer Pedersen

Neutron correlation spectroscopy can exceed direct spectroscopy in the incoming beam intensity by up to two orders of magnitude at the same energy resolution. However, the propagation of the counting noise in the correlation algorithm of…

Instrumentation and Detectors · Physics 2016-09-13 F. Mezei , M. T. Caccamo , F. Migliardo , S. Magazù

Making material experiments more efficient is a high priority for materials scientists who seek to discover new materials with desirable properties. In this paper, we investigate how to optimize the laborious sequential measurements of…

Materials Science · Physics 2019-10-24 Takuya Kanazawa , Akinori Asahara , Hidekazu Morita

We describe a method of white-beam inelastic neutron scattering for improved measurement efficiency. The method consists of matrix inversion and selective extraction. The former is to resolve each incident energy component from the…

Materials Science · Physics 2015-03-19 K. Tomiyasu , M. Matsuura , H. Kimura , K. Iwasa , K. Ohoyama , T. Yokoo , S. Itoh , E. Kudoh , T. Sato , M. Fujita

We present a novel method for sorting events. So far, single variables like flow vector magnitude were used for sorting events. Our approach takes into account the whole azimuthal angle distribution rather than a single variable. This…

Nuclear Theory · Physics 2016-03-17 Renata Kopecna , Boris Tomasik

The extraction of any physical information from quasielastic neutron scattering spectra is generally done by fitting a model to the data by means of chi-square minimization procedure. However, as pointed out by the pioneering work of D.S.…

Data Analysis, Statistics and Probability · Physics 2009-07-23 L. C. Pardo , M. Rovira-Esteva , S. Busch , M. D. Ruiz-Martin , J. Ll. Tamarit , T. Unruh

Background: Uncertainty quantification for nuclear theories has gained a more prominent role in the field, with more and more groups attempting to understand the uncertainties on their calculations. However, recent studies have shown that…

Nuclear Theory · Physics 2021-12-03 M. Catacora-Rios , G. B. King , A. E. Lovell , F. M. Nunes
‹ Prev 1 2 3 10 Next ›