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The ability to detect when a system undergoes an incipient fault is of paramount importance in preventing a critical failure. Classic methods for fault detection (including model-based and data-driven approaches) rely on thresholding error…

Signal Processing · Electrical Eng. & Systems 2025-02-13 Camilo Ramírez , Jorge F. Silva , Ferhat Tamssaouet , Tomás Rojas , Marcos E. Orchard

Neutrino experiments study the least understood of the Standard Model particles by observing their direct interactions with matter or searching for ultra-rare signals. The study of neutrinos typically requires overcoming large backgrounds,…

Computational Physics · Physics 2020-12-30 Fernanda Psihas , Micah Groh , Christopher Tunnell , Karl Warburton

In scientific inference problems, the underlying statistical modeling assumptions have a crucial impact on the end results. There exist, however, only a few automatic means for validating these fundamental modelling assumptions. The…

Methodology · Statistics 2019-05-21 Andreas Svensson , Dave Zachariah , Petre Stoica , Thomas B. Schön

We discuss the implementation of the nuclear model based on realistic nuclear spectral functions in the GENIE neutrino interaction generator. Besides improving on the Fermi gas description of the nuclear ground state, our scheme involves a…

High Energy Physics - Experiment · Physics 2014-11-19 C. -M. Jen , A. Ankowski , O. Benhar , A. P. Furmanski , L. N. Kalousis , C. Mariani

Model-based approaches for image reconstruction, analysis and interpretation have made significant progress over the last decades. Many of these approaches are based on either mathematical, physical or biological models. A challenge for…

Computer Vision and Pattern Recognition · Computer Science 2019-10-01 Daniel Rueckert , Julia A. Schnabel

Validation is often defined as the process of determining the degree to which a model is an accurate representation of the real world from the perspective of its intended uses. Validation is crucial as industries and governments depend…

Data Analysis, Statistics and Probability · Physics 2015-06-26 D. Sornette , A. B. Davis , K. Ide , K. R. Vixie , V. Pisarenko , J. R. Kamm

A networked oscillator based analysis is performed for periodic bluff body flows to examine and control the transfer of kinetic energy. Spatial modes extracted from the flow field with corresponding amplitudes form a set of oscillators…

Fluid Dynamics · Physics 2018-06-27 Aditya G. Nair , Steven L. Brunton , Kunihiko Taira

We explore the complementarity between LHC searches and neutrino experiments in probing neutrino non-standard interactions. Our study spans the theoretical frameworks of effective field theory, simplified model and an illustrative UV…

High Energy Physics - Phenomenology · Physics 2021-02-16 K. S. Babu , Dorival Gonçalves , Sudip Jana , Pedro A. N. Machado

Neutrino oscillations have become well-known phenomenon; the measurements of neutrino mixing angles and mass squared differences are continuously improving. Future oscillation experiments will eventually determine the remaining unknown…

High Energy Physics - Phenomenology · Physics 2015-09-30 O. G. Miranda , H. Nunokawa

Global analyses of particle physics data are integral for validating and scrutinizing published results of experiments. Global fits of anomalous oscillation data which search for one or more eV-scale sterile neutrinos are particularly…

High Energy Physics - Phenomenology · Physics 2025-12-08 Joshua Villarreal , Julia Woodward , John Hardin , Janet Conrad

We investigate whether a neural network approach can reproduce and predict the electron-nucleus cross sections in the kinematical domain of present and future accelerator-based neutrino oscillation experiments. For this purpose, we consider…

Nuclear Theory · Physics 2023-06-21 O. Al Hammal , M. Martini , J. Frontera-Pons , T. H. Nguyen , R. Perez-Ramos

We study to what extent upcoming precision neutrino oscillation experiments will be able to exclude one of the most predictive models of neutrino mass and mixing: the Littlest Seesaw. We show that this model provides a good fit to current…

High Energy Physics - Phenomenology · Physics 2017-04-26 Peter Ballett , Stephen F. King , Silvia Pascoli , Nick W. Prouse , TseChun Wang

While many statistical models and methods are now available for network analysis, resampling network data remains a challenging problem. Cross-validation is a useful general tool for model selection and parameter tuning, but is not directly…

Methodology · Statistics 2020-05-04 Tianxi Li , Elizaveta Levina , Ji Zhu

In neutrino oscillation experiments precise measurement of neutrino oscillation parameters is of prime importance as well as a challenge. To improve the statistics, presently running and proposed experiments are using heavy nuclear targets.…

High Energy Physics - Phenomenology · Physics 2020-09-18 Srishti Nagu , Jaydip Singh , Jyotsna Singh , R. B. Singh

Data-driven simulation of pedestrian dynamics is an incipient and promising approach for building reliable microscopic pedestrian models. We propose a methodology based on generalized regression neural networks, which does not have to deal…

Physics and Society · Physics 2019-07-19 Rafael F. Martin , Daniel R. Parisi

In recent years a number of new theoretical models have been implemented into Monte-Carlo neutrino interaction event generators. Being able to compare multiple model predictions is invaluable to the field, especially as it is unfortunately…

High Energy Physics - Experiment · Physics 2016-11-11 P. Stowell , S. Cartwright , L. Pickering , C. Wret , C. Wilkinson

In analyzing neutrino oscillation experiments it is often assumed that while new physics contributes to neutrino masses, neutrino interactions are given by the Standard Model. We develop a formalism to study new physics effects in neutrino…

High Energy Physics - Phenomenology · Physics 2009-10-28 Yuval Grossman

The possibility of measuring neutral-current coherent elastic neutrino-nucleus scattering (CENNS) at the TEXONO experiment has opened high expectations towards probing exotic neutrino properties. Focusing on low threshold Germanium-based…

High Energy Physics - Phenomenology · Physics 2015-10-06 T. S. Kosmas , O. G. Miranda , D. K. Papoulias , M. Tortola , J. W. F. Valle

In this paper, we develop an implementation of cross-validation for penalized linear mixed models. While these models have been proposed for correlated high-dimensional data, the current literature implicitly assumes that tuning parameter…

Methodology · Statistics 2025-03-19 Tabitha K. Peter , Patrick J. Breheny

The low energy part of the reactor neutrino spectra has not been experimentally measured. Its uncertainties limit the sensitivities in certain reactor neutrino experiments. The origin of these uncertainties are discussed, and the effects on…

High Energy Physics - Experiment · Physics 2009-09-25 Hau-Bin Li , Henry T. Wong