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We present a Bayesian surrogate model for the analysis of periodic or quasi-periodic time series data. We describe a computationally efficient implementation that enables Bayesian model comparison. We apply this model to simulated and real…

Methodology · Statistics 2011-07-21 Eric B. Ford , Althea V. Moorhead , Dimitri Veras

A recent proposal to measure the proton form factor by means of muon-proton scattering will use muons which are not ultrarelativistic (and also not nonrelativistic). The usual equations describing the scattering cross section use the…

General Physics · Physics 2013-02-06 E. Borie

Surrogate models provide compact relations between user-defined input parameters and output quantities of interest, enabling the efficient evaluation of complex parametric systems in many-query settings. Such capabilities are essential in a…

Numerical Analysis · Mathematics 2026-03-16 Matteo Giacomini , Pedro Díez

A measurement of total cross-section values of the $^{130}$Ba(p,$\gamma$)$^{131}$La reaction at low proton energies allows a stringent test of statistical model predictions with different proton+nucleus optical model potentials. Since no…

Nuclear Experiment · Physics 2014-09-30 L. Netterdon , A. Endres , G. G. Kiss , J. Mayer , T. Rauscher , P. Scholz , K. Sonnabend , Zs. Török , A. Zilges

We investigate the region of the nuclear chart around $A \simeq 70$ from a three-body perspective, where we compute reaction rates for the radiative capture of two protons. One key quantity is here the photon dissociation cross section for…

Nuclear Theory · Physics 2017-02-23 D. Hove , E. Garrido , A. S. Jensen , H. O. U. Fynbo , D. V. Fedorov , N. T. Zinner

Leveraging the kernel trick in both the input and output spaces, surrogate kernel methods are a flexible and theoretically grounded solution to structured output prediction. If they provide state-of-the-art performance on complex data sets…

Machine Learning · Statistics 2024-05-07 Tamim El Ahmad , Luc Brogat-Motte , Pierre Laforgue , Florence d'Alché-Buc

Fatigue crack growth is one of the most common types of deterioration in metal structures with significant implications on their reliability. Recent advances in Structural Health Monitoring (SHM) have motivated the use of structural…

Machine Learning · Statistics 2023-10-12 Nicholas E. Silionis , Konstantinos N. Anyfantis

High-fidelity numerical simulations of chaotic, high dimensional nonlinear dynamical systems are computationally expensive, necessitating the development of efficient surrogate models. Most surrogate models for such systems are…

Machine Learning · Computer Science 2026-03-16 Dibyajyoti Chakraborty , Hojin Kim , Romit Maulik

Proton capture on $^{19,20}$O nuclei is measured in inverse kinematics with the active target detector MuSIC@Indiana using CH$_4$ as the target gas. Rejection of unreacted and inelastically scattered beam, along with transfer and fusion on…

Nuclear Experiment · Physics 2026-05-21 Rohit Kumar , H. Desilets , R. T. deSouza

A measurement of the inelastic proton-proton cross section with the CMS detector at a center-of-mass energy of $\sqrt{s} =$ 13 TeV is presented. The analysis is based on events with energy deposits in the forward calorimeters, which cover…

High Energy Physics - Experiment · Physics 2018-08-09 CMS Collaboration

Limiting the injection rate to restrict the pressure below a threshold at a critical location can be an important goal of simulations that model the subsurface pressure between injection and extraction wells. The pressure is approximated by…

A new model is proposed for fusion mechanisms of massive nuclear systems where so-called fusion hindrance exists. The model describes two-body collision processes in an approaching phase and shape evolutions of an amalgamated system into…

Nuclear Theory · Physics 2009-11-07 Caiwan Shen , Grigori Kosenko , Yasuhisa Abe

Recent measurements for fusion cross section at energies around the Coulomb barrier have systematically indicated a significant deviation of fusion cross sections from a prediction of double-folding model. It has been argued that the…

Nuclear Theory · Physics 2009-11-11 K. Hagino , K. Washiyama

Interaction cross section measurements in fixed-target scattering experiments are typically performed by measuring the attenuation of a beam of particles that is incident upon a target slab of material. A fully active sampling calorimeter,…

Instrumentation and Detectors · Physics 2022-09-30 Johnny Ho , David W. Schmitz

Predicting the behavior of complex systems in engineering often involves significant uncertainty about operating conditions, such as external loads, environmental effects, and manufacturing variability. As a result, uncertainty…

Computation · Statistics 2025-07-17 S. Marelli , S. Schär , B. Sudret

The differential cross section for the inelastic magnetic scattering of neutrons by superconducting rings is derived theoretically taking account of the interaction of the neutron magnetic moment with magnetic field created by the…

Superconductivity · Physics 2015-05-18 A. I. Agafonov

Neural network surrogate models have emerged as a promising approach to model solution fields for a wide variety of boundary value problems encountered in physical modeling. Stochastic problems represent an area of particularly high…

Machine Learning · Statistics 2026-05-18 Noah Wade , Kirubel Teferra

By evaluating all the contributions of the intermediate states of the multiple scattering theory diagrams, we compute the integrated stripping cross sections of collisions among light nuclei. The resulting expressions have the simple form…

High Energy Physics - Phenomenology · Physics 2009-10-31 Yu. M. Shabelski , D. Treleani

We propose a multi-fidelity neural network surrogate sampling method for the uncertainty quantification of physical/biological systems described by ordinary or partial differential equations. We first generate a set of low/high-fidelity…

Numerical Analysis · Mathematics 2020-05-07 Mohammad Motamed

The coplete analysis of the model-independent leading radiative corrections to cross-section and polarization observables in semi-inclusive deep-inelastic electron-nucleus scattering with detection of a proton and scattered electron in…

High Energy Physics - Phenomenology · Physics 2014-11-17 A. V. Afanas'ev , I. Akushevich , G. I. Gakh , N. P. Merenkov
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