Measurement of differential cross sections for single diffractive dissociation in root s=8 TeV pp collisions using the ATLAS ALFA spectrometer
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Neutrino-nucleus scattering cross sections are critical theoretical inputs for long-baseline neutrino oscillation experiments. However, robust modeling of these cross sections remains challenging. For a simple but physically motivated toy model of the DUNE experiment, we demonstrate that an accurate neural-network model of the cross section—leveraging only Standard-Model symmetries—can be learned from near-detector data. We perform a neutrino oscillation analysis with simulated far-detector events, finding that oscillation analysis results enabled by our data-driven cross-section model approach the theoretical limit achievable with perfect prior knowledge of the cross section. We further quantify the effects of flux shape and detector resolution uncertainties as well as systematics from cross-section mismodeling. This proof-of-principle study highlights the potential of future neutrino near-detector datasets and data-driven cross-section models.
Neutrino-nucleus scattering cross sections are critical theoretical inputs for long-baseline neutrino oscillation experiments. However, robust modeling of these cross sections remains challenging. For a simple but physically motivated toy model of the DUNE experiment, we demonstrate that an accurate neural-network model of the cross section—leveraging only Standard-Model symmetries— can be learned from near-detector data. We perform a neutrino oscillation analysis with simulated far-detector events, finding that oscillation analysis results enabled by our data-driven cross-section model approach the theoretical limit achievable with perfect prior knowledge of the cross section. We further quantify the effects of flux shape and detector resolution uncertainties as well as systematics from cross-section mismodeling. This proof-of-principle study highlights the potential of future neutrino near-detector datasets and data-driven cross-section models.
Neutrino-nucleus scattering cross sections are critical theoretical inputs for long-baseline neutrino oscillation experiments. However, robust modeling of these cross sections remains challenging. For a simple but physically motivated toy model of the DUNE experiment, we demonstrate that an accurate neural-network model of the cross section -- leveraging Standard Model symmetries -- can be learned from near-detector data. We then perform a neutrino oscillation analysis with simulated far-detector events, finding that the modeled cross section achieves results consistent with what could be obtained if the true cross section were known exactly. This proof-of-principle study highlights the potential of future neutrino near-detector datasets and data-driven cross-section models.
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For decades, copper has been used to improve the performance of cadmium telluride thin film solar cells. However, it has also been shown to be the main cause of metastability in CdTe. Recently a low activation energy has been reported for the thermal diffusion of Cu in CdTe explaining the ease of motion that it has under moderate temperatures. The community consensus is that copper segregates to the absorber grain boundaries, where it's either beneficial or detrimental to device performance depending on its concentration. Using nanoscale X-ray micrsocopy and a two-dimensional drift-diffusion model we present a preliminary correlation between local copper distribution and electrical performance of a single-junction CdTe/CdS solar cell.
Modern neutrino-nucleus cross section computations need to incorporate sophisticated nuclear models to achieve greater predictive precision. However, the computational complexity of these advanced models often limits their practicality for experimental analyses. To address this challenge, we introduce a new Monte Carlo method utilizing normalizing flows to generate surrogate cross sections that closely approximate those of the original model while significantly reducing computational overhead. As a case study, we built a Monte Carlo event generator for the neutrino-nucleus cross section model developed by the Ghent group. This model employs a Hartree-Fock procedure to establish a quantum mechanical framework in which both the bound and scattering nucleon states are solutions to the mean-field nuclear potential. The surrogate cross sections generated by our method demonstrate excellent accuracy with a relative effective sample size of more than 98.4%, providing a computationally efficient alternative to traditional Monte Carlo sampling methods for differential cross sections.
Cross sections for photo-induced bound-free and free-free transitions in plasmas are evaluated in the average-atom approximation and applied to determine opacities of dense plasmas of light elements. Parameters characterizing the plasmas (chemical potential, average ionic charge, free electron density, bound and continuum wave functions, and occupation numbers) are obtained from the average-atom model. Lowest-order calculations of the free-free cross sections, which diverge in the low-frequency limit, are regularized by accounting for the finite electron-ion relaxation time. The resulting analysis provides the basis for average-atom studies of plasma opacities. Such studies are presented for dense lithium, beryllium, boron, and carbon. Applications are given to Rosseland mean opacities of dense hydrogen and deuterium plasmas and to comparisons of free-free to bound-free opacities in shock-compressed plasmas. Average-atom cross section and opacity calculations are extended to plasmas consisting of more than one ionic species, boron nitride, polystyrene, and a composite H, He, C plasma.
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The generation of high-order neutron scattering cross sections consistent with high-fidelity simulations remains an area of active research. Popular options include generating cross sections from continuous energy Monte Carlo calculations or generating cross sections from a deterministic neutron transport calculation with high-fidelity tabulated cross sections. Both options present challenges. Monte Carlo simulations can naturally process continuous energy cross section data and allow for the general description of anisotropic neutron scattering given a scattering law. However, Monte Carlo simulations are inherently related to particle weighting and it has been suggested that this may be unacceptable for generating high-order neutron scattering cross sections. Deterministic neutron transport calculations can easily calculate high-order moments of the flux to appropriately calculate higher-order neutron scattering cross sections but are generally limited by discretization of space, energy, and angle. In this work, the trade-offs between generation of high-order neutron scattering cross sections via Monte Carlo and deterministic neutron transport methods are investigated. The methods implemented in the Monte Carlo computer program Serpent and the deterministic fast reactor neutron cross section generator MC2-3 are compared. Cross sections resulting from these methods are used in Rattlesnake, a deterministic neutron transport code developed by Idaho National Laboratory (INL), and results are compared to a reference continuous energy Monte Carlo calculation. Whereas previous work investigating the effects of anisotropic neutron scattering has focused on light water reactor (LWR) simulations, this work focuses on high-order neutron scattering cross sections as they relate to fast reactor simulations. To investigate the consequences of the Serpent and MC2-3 methodologies, a test problem is developed. The test problem is a one-dimensional geometry with fast reactor materials designed to demonstrate deep penetration and exacerbate the effects of high-order neutron scattering. Based on the results of the deep penetration test problem, it is concluded that P3 neutron scattering cross sections are sufficient to describe anisotropic scattering in fast reactor materials. Any neutron scattering of order higher than P3 offers negligible change in the eigenvalue of the test problem. Additionally, it is determined that the methodology as implemented in Serpent is applicable for generating high-order neutron scattering cross sections through at least P3 in fast reactor materials.
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The thermal neutron capture cross section of 88 Zr was recently reported to be the second largest in nature with the largest resonance integral measured. Presumably, these very large values are caused by a resonance or resonances very near thermal energy. Determining their energies and widths, and hence the shape of the cross section away from thermal energies,is useful for applications. The short half-life (83.4 days) and associated large background, renders direct measurements of the neutron capture cross section impossible using current techniques. However, it is possible to measure the total neutron cross section, and hence the resonance properties, using the newly commissioned Device for Indirect Capture Experiments on Radionuclides (DICER) at the Los Alamos Neutron Science Center (LANSCE). Transmission measurements are utilized as a surrogate method to perform capture measurements. The 88 Zr needed for a DICER measurement was produced at the Isotope Production Facility (IPF) and cleanly separated from the production target material. A description of the new instrument, efforts and preliminary results on 88 Zr will be presented.
NOvA inclusive electron neutrino cross section results presented at Neutrino2020Exposure:8.09E20 protons-on-target, neutrino-enhanced beamData release contains 3 ROOT files containing the double-differential measurement with respect to electron angle (cos theta) and electron energy, a single-differential measurement with respect to squared four-momentum transfer (Q2), and the total cross section as a function of neutrino energy. The 1D cross-section measurements include the same kinematic phase space restrictions present in the double-differential analysis.The files, xsec_{dThdE/Enu/dQ2}.root, contain the extracted cross section and associated covariance matrices for the double-differential cross section with respect to the observed electron kinematics, dThdE, neutrino energy, Enu, and squared four-momentum transfer, Q^2.In each file there will be the following histograms:— TH2D/TH1D xsec: unfolded measured cross section— TH2D xsec_cov: cross section covariance matrix— TH2D stat_cov: statistical covariance matrixIncludes text files, xsec_{dThdE/Enu/dQ2}.txt show the corresponding histograms in plain text format.
Outline: Why cross sections are relevant for neutrino oscillation; Past and present measurements of neutrino cross sections; Theoretical models of neutrino cross sections; Future program for neutrino cross section measurements and calculations.
Neutrino-nucleus cross section measurements are needed to improve interaction modeling to meet the precision needs of neutrino experiments in efforts to measure oscillation parameters and search for physics beyond the Standard Model. We review the difficulties associated with modeling neutrino-nucleus interactions that lead to a dependence on event generators in oscillation analyses and cross section measurements alike. We then describe data-driven model validation techniques intended to address this model dependence. The method relies on utilizing various goodness-of-fit tests and the correlations between different observables and channels to probe the model for defects in the phase space relevant for the desired analysis. These techniques shed light on relevant mismodeling, allowing it to be detected before it begins to bias the cross section results. We compare more commonly used model validation methods which directly validate the model against alternative ones to these data-driven techniques and show their efficacy with fake data studies. These studies demonstrate that employing data-driven model validation in cross section measurements represents a reliable strategy to produce robust results that will stimulate the desired improvements to interaction modeling.
Neutrino-nucleus cross section measurements are needed to improve interaction modeling to meet the precision needs of neutrino experiments in efforts to measure oscillation parameters and search for physics beyond the Standard Model. We review the difficulties associated with modeling neutrino-nucleus interactions that lead to a dependence on event generators in oscillation analyses and cross section measurements alike. We then describe data-driven model validation techniques intended to address this model dependence. The method relies on utilizing various goodness-of-fit tests and the correlations between different observables and channels to probe the model for defects in the phase space relevant for the desired analysis. These techniques shed light on relevant mismodeling, allowing it to be detected before it begins to bias the cross section results. We compare more commonly used model validation methods which directly validate the model against alternative ones to these data-driven techniques and show their efficacy with fake data studies. These studies demonstrate that employing data-driven model validation in cross section measurements represents a reliable strategy to produce robust results that will stimulate the desired improvements to interaction modeling.