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相关论文: A DG-IMEX method for two-moment neutrino transport…

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We introduce a model for Non-Standard neutral current Interaction (NSI) between neutrinos and the matter fields, with an arbitrary coupling to the up and down quarks. The model is based on a new $U(1)$ gauge symmetry with a light gauge…

高能物理 - 唯象学 · 物理学 2023-02-22 Nicolás Bernal , Yasaman Farzan

We have developed an implicit, multi-group, time-dependent, spherical neutrino transport code based on the Feautrier variables, the tangent-ray method, and accelerated ${\bf \Lambda}$ iteration. The code achieves high angular resolution, is…

天体物理学 · 物理学 2009-10-31 A. Burrows , T. Young , P. A. Pinto , R. Eastman , T. Thompson

High-order discretizations of partial differential equations (PDEs) necessitate high-order time integration schemes capable of handling both stiff and nonstiff operators in an efficient manner. Implicit-explicit (IMEX) integration based on…

数值分析 · 数学 2022-01-19 Steven Roberts , Arash Sarshar , Adrian Sandu

In this work, we propose a nonlinear stabilization technique for scalar conservation laws with implicit time stepping. The method relies on an artificial diffusion method, based on a graph-Laplacian operator. It is nonlinear, since it…

数值分析 · 计算机科学 2016-12-23 Santiago Badia , Jesús Bonilla

In the present work, we investigate a model of the invasion of healthy tissue by cancer cells which is described by a system of nonlinear PDEs consisting of a cross-diffusion-reaction equation and two additional nonlinear ordinary…

数值分析 · 数学 2023-07-18 Shahin Heydari , Petr Knobloch , Thoma Wick

This paper focuses on proposing a deep learning initialized iterative method (Int-Deep) for low-dimensional nonlinear partial differential equations (PDEs). The corresponding framework consists of two phases. In the first phase, an…

数值分析 · 数学 2020-08-26 Jianguo Huang , Haoqin Wang , Haizhao Yang

With the increased penetrations of distributed energy resources (DERs), the need for integrated transmission and distribution system analysis (T&D) is imperative. This paper presents an integrated unbalanced T&D analysis framework using an…

系统与控制 · 电气工程与系统科学 2020-07-15 Gayathri Krishnamoorthy , Anamika Dubey

Next generation direct dark matter (DM) detection experiments will have unprecedented capabilities to explore coherent neutrino-nucleus scattering (CE$\nu$NS) complementary to dedicated neutrino experiments. We demonstrate that future DM…

高能物理 - 唯象学 · 物理学 2024-12-03 Thomas Schwemberger , Volodymyr Takhistov , Tien-Tien Yu

This paper proposes and analyzes two fully discrete mixed interior penalty discontinuous Galerkin (DG) methods for the fourth order nonlinear Cahn-Hilliard equation. Both methods use the backward Euler method for time discretization and…

数值分析 · 数学 2015-02-24 Xiaobing Feng , Yukun Li , Yulong Xing

Systems of reaction-diffusion partial differential equations (RD-PDEs) are widely applied for modelling life science and physico-chemical phenomena. In particular, the coupling between diffusion and nonlinear kinetics can lead to the…

数值分析 · 数学 2019-03-13 Maria Chiara D'Autilia , Ivonne Sgura , Valeria Simoncini

We present a new method for neutrino-matter coupling in multi-dimensional radiation-hydrodynamic simulations of core-collapse supernova (CCSN) with the full Boltzmann neutrino transport. The development is motivated by the fact that the…

高能天体物理现象 · 物理学 2019-08-07 Hiroki Nagakura , Kohsuke Sumiyoshi , Shoichi Yamada

We developed a machine learning model using LightGBM, one of the most popular gradient-boosting decision tree methods these days, to predict the Eddington tensor, or the second-order angular moment, for neutrino radiation transport in…

高能物理 - 唯象学 · 物理学 2025-04-29 Shota Takahashi , Akira Harada , Shoichi Yamada

As low-threshold dark matter detectors advance in development, they will become sensitive to recoils from solar neutrinos which opens up the possibility to explore neutrino properties. We predict the enhancement of the event rate of solar…

高能物理 - 唯象学 · 物理学 2022-07-20 Thomas Schwemberger , Tien-Tien Yu

Neutrinos with energy of order 10~MeV, such as from pion decay-at-rest sources, are an invaluable tool for studying low-energy neutrino interactions with nuclei -- previously enabling the first measurement of coherent elastic…

高能物理 - 唯象学 · 物理学 2022-12-23 Bhaskar Dutta , Wei-Chih Huang , Jayden L. Newstead , Vishvas Pandey

We develop a numerical code to calculate the neutrino transfer with multi-energy and multi-angle in three dimensions (3D) for the study of core-collapse supernovae. The numerical code solves the Boltzmann equations for neutrino…

高能天体物理现象 · 物理学 2012-03-26 Kohsuke Sumiyoshi , Shoichi Yamada

We demonstrate the prompt-delayed signals induced by knockout neutrons from the quasi-elastic scattering in neutrino experiments provides a new avenue for detecting light dark matter. As an illustration, we consider the detection of…

高能物理 - 唯象学 · 物理学 2026-03-25 Yuanlin Gong , Feiran Lin , Ning Liu , Liangliang Su , Lei Wu

We present a unified approach to neutrino processes in nucleon matter based on Landau's theory of Fermi liquids that includes one- and two-quasiparticle-quasihole pair states as well as mean-field effects. We show how rates of neutrino…

核理论 · 物理学 2008-11-26 G. I. Lykasov , C. J. Pethick , A. Schwenk

We classify new physics signals in coherent elastic neutrino-nucleus scattering (CE$\nu$NS) processes induced by $^8$B solar neutrinos in multi-ton xenon dark matter (DM) detectors. Our analysis focuses on vector and scalar interactions in…

高能物理 - 唯象学 · 物理学 2019-10-29 D. Aristizabal Sierra , Bhaskar Dutta , Shu Liao , Louis E. Strigari

We investigate new physics with light-neutral mediators through coherent elastic neutrino-nucleus scattering (CE$\nu$NS) at low energies. These mediators, with a mass of less than $1$ GeV, are common properties for extensions of the…

高能物理 - 唯象学 · 物理学 2024-01-24 Mehmet Demirci , M. Fauzi Mustamin

We propose a Newton-based scheme, initialized by neural operator predictions, to accelerate the parametric solution of nonlinear problems in computational solid mechanics. First, a physics informed conditional neural field is trained to…