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We introduce two new methods that are designed to improve the realism and utility of large, active region-scale 3D MHD models of the solar atmosphere. We apply these methods to RADMHD, a code capable of modeling the Sun's upper convection…

Solar and Stellar Astrophysics · Physics 2010-05-06 William P. Abbett , George H. Fisher

We study the derived category of coherent sheaves on various versions of moduli space of vector bundles on curves by the Borel-Weil-Bott theory for loop groups and $\Theta$-stratification, and construct a semiorthogonal decomposition with…

Algebraic Geometry · Mathematics 2021-09-02 Kai Xu , Shing-Tung Yau

We present results from multifrequency polarimetry of NRAO 140 using the Very Long Baseline Array. These observations allow us to reveal the distributions of both the polarization position angle and the Faraday rotation measure (RM). These…

Astrophysics · Physics 2009-11-13 Keiichi Asada , Makoto Inoue , Masanori Nakamura , Seiji Kameno , Hiroshi Nagai

In this work, we present a nonhomogeneous version of the classical div-curl type estimates in the setup of elliptic system of complex vector fields with constant coefficients on local Hardy space $h^1$. As an application, we obtain a…

Analysis of PDEs · Mathematics 2025-05-01 Catarina Machado , Tiago Picon

Magnetostatics defines a class of boundary value problems in which the topology of the domain plays a subtle role. For example, representability of a divergence-free field as the curl of a vector potential comes about because of homological…

Plasma Physics · Physics 2024-06-19 David Pfefferlé , Lyle Noakes

Decoupled fractional Laplacian wave equation can describe the seismic wave propagation in attenuating media. Fourier pseudospectral implementations, which solve the equation in spatial frequency domain, are the only existing methods for…

Numerical Analysis · Mathematics 2018-01-08 Yiran Xu , Jingye Li , Guofei Pang , Zhikai Wang , Xiaohong Chen

By combining the Grassmann algebra with multi-scale entanglement renormalization ansatz (MERA), we introduce a new unbiased and effective numerical method for simulating 2D strongly correlated electronic systems. The new GMERA method…

Strongly Correlated Electrons · Physics 2015-06-12 Jie Lou , Yan Chen

We introduce new hybridizable discontinuous Galerkin (HDG) methods for solving the two-dimensional vector Laplacian equation under three types of boundary conditions: electric, magnetic, and Dirichlet. The method is formulated on a…

Numerical Analysis · Mathematics 2026-04-08 Bernardo Cockburn , Cristhian Núñez , Manuel A. Sánchez

In the holographic correspondence of quantum gravity, a global onsite symmetry at the boundary generally translates to a local gauge symmetry in the bulk. We describe one way how the global boundary onsite symmetries can be gauged within…

Strongly Correlated Electrons · Physics 2018-01-31 Sukhwinder Singh , Nathan A. McMahon , Gavin K. Brennen

In this paper we study moduli spaces of sheaves on an abelian or projective K3 surface. If $S$ is a K3, $v=2w$ is a Mukai vector on $S$, where $w$ is primitive and $w^{2}=2$, and $H$ is a $v-$generic polarization on $S$, then the moduli…

Algebraic Geometry · Mathematics 2014-03-04 Arvid Perego , Antonio Rapagnetta

Nonlocal operators that have appeared in a variety of physical models satisfy identities and enjoy a range of properties similar to their classical counterparts. In this paper we obtain Helmholtz-Hodge type decompositions for two-point…

Analysis of PDEs · Mathematics 2019-08-26 M. D'Elia , C. Flores , X. Li , P. Radu , Y. Yu

Unknown-view tomography (UVT) reconstructs a 3D density map from its 2D projections at unknown, random orientations. A line of work starting with Kam (1980) employs the method of moments (MoM) with rotation-invariant Fourier features to…

Optimization and Control · Mathematics 2023-06-13 Shuai Huang , Mona Zehni , Ivan Dokmanić , Zhizhen Zhao

We propose a new approach, multi-view Laplacian support vector machines (SVMs), for semi-supervised learning under the multi-view scenario. It integrates manifold regularization and multi-view regularization into the usual formulation of…

Machine Learning · Computer Science 2013-07-29 Shiliang Sun

In recent years, new high spatial resolution observations of the Sun's atmosphere have revealed the presence of a plethora of small-scale magnetic elements down to the resolution limit of current cohort of solar telescopes ($\sim 100-120$…

This paper presents a numerical study on multigrid algorithms of $V$-cycle type for problems posed in the Hilbert space $H(\mathbf{curl})$ in three dimensions. The multigrid methods are designed for discrete problems originated from the…

Numerical Analysis · Mathematics 2022-09-07 Duk-Soon Oh

We construct a space of vector fields that are normal to differentiable curves in the plane. Its basis functions are defined via saddle point variational problems in reproducing kernel Hilbert spaces (RKHSs). First, we study the properties…

Optimization and Control · Mathematics 2018-07-04 Alberto Paganini , Kevin Sturm

We construct an explicit orthonormal basis of piecewise ${}_{i+1}F_{i}$ hypergeometric polynomials for the Alpert multiresolution analysis. The Fourier transform of each basis function is written in terms of ${}_2F_3$ hypergeometric…

Classical Analysis and ODEs · Mathematics 2015-02-05 Jeffrey S. Geronimo , Plamen Iliev

We propose V--cycle multigrid methods for vector field problems arising from the lowest order hexahedral N\'{e}d\'{e}lec finite element. Since the conventional scalar smoothing techniques do not work well for the problems, a new type of…

Numerical Analysis · Mathematics 2022-05-13 Duk-Soon Oh

An analogue of the total variation prior for the normal vector field along the boundary of piecewise flat shapes in 3D is introduced. A major class of examples are triangulated surfaces as they occur for instance in finite element…

Numerical Analysis · Mathematics 2020-06-24 Ronny Bergmann , Marc Herrmann , Roland Herzog , Stephan Schmidt , José Vidal Núñez

Implicit Neural Representations (INRs) have emerged as a powerful paradigm for parameterizing physical fields, yet they often suffer from spectral bias and the computational expense of non-convex optimization. We introduce the Vekua Layer…

Machine Learning · Computer Science 2025-12-15 Vladimer Khasia