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Two-dimensional array-based datasets are pervasive in a variety of domains. Current approaches for generative modeling have typically been limited to conventional image datasets and performed in the pixel domain which do not explicitly…

Machine Learning · Computer Science 2021-07-12 Hoda Shajari , Jaemoon Lee , Sanjay Ranka , Anand Rangarajan

Datasets such as images, text, or movies are embedded in high-dimensional spaces. However, in important cases such as images of objects, the statistical structure in the data constrains samples to a manifold of dramatically lower…

Machine Learning · Computer Science 2019-10-29 Stefano Recanatesi , Matthew Farrell , Madhu Advani , Timothy Moore , Guillaume Lajoie , Eric Shea-Brown

Using dimensional reduction we construct an effective 3D theory of the Minimal Supersymmetric Standard Model at finite temperature. The final effective theory is obtained after three successive stages of integration out of massive…

High Energy Physics - Phenomenology · Physics 2011-05-05 Marta Losada

Context. Observations of many active regions show a slow systematic outflow/upflow from their edges lasting from hours to days. At present no physical explanation has been proven, while several suggestions have been put forward. Aims. This…

Solar and Stellar Astrophysics · Physics 2021-08-25 K. Galsgaard , M. S. Madjarska , K. Vanninathan , Z. Huang , M. Presmann

We assemble the equations of general relativistic magnetohydrodynamics (MHD) in 3+1 form. These consist of the complete coupled set of Maxwell equations for the electromagnetic field, Einstein's equations for the gravitational field, and…

Astrophysics · Physics 2009-11-07 Thomas W. Baumgarte , Stuart L. Shapiro

We propose some one-dimensional reduced models for the three-dimensional electron magnetohydrodynamics which involves a highly nonlinear Hall term with intricate structure. The models contain nonlocal nonlinear terms. Local well-posedness…

Analysis of PDEs · Mathematics 2022-05-23 Mimi Dai

Integrable systems in low dimensions, constructed through the symmetry reduction method, are studied using phase portrait and variable separation techniques. In particular, invariant quantities and explicit periodic solutions are…

solv-int · Physics 2009-10-31 J. A. Calzada , M. A. del Olmo , M. A. Rodriguez

The three-dimensional compressible magnetohydrodynamic (MHD) isentropic flow with zero magnetic diffusivity is studied. The vanishing magnetic diffusivity causes significant difficulties due to the loss of dissipation of the magnetic field.…

Analysis of PDEs · Mathematics 2011-08-30 Xiaoli Li , Ning Su , Dehua Wang

Magnetic reconnection drives a wide range of astrophysical plasma phenomena, including solar flares, by converting magnetic energy into plasma energy through changes in magnetic field topology. Petschek reconnection is a magnetohydrodynamic…

Solar and Stellar Astrophysics · Physics 2026-04-01 Keita Akutagawa , Shinsuke Imada , Munehito Shoda

Applications of deep learning to physical simulations such as Computational Fluid Dynamics have recently experienced a surge in interest, and their viability has been demonstrated in different domains. However, due to the highly complex,…

Machine Learning · Computer Science 2025-03-19 Giuseppe Bruni , Sepehr Maleki , Senthil K. Krishnababu

In magnetohydrodynamic (MHD) turbulence, the large-scale magnetic field sets a preferred local direction for the small-scale dynamics, altering the statistics of turbulence from the isotropic case. This happens even in the absence of a…

Plasma Physics · Physics 2017-05-10 Vladimir Zhdankin , Stanislav Boldyrev , Joanne Mason

We derive dyadic models for the magnetohydrodynamics with Hall effect by including the intermittency dimension as a parameter. For such dyadic models, existence of global weak solutions is established. In addition, local strong solution is…

Analysis of PDEs · Mathematics 2021-11-10 Mimi Dai

The impressive progress of the kinetic schemes in the solution of gas dynamics problems and the development of effective parallel algorithms for modern high performance parallel computing systems led to the development of advanced methods…

Plasma Physics · Physics 2013-05-06 B. Chetverushkin , N. D'Ascenzo , V. Saveliev

Computational magnetohydrodynamics (MHD) for space physics has become an essential area in understanding the multiscale dynamics of geophysical and astrophysical plasma processes, partially motivated by the lack of space data. Full MHD…

Smoothed particle magnetohydrodynamics has reached a level of maturity that enables the study of a wide range of astrophysical problems. In this review, the numerical details of the modern SPMHD method are described. The three fundamental…

Instrumentation and Methods for Astrophysics · Physics 2023-11-27 Terrence S. Tricco

A systematic study of energy conservation for extended magnetohydrodynamic (MHD) models that include Hall terms and electron inertia is performed. It is observed that commonly used models do not conserve energy in the ideal limit, i.e.,…

Plasma Physics · Physics 2015-06-19 Keiji Kimura , P. J. Morrison

Computing reduced-order models using non-intrusive methods is particularly attractive for systems that are simulated using black-box solvers. However, obtaining accurate data-driven models can be challenging, especially if the underlying…

Mathematical Physics · Physics 2024-01-03 Alberto Padovan , Blaine Vollmer , Daniel J. Bodony

This paper explores structure formation in two-dimensional magnetohydrodynamic (MHD) turbulence as a modulational instability (MI) of turbulent fluctuations. We focus on the early stages of structure formation and consider simple…

Plasma Physics · Physics 2024-02-21 S. Jin , I. Y. Dodin

Electron magnetohydrodynamic (EMHD) turbulence in two dimensions is studied via high-resolution numerical simulations with a normal diffusivity. The resulting energy spectra asymptotically approach a $k^{-5/2}$ law with increasing $R_B$,…

Plasma Physics · Physics 2009-05-01 C. J. Wareing , R. Hollerbach

Advances in mobile computing technologies have made it possible to monitor and apply data-driven interventions across complex systems in real time. Markov decision processes (MDPs) are the primary model for sequential decision problems with…

Methodology · Statistics 2018-03-20 Longshaokan Wang , Eric B. Laber , Katie Witkiewitz
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