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The modeling of superconducting magnetic bearing (SMB) is of great significance for predicting and optimizing its levitation performance before construction. Although lots of efforts have been made in this area, it still remains some space…

Superconductivity · Physics 2018-08-01 Loïc Quéval , Kun Liu , Wenjiao Yang , Víctor M. R. Zermeño , Guangtong Ma

The supersymmetric standard model with supergravity-inspired soft breaking terms predicts a rich pectrum of sparticles to be discovered at the SSC, LHC and NLC. Because there are more supersymmetric particles than unknown parameters, one…

High Energy Physics - Phenomenology · Physics 2011-03-04 Stephen P. Martin , Pierre Ramond

Learning dynamical models from data plays a vital role in engineering design, optimization, and predictions. Building models describing dynamics of complex processes (e.g., weather dynamics, or reactive flows) using empirical knowledge or…

Machine Learning · Computer Science 2024-09-21 Pawan Goyal , Peter Benner

Although the hyperbolic metric possesses many remarkable properties, it is not defined on arbitrary subdomains of $\mathbb{R}^n$ with $n \geq 2$. This article introduces a new hyperbolic-type metric that provides an alternative approach to…

Metric Geometry · Mathematics 2025-08-01 Bibekananda Maji , Pritam Naskar , Swadesh Kumar Sahoo

We introduce a notion of subunit vector field for fully nonlinear degenerate elliptic equations. We prove that an interior maximum of a viscosity subsolution of such an equation propagates along the trajectories of subunit vector fields.…

Analysis of PDEs · Mathematics 2018-12-27 Martino Bardi , Alessandro Goffi

Given a residually connected incidence geometry $\Gamma$ that satisfies two conditions, denoted $(B_1)$ and $(B_2)$, we construct a new geometry $H(\Gamma)$ with properties similar to those of $\Gamma$. This new geometry $H(\Gamma)$ is…

Combinatorics · Mathematics 2024-05-30 Claudio Alexandre Piedade , Philippe Tranchida

We introduce a framework for solving a class of parabolic partial differential equations on triangle mesh surfaces, including the Hamilton-Jacobi equation and the Fokker-Planck equation. PDE in this class often have nonlinear or stiff terms…

Numerical Analysis · Mathematics 2024-06-04 Leticia Mattos Da Silva , Oded Stein , Justin Solomon

This dissertation presents a new coupled electro-mechanical model that is an improvement on the classical parallel-plate approximation. The model employs a hyperbolic function to account for the beam deformed shape and electrostatic field.…

Applied Physics · Physics 2017-08-24 Xi Luo

In earlier works on Shape Dynamics (SD), a linear method of solving a particular set of Lichnerowicz-type equations through the implicit function theorem was developed in order to implicitly construct SD's global Hamiltonian and eliminate…

General Relativity and Quantum Cosmology · Physics 2012-01-23 Henrique Gomes

We introduce a deep learning framework designed to train smoothed elastoplasticity models with interpretable components, such as a smoothed stored elastic energy function, a yield surface, and a plastic flow that are evolved based on a set…

Machine Learning · Computer Science 2020-10-23 Nikolaos N. Vlassis , WaiChing Sun

We consider the many-body spectra of interacting bosonic quantum fields on a lattice in the semiclassical limit of large particle number $N$. We show that the many-body density of states can be expressed as a coherent sum over oscillating…

Quantum Physics · Physics 2015-12-11 Thomas Engl , Juan Diego Urbina , Klaus Richter

A new development of the ``monodromy transform'' method for analysis of hyperbolic as well as elliptic integrable reductions of Einstein equations is presented. Compatibility conditions for some alternative representations of the…

General Relativity and Quantum Cosmology · Physics 2008-11-26 G. A. Alekseev

Hyperparameters greatly impact models' capabilities; however, modern models are too large for extensive search. Instead, researchers design recipes that train well across scales based on their understanding of the hyperparameters. Despite…

Machine Learning · Computer Science 2025-10-06 Nicholas Lourie , He He , Kyunghyun Cho

This work presents a novel physics-informed deep learning based super-resolution framework to reconstruct high-resolution deformation fields from low-resolution counterparts, obtained from coarse mesh simulations or experiments. We leverage…

Machine Learning · Computer Science 2022-11-24 Rajat Arora

We consider some new limits for the elliptic hypergeometric integrals on root systems. After the degeneration of elliptic beta integrals of type I and type II for root systems $A_n$ and $C_n$ to the hyperbolic hypergeometric integrals, we…

Classical Analysis and ODEs · Mathematics 2024-07-24 G. A. Sarkissian , V. P. Spiridonov

This work extends, to moving geometries, the immersed boundary method based on volume penalization and selective frequency damping approach [J. Kou, E. Ferrer, A combined volume penalization/selective frequency damping approach for immersed…

Fluid Dynamics · Physics 2024-01-10 Jiaqing Kou , Esteban Ferrer

This paper presents a new concept of geometric multipole expansion for the conductivity or anti-plane elasticity problem in two dimensions by using the Faber polynomials. As an application, we construct semi-neutral inclusions of general…

Numerical Analysis · Mathematics 2021-06-23 Doosung Choi , Junbeom Kim , Mikyoung Lim

In this article we study the MSSM with stops and Higgs scalars much lighter than gluinos and squarks of the first two generations. In this setup, one should use an effective field theory with partial supersymmetry in which the gluino and…

High Energy Physics - Phenomenology · Physics 2017-11-15 Jason Aebischer , Andreas Crivellin , Christoph Greub , Youichi Yamada

Modeling the inherent hierarchical structure of 3D objects and 3D scenes is highly desirable, as it enables a more holistic understanding of environments for autonomous agents. Accomplishing this with implicit representations, such as…

Computer Vision and Pattern Recognition · Computer Science 2025-10-27 Lisa Weijler , Sebastian Koch , Fabio Poiesi , Timo Ropinski , Pedro Hermosilla

The two-dimensional extended Hubbard model that includes a nearest- neighbor Heisenberg interaction is studied using a mean-field theory where quasiparticles are defined by an U(8) group of canonical transformations. The theory is a…

Condensed Matter · Physics 2009-10-22 A. B. Eriksson , T. Einarsson , S. Ostlund