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Obtaining complete information about the shape of an object by looking at it from a single direction is impossible in general. In this paper, we theoretically study obtaining differential geometric information of an object from orthogonal…

Differential Geometry · Mathematics 2020-10-08 Masaru Hasegawa , Yutaro Kabata , Kentaro Saji

A template-based generic programming approach was presented in a previous paper that separates the development effort of programming a physical model from that of computing additional quantities, such as derivatives, needed for embedded…

Mathematical Software · Computer Science 2012-05-18 Roger P. Pawlowski , Eric T. Phipps , Andrew G. Salinger , Steven J. Owen , Christopher M. Siefert , Matthew L. Staten

We obtain approximate convexity principles for solutions to some classes of nonlinear elliptic partial differential equations in convex domains involving approximately concave nonlinearities. Furthermore, we provide some applications to…

Analysis of PDEs · Mathematics 2019-02-19 Claudia Bucur , Marco Squassina

Recently, a family of unconventional integrators for ODEs with polynomial vector fields was proposed, based on the polarization of vector fields. The simplest instance is the by now famous Kahan discretization for quadratic vector fields.…

Exactly Solvable and Integrable Systems · Physics 2024-02-28 Yuri B. Suris

We present a spectrally accurate embedded boundary method for solving linear, inhomogeneous, elliptic partial differential equations (PDE) in general smooth geometries, focusing in this manuscript on the Poisson, modified Helmholtz, and…

Numerical Analysis · Mathematics 2022-09-28 David B. Stein

Distance functions are crucial in robotics for representing spatial relationships between a robot and its environment. They provide an implicit, continuous, and differentiable representation that integrates seamlessly with control,…

Robotics · Computer Science 2026-01-28 Yiming Li , Jiacheng Qiu , Sylvain Calinon

Partial differential equations often contain unknown functions that are difficult or impossible to measure directly, hampering our ability to derive predictions from the model. Workflows for recovering scalar PDE parameters from data are…

Machine Learning · Computer Science 2026-02-16 Torkel E. Loman , Yurij Salmaniw , Antonio Leon Villares , Jose A. Carrillo , Ruth E. Baker

We derive the exact generating function for planar maps (genus zero fatgraphs) with vertices of arbitrary even valence and with two marked points at a fixed geodesic distance. This is done in a purely combinatorial way based on a bijection…

Statistical Mechanics · Physics 2010-04-05 J. Bouttier , P. Di Francesco , E. Guitter

Data are often represented as graphs. Many common tasks in data science are based on distances between entities. While some data science methodologies natively take graphs as their input, there are many more that take their input in…

Machine Learning · Computer Science 2019-09-19 Leo Liberti

In this article, we describe an approach for solving partial differential equations with general boundary conditions imposed on arbitrarily shaped boundaries. A continuous function, the domain parameter, is used to modify the original…

Mathematical Physics · Physics 2015-05-28 Hui-Chia Yu , Hsun-Yi Chen , K. Thornton

The aim of this paper is to suggest a new viewpoint to study qualitative properties of solutions of semilinear elliptic PDE's defined outside a compact set. The relevant tools come from spectral theory and from a combination of stochastic…

Differential Geometry · Mathematics 2012-08-07 G. Pacelli Bessa , Stefano Pigola , Alberto G. Setti

We consider propagating, spatially localised waves in a class of equations that contain variational and non-variational terms. The dynamics of the waves is analysed through a collective coordinate approach. Motivated by the variational…

Pattern Formation and Solitons · Physics 2015-06-16 J. H. P. Dawes , H. Susanto

Tropical Differential Algebraic Geometry considers difficult or even intractable problems in Differential Equations and tries to extract information on their solutions from a restricted structure of the input. The Fundamental Theorem of…

We present a short review of the evolution of the methodology of the Method of simplest equation for obtaining exact particular solutions of nonlinear partial differential equations (NPDEs) and the recent extension of a version of this…

Exactly Solvable and Integrable Systems · Physics 2019-06-20 Nikolay K. Vitanov

The modern machine learning methods allow one to obtain the data-driven models in various ways. However, the more complex the model is, the harder it is to interpret. In the paper, we describe the algorithm for the mathematical equations…

Neural and Evolutionary Computing · Computer Science 2021-09-09 Alexander Hvatov , Mikhail Maslyaev

We propose a simple relativistic derivation of the electric and the magnetic fields generated by an electric point charge moving with constant velocity. Our approach is based on the radar detection of the point space coordinates where the…

General Physics · Physics 2008-12-02 Bernhard Rothenstein , Stefan Popescu , George J. Spix

We present a systematic technique to find explicit solutions of birational maps, provided that these solutions are given in terms of elliptic functions. The two main ingredients are: (i) application of classical addition theorems for…

Exactly Solvable and Integrable Systems · Physics 2019-11-11 Matteo Petrera , Andreas Pfadler , Yuri B. Suris

We use the method of synthetic differential geometry to revisit the geometric reasoning employed by Lie, Klein and others in their study of partial differential equations.

Analysis of PDEs · Mathematics 2010-11-29 Anders Kock

In this work we study the problem about learning a partial differential equation (PDE) from its solution data. PDEs of various types are used as examples to illustrate how much the solution data can reveal the PDE operator depending on the…

Numerical Analysis · Mathematics 2022-11-10 Yuchen He , Hongkai Zhao , Yimin Zhong

A new formulation of physical thermal models for variable plug flow through a pipe is proposed. The derived model is based on a commonly used one-dimensional distributed parameter model, which explicitly takes into account the heat capacity…

Systems and Control · Electrical Eng. & Systems 2020-01-10 Jens Wurm , Simon Bachler , Frank Woittennek