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Related papers: Solving large classes of nonlinear systems of PDEs

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In this paper, we consider the {\it tensor absolute value equations} (TAVEs), which is a newly introduced problem in the context of multilinear systems. Although the system of TAVEs is an interesting generalization of matrix {\it absolute…

Optimization and Control · Mathematics 2018-10-16 Chen Ling , Weijie Yan , Hongjin He , Liqun Qi

We consider a class of particular solutions to the (2+1)-dimensional nonlinear partial differential equation (PDE) $u_t +\partial_{x_2}^n u_{x_1} - u_{x_1} u =0$ (here $n$ is any integer) reducing it to the ordinary differential equation…

Exactly Solvable and Integrable Systems · Physics 2015-06-15 A. I. Zenchuk

In this paper we provide a rigorous mathematical foundation for continuous approximations of a class of systems with piece-wise continuous functions. By using techniques from the theory of differential inclusions, the underlying piece-wise…

Chaotic Dynamics · Physics 2014-08-20 Marius-F. Danca

High-dimensional partial-differential equations (PDEs) arise in a number of fields of science and engineering, where they are used to describe the evolution of joint probability functions. Their examples include the Boltzmann and…

Numerical Analysis · Mathematics 2018-10-17 A. M. P. Boelens , D. Venturi , D. M. Tartakovsky

In this paper we employ a "direct method" in order to obtain rank-k solutions of any hyperbolic system of first order quasilinear differential equations in many dimensions. We discuss in detail the necessary and sufficient conditions for…

Mathematical Physics · Physics 2015-06-26 A. M. Grundland , B. Huard

Finite element simulations have been used to solve various partial differential equations (PDEs) that model physical, chemical, and biological phenomena. The resulting discretized solutions to PDEs often do not satisfy requisite physical…

Numerical Analysis · Mathematics 2022-03-17 Vidhi Zala , Robert M. Kirby , Akil Narayan

We represent an integration algorithm combining the characteristics method and Hopf-Cole transformation. This algorithm allows one to partially integrate a large class of multidimensional systems of nonlinear Partial Differential Equations…

Exactly Solvable and Integrable Systems · Physics 2012-10-29 A. I. Zenchuk

Over the centuries mathematicians have been challenged by the partial differential equations (PDEs) that describe the motion of fluids in many physical contexts. Important and beautiful results were obtained in the past one hundred years,…

Analysis of PDEs · Mathematics 2023-07-05 Alexey Cheskidov , Mimi Dai , Susan Friedlander

We are concerned with hyperbolic systems of order-one linear PDEs originated on non-characteristic manifolds. We put forward a simple but effective method of transforming such initial conditions to standard initial conditions (i.e. when the…

Analysis of PDEs · Mathematics 2019-05-22 Alexei Rybkin

Identifying integrable coupled nonlinear ordinary differential equations (ODEs) of dissipative type and deducing their general solutions are some of the challenging tasks in nonlinear dynamics. In this paper we undertake these problems and…

Exactly Solvable and Integrable Systems · Physics 2010-10-28 R. Gladwin Pradeep , V. K. Chandrasekar , M. Senthilvelan , M. Lakshmanan

Partial differential equations (PDE) often involve parameters, such as viscosity or density. An analysis of the PDE may involve considering a large range of parameter values, as occurs in uncertainty quantification, control and…

Numerical Analysis · Mathematics 2017-09-28 Max Gunzburger , Nan Jiang , Michael Schneier

We give different proofs and prove new results on the non complete solvability of some systems of complex first order p.d.e.'s, especially related to the analysis on CR manifolds.

Analysis of PDEs · Mathematics 2011-11-14 C. Denson Hill , Mauro Nacinovich

In this paper, a class of non-Markovian forward-backward doubly stochastic systems is studied. By using the technique of functional It\^o (or path-dependent) calculus, the relationship between the systems and related path-dependent…

Probability · Mathematics 2022-06-14 Yufeng Shi , Jiaqiang Wen , Jie Xiong

We develop a one step matrix method in order to obtain approximate solutions of first order systems and non-linear ordinary differential equations, reducible to first order systems. We find a sequence of such solutions that converge to the…

Numerical Analysis · Mathematics 2021-07-28 J. J. Alvarez-Sanchez , M. Gadella , L. P. Lara

In this paper, we introduce a general constructive method to compute solutions of initial value problems of semilinear parabolic partial differential equations on hyper-rectangular domains via semigroup theory and computer-assisted proofs.…

Analysis of PDEs · Mathematics 2025-01-22 Gabriel William Duchesne , Jean-Philippe Lessard , Akitoshi Takayasu

We introduce a new class of nonlinear Stochastic Differential Equations in the sense of McKean, related to non conservative nonlinear Partial Differential equations (PDEs). We discuss existence and uniqueness pathwise and in law under…

Probability · Mathematics 2015-04-16 Anthony Lecavil , Nadia Oudjane , Francesco Russo

Nonlinear systems of partial differential equations (PDEs) may permit several distinct solutions. The typical current approach to finding distinct solutions is to start Newton's method with many different initial guesses, hoping to find…

Numerical Analysis · Mathematics 2015-07-03 Patrick E. Farrell , Ásgeir Birkisson , Simon W. Funke

We are interested in the numerical solution of coupled nonlinear partial differential equations (PDEs) in two and three dimensions. Under certain assumptions on the domain, we take advantage of the Kronecker structure arising in standard…

Numerical Analysis · Mathematics 2021-07-21 Gerhard Kirsten

We tersely review a recently introduced technique to identify systems of two nonlinearly-coupled Ordinary Di{\S}erential Equations (ODEs) solvable by algebraic operations; and we report some specifc examples of this kind, namely systems of…

Mathematical Physics · Physics 2020-01-08 Francesco Calogero , Farrin Payandeh

First order optimization algorithms play a major role in large scale machine learning. A new class of methods, called adaptive algorithms, were recently introduced to adjust iteratively the learning rate for each coordinate. Despite great…

Machine Learning · Computer Science 2019-10-01 André Belotto da Silva , Maxime Gazeau