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We describe an efficient domain decomposition-based framework for nonlinear multiscale PDE problems. The framework is inspired by manifold learning techniques and exploits the tangent spaces spanned by the nearest neighbors to compress…

Numerical Analysis · Mathematics 2021-11-10 Shi Chen , Qin Li , Jianfeng Lu , Stephen J. Wright

Employing two distinct types of regularization terms, we propose two regularized extragradient methods for solving equilibrium problems on Hadamard manifolds. The sequences generated by these extragradient algorithms converge to a solution…

Optimization and Control · Mathematics 2026-01-06 Shikher Sharmaa , Pankaj Gautam , Simeon Reich

For a linear nonvariational operator structured on smooth H\"ormander's vector fields, with H\"older continuous coefficients, we prove a regularity result in the spaces of H\"older functions. We deduce an analogous regularity result for…

Analysis of PDEs · Mathematics 2013-04-19 Marco Bramanti , Maria Stella Fanciullo

This paper is devoted to order-one explicit approximations of random periodic solutions to multiplicative noise driven stochastic differential equations (SDEs) with non-globally Lipschitz coefficients. The existence of the random periodic…

Probability · Mathematics 2025-01-06 Yujia Guo , Xiaojie Wang , Yue Wu

The paper proves Liouville-type results for stable solutions of semilinear elliptic PDEs with convex nonlinearity, posed on the entire Euclidean space. Extensions to solutions which are stable outside a compact set are also presented.

Analysis of PDEs · Mathematics 2008-06-17 Louis Dupaigne , Alberto Farina

The compact explicit expressions for formal exact operator solutions to Cauchy problem for sufficiently general systems of nonlinear differential equations (ODEs and PDEs) in the form of chronological operator exponents are given. The…

Mathematical Physics · Physics 2009-10-21 Yu. N. Kosovtsov

Reduced-order models of time-dependent partial differential equations (PDEs) where the solution is assumed as a linear combination of prescribed modes are rooted in a well-developed theory. However, more general models where the reduced…

Analysis of PDEs · Mathematics 2021-09-30 William Anderson , Mohammad Farazmand

A general method for solving nonlinear ill-posed problems is developed. The method consists of solving a Cauchy problem with a regularized operator and proving that the solution of this problem tends, as time grows, to a solution of the…

Mathematical Physics · Physics 2007-05-23 R. Airapetyan , A. G. Ramm , A. Smirnova

We study a class of linear parabolic path-dependent PDEs (PPDEs) defined on the space of c\`adl\`ag paths $x \in D([0,T])$, in which the coefficient functions at time $t$ depend on $x(t)$ and $\int_{0}^{t}x(s)dA_{s}$, for some…

Probability · Mathematics 2023-10-09 Bruno Bouchard , Xiaolu Tan

In this article we study the long-time behaviour of a system of nonlinear Partial Differential Equations (PDEs) modelling the motion of incompressible, isothermal and conducting modified bipolar fluids in presence of magnetic field. We…

Analysis of PDEs · Mathematics 2015-07-06 Paul Andre Razafimandimby

We combine the parameterization method for invariant manifolds with the finite element method for elliptic PDEs,to obtain a new computational framework for high order approximation of invariant manifolds attached to unstable equilibrium…

Dynamical Systems · Mathematics 2022-03-08 Jorge Gonzalez , J. D Mireles-James , Necibe Tuncer

This paper is concerned with developing accurate and efficient discontinuous Galerkin methods for fully nonlinear second order elliptic and parabolic partial differential equations (PDEs) in the case of one spatial dimension. The primary…

Numerical Analysis · Mathematics 2012-12-05 Xiaobing Feng , Thomas Lewis

This work extends the paradigm of evolutional deep neural networks (EDNNs) to solving parametric time-dependent partial differential equations (PDEs) on domains with geometric structure. By introducing positional embeddings based on…

Numerical Analysis · Mathematics 2023-08-08 Mariella Kast , Jan S Hesthaven

In this paper, we design and analyze a Hybrid-High Order (HHO) approximation for a class of quasilinear elliptic problems of nonmonotone type. The proposed method has several advantages, for instance, it supports arbitrary order of…

Numerical Analysis · Mathematics 2021-11-01 Thirupathi Gudi , Gouranga Mallik , Tamal Pramanick

The two-matrix model can be solved by introducing bi-orthogonal polynomials. In the case the potentials in the measure are polynomials, finite sequences of bi-orthogonal polynomials (called "windows") satisfy polynomial ODEs as well as…

Exactly Solvable and Integrable Systems · Physics 2015-06-26 M. Bertola , B. Eynard

In this paper, we establish the second order estimates of solutions to the first initial-boundary value problem for general Hessian type fully nonlinear parabolic equations on Riemannian manifolds. The techniques used in this article can…

Analysis of PDEs · Mathematics 2015-02-14 Heming Jiao

In this paper, we prove that sufficiently regular solutions of any quasilinear PDE can be approximated by solutions of systems of N distinguishable particles, to within 1/ ln(N ). This intruiguing result is related to recent developments in…

Analysis of PDEs · Mathematics 2025-01-22 Thierry Paul , Emmanuel Trélat

The methodology of the Riemann-Hilbert (RH) factorisation approach for Lax-pair isospectral deformations is used to derive, in the solitonless sector, the leading-order asymptotics as $t \to \pm \infty$ $(x/t \sim \mathcal{O}(1))$ of…

Exactly Solvable and Integrable Systems · Physics 2007-05-23 A. H. Vartanian

The generalized Hastings-McLeod solutions to the inhomogeneous Painlev\'{e}-II equation arise in multi-critical unitary random matrix ensembles, the chiral two-matrix model for rectangular matrices, non-intersecting squared Bessel paths,…

Mathematical Physics · Physics 2024-04-15 Kurt Schmidt , Robert Buckingham

Probabilistic solvers for ordinary differential equations (ODEs) provide efficient quantification of numerical uncertainty associated with simulation of dynamical systems. Their convergence rates have been established by a growing body of…

Machine Learning · Statistics 2020-12-21 Nicholas Krämer , Philipp Hennig