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Many physical problems such as Allen-Cahn flows have natural maximum principles which yield strong point-wise control of the physical solutions in terms of the boundary data, the initial conditions and the operator coefficients.…

Numerical Analysis · Mathematics 2021-07-21 Dong Li

We prove a strong maximum principle for Schr\"odinger operators defined on a class of fractal sets and their blowups without boundary. Our primary interest is in weaker regularity conditions than have previously appeared in the literature;…

Functional Analysis · Mathematics 2019-02-18 Marius V. Ionescu , Kasso A. Okoudjou , Luke G. Rogers

We extend Peng's maximum principle for semilinear stochastic partial differential equations (SPDEs) in one space-dimension with non-convex control domains and control-dependent diffusion coefficients to the case of general cost functionals…

Probability · Mathematics 2021-10-28 Wilhelm Stannat , Lukas Wessels

We show that the N-barrier maximum principle (NBMP) remains true for $n$ $(n>2)$ species. In addition, a stronger lower bound in NBMP is given by employing an improved tangent line method. As an application of NBMP, we establish a…

Analysis of PDEs · Mathematics 2016-04-12 Chiun-Chuan Chen , Li-Chang Hung , Chen-Chih Lai

This paper presents three versions of maximum principle for a stochastic optimal control problem of Markov regime-switching forward-backward stochastic differential equations with jumps (FBSDEJs). A general sufficient maximum principle for…

Optimization and Control · Mathematics 2014-10-14 Olivier Menoukeu Pamen

In this paper, we investigate the monotonicity of solutions for a nonlinear equations involving the fractional Laplacian with variable exponent. We first prove different maximum principles involving this operator. Then we employ the direct…

Analysis of PDEs · Mathematics 2024-04-03 Anouar Bahrouni , Abdelhakim Sahbani , Ariel Salort

We study one-sided nonlocal equations of the form $$\int_{x_0}^\infty\frac{u(x)-u(x_0)}{(x-x_0)^{1+\alpha}} dx=f(x_0),$$ on the real line. Notice that to compute this nonlocal operator of order $0<\alpha<1$ at a point $x_0$ we need to know…

Analysis of PDEs · Mathematics 2016-02-22 A. Bernardis , F. J. Martín-Reyes , P. R. Stinga , J. L. Torrea

In this paper, we propose the parametrized maximum principle preserving (MPP) flux limiter, originally developed in [Z. Xu, Math. Comp., (2013), in press], to the semi- Lagrangian finite difference weighted essentially non-oscillatory…

Numerical Analysis · Mathematics 2015-06-18 Tao Xiong , Jing-Mei Qiu , Zhengfu Xu , Andrew Christlieb

In this paper, we investigate the optimal control problems for stochastic differential equations (SDEs in short) of mean-field type with jump processes. The control variable is allowed to enter into both diffusion and jump terms. This…

Optimization and Control · Mathematics 2013-02-27 Mokhtar Hafayed , Syed Abbas

Maximum principles and uniform anti-maximum principles are a ubiquitous topic in PDE theory that is closely tied to the Krein--Rutman theorem and kernel estimates for resolvents. We take up a classical idea of Tak\'a\v{c} - to prove…

Analysis of PDEs · Mathematics 2024-04-12 Sahiba Arora , Jochen Glück

We obtain a family of nonlinear maximum principles for linear dissipative nonlocal operators, that are general, robust, and versatile. We use these nonlinear bounds to provide transparent proofs of global regularity for critical SQG and…

Analysis of PDEs · Mathematics 2011-10-04 Peter Constantin , Vlad Vicol

We consider a "superposition operator" obtained through the continuous superposition of operators of mixed fractional order, modulated by a signed Borel finite measure defined over the set $[0, 1]$. The relevance of this operator is rooted…

Analysis of PDEs · Mathematics 2026-04-15 Serena Dipierro , Edoardo Proietti Lippi , Caterina Sportelli , Enrico Valdinoci

In this paper, we study the relationship between maximum principle (MP) and dynamic programming principle (DPP) for stochastic recursive optimal control problem driven by $G$-Brownian motion. Under the smooth assumption for the value…

Optimization and Control · Mathematics 2022-10-12 Xiaojuan Li

We derive explicit pointwise bounds for the spatial derivative $\left| \frac{\partial V}{\partial x} \right|$ of solutions to linear parabolic PDEs with Neumann boundary conditions. The bound is fully explicit in the sense that it depends…

Probability · Mathematics 2025-12-25 C Ciccarella

Many astrophysical phenomena exhibit relativistic radiative flows. While velocities in excess of $v \sim 0.1c$ can occur in these systems, it has been common practice to approximate radiative transfer to $\cO(v/c)$. In the case of neutrino…

Astrophysics · Physics 2007-05-23 Christian Y. Cardall , Eric J. Lentz , Anthony Mezzacappa

We prove a version of the stochastic maximum principle, in the sense of Pontryagin, for the finite horizon optimal control of a stochastic partial differential equation driven by an infinite dimensional additive noise. In particular we…

Probability · Mathematics 2017-03-14 Marco Fuhrman , Carlo Orrieri

A general maximum principle is proved for optimal controls of abstract semilinear stochastic evolution equations. The control variable, as well as linear unbounded operators, acts in both drift and diffusion terms, and the control set need…

Optimization and Control · Mathematics 2013-12-30 Kai Du , Qingxin Meng

Moderate deviation principles for stochastic differential equations driven by a Poisson random measure (PRM) in finite and infinite dimensions are obtained. Proofs are based on a variational representation for expected values of positive…

Probability · Mathematics 2014-01-29 Amarjit Budhiraja , Paul Dupuis , Arnab Ganguly

This paper is concerned with the relationship between general maximum principle and dynamic programming principle for the stochastic recursive optimal control problem with jumps, where the control domain is not necessarily convex. Relations…

Optimization and Control · Mathematics 2024-06-04 Bin Wang , Jingtao Shi

The continuous dynamical system approach to deep learning is explored in order to devise alternative frameworks for training algorithms. Training is recast as a control problem and this allows us to formulate necessary optimality conditions…

Machine Learning · Computer Science 2018-06-05 Qianxiao Li , Long Chen , Cheng Tai , Weinan E