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In this article we show a robustness theorem for controlled stochastic differential equations driven by approximations of Brownian motion. Often, Brownian motion is used as an idealized model of a diffusion where approximations such as…

Optimization and Control · Mathematics 2023-12-07 Somnath Pradhan , Zachary Selk , Serdar Yüksel

We derive first-order Pontryagin optimality conditions for stochastic optimal control with deterministic controls for systems modeled by rough differential equations (RDE) driven by Gaussian rough paths. This Pontryagin Maximum Principle…

Optimization and Control · Mathematics 2025-10-07 Thomas Lew

Exploiting our previous results on higher order controlled Lagrangians in [Nonlinear Anal. {\bf 207} (2021), 112263], we derive here an analogue of the classical first order Pontryagin Maximum Principle (PMP) for cost minimising problems…

Optimization and Control · Mathematics 2023-03-17 Franco Cardin , Cristina Giannotti , Andrea Spiro

We introduce an innovative numerical technique based on convex optimization to solve a range of infinite dimensional variational problems arising from the application of the background method to fluid flows. In contrast to most existing…

Fluid Dynamics · Physics 2016-04-13 G. Fantuzzi , A. Wynn

We study a control problem where the state equation is a nonlinear partial differential equation of the calculus of variation in a bounded domain, perturbed by noise. We allow the control to act on the boundary and set stochastic boundary…

Probability · Mathematics 2025-11-26 Stefano Bonaccorsi , Adrian Zalinescu

We prove a maximum principle for the problem of optimal control for a fractional diffusion with infinite horizon. Further, we show existence of fractional backward stochastic differential equations on infinite horizon. We illustrate our…

Optimization and Control · Mathematics 2012-06-29 Sven Haadem

In this paper, we introduce and analyze a class of numerical schemes that demonstrate remarkable superiority in terms of efficiency, the preservation of positivity, energy stability, and high-order precision to solve the time-dependent…

Numerical Analysis · Mathematics 2025-07-01 Waixiang Cao , Yuzhe Qin , Minqiang Xu

Accurate derivatives are important for efficiently locally traversing and converging in quantum optimization landscapes. By deriving analytically exact control derivatives (gradient and Hessian) for unitary control tasks, we show here that…

The parabolic-elliptic Keller-Segel equation with sensitivity saturation, because of its pattern formation ability, is a challenge for numerical simulations. We provide two finite-volume schemes whose goals are to preserve, at the discrete…

Numerical Analysis · Mathematics 2018-10-30 Luís Neves de Almeida , Federica Bubba , Benoît Perthame , Camille Pouchol

This work addresses a central challenge in the numerical analysis of the cutoff spatially homogeneous Boltzmann equation: the development of rigorously justified, accurate numerical schemes. We present (i) a novel Fourier spectral method…

Numerical Analysis · Mathematics 2026-03-30 Yanzhi Gui , Ling-Bing He , Liu Liu

This paper proposes a novel approach to solving nonlinear programming problems using a sharp augmented Lagrangian method with a smoothing technique. Traditional sharp augmented Lagrangian methods are known for their effectiveness but are…

Optimization and Control · Mathematics 2024-10-07 José Luis Romero , Damián Fernandez , Germán Ariel Torres

We consider the optimal control of a PDE with random source term subject to probabilistic or almost sure state constraints. In the main theoretical result, we provide an exact formula for the Clarke subdifferential of the probability…

Optimization and Control · Mathematics 2023-11-28 Caroline Geiersbach , René Henrion , Pedro Pérez-Aros

In this paper, a maximum principle for the one-dimensional sub-diffusion equation with Atangana-Baleanu fractional derivative is formulated and proved. The proof of the maximum principle is based on an extremum principle for the…

Analysis of PDEs · Mathematics 2018-01-29 Meiirkhan Borikhanov , Mokhtar Kirane , Berikbol T. Torebek

Discrete-time robust optimal control problems generally take a min-max structure over continuous variable spaces, which can be difficult to solve in practice. In this paper, we extend the class of such problems that can be solved through a…

Optimization and Control · Mathematics 2024-04-30 Jad Wehbeh , Eric C. Kerrigan

We study the numerical solution of a Cahn-Hilliard/Allen-Cahn system with strong coupling through state and gradient dependent non-diagonal mobility matrices. A fully discrete approximation scheme in space and time is proposed which…

Numerical Analysis · Mathematics 2024-08-02 Aaron Brunk , Herbert Egger , Oliver Habrich

In this paper, the optimal control for discrete-time systems driven by fractional noises is studied. A stochastic maximum principle is obtained by introducing a backward stochastic difference equation contains both fractional noises and the…

Optimization and Control · Mathematics 2024-12-24 Yuecai Han , Yuhang Li

An important yet challenging problem in numerical linear algebra is finding a principal submatrix with maximum determinant from a given symmetric positive semidefinite matrix. This problem arises in experimental design, statistics, and…

Optimization and Control · Mathematics 2026-05-26 Hao Hu , Stefan Sremac , Hugo J. Woerdeman , Henry Wolkowicz

In this work, we establish the maximal $\ell^p$-regularity for several time stepping schemes for a fractional evolution model, which involves a fractional derivative of order $\alpha\in(0,2)$, $\alpha\neq 1$, in time. These schemes include…

Numerical Analysis · Mathematics 2017-03-30 Bangti Jin , Buyang Li , Zhi Zhou

We approximate the solution of the stationary Stokes equations with various conforming and nonconforming inf-sup stable pairs of finite element spaces on simplicial meshes. Based on each pair, we design a discretization that is…

Numerical Analysis · Mathematics 2019-02-12 Christian Kreuzer , Pietro Zanotti

In this article, we derive first-order necessary optimality conditions for a constrained optimal control problem formulated in the Wasserstein space of probability measures. To this end, we introduce a new notion of localised metric…

Optimization and Control · Mathematics 2021-04-28 Benoît Bonnet , Hélène Frankowska
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