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Finite element approximations of Dirichlet boundary control problems governed by parabolic PDEs on convex polygonal domains are studied in this paper. The existence of a unique solution to optimal control problems is guaranteed based on…

Optimization and Control · Mathematics 2014-10-02 Wei Gong , Michael Hinze , Zhaojie Zhou

We apply a continuous data assimilation method to the Navier-Stokes-Fourier system governing the evolution of a compressible, rotating and thermally driven fluid. A rigorous proof of the tracking property is given in the asymptotic regime…

Analysis of PDEs · Mathematics 2025-10-24 Eduard Feireisl , Wladimir Neves

Diffusion and flow-matching have emerged as powerful methodologies for generative modeling, with remarkable success in capturing complex data distributions and enabling flexible guidance at inference time. Many downstream applications,…

Machine Learning · Computer Science 2026-04-28 Zeyang Li , Kaveh Alim , Navid Azizan

We consider a nonlinear control system with vector-valued measures as controls and with dynamics depending on time delayed states. First, we introduce a notion of discontinuous, bounded variation solution associated with this system and…

Optimization and Control · Mathematics 2024-09-02 Giovanni Fusco , Monica Motta , Richard Vinter

For shape optimization problems, governed by elliptic equations with Dirichlet boundary condition and random coefficients, we utilize a penalization technique to get the approximate problem. We consider that uncertainties exists in the…

Optimization and Control · Mathematics 2025-08-26 Xiaowei Pang

In this paper, a quadratic optimal control problem is considered for second-order parabolic PDEs with homogeneous Dirichlet boundary conditions, in which the "point" control function (depending only on time) constitutes a source term. These…

Systems and Control · Electrical Eng. & Systems 2024-07-04 Gilberto O. Corrêa , Marlon M. López-Flores , Alexandre L. Madureira

The solution of partial differential equations (PDEs) on complex domains often presents a significant computational challenge by requiring the generation of fitted meshes. The Diffuse Domain Method (DDM) is an alternative which reformulates…

Numerical Analysis · Mathematics 2026-05-13 Luke Benfield , Andreas Dedner

This study focuses on using direct methods (first-discretize-then-optimize) to solve optimal control problems for a class of nonsmooth dynamical systems governed by differential variational inequalities (DVI), called optimal control…

Optimization and Control · Mathematics 2025-12-04 Kangyu Lin , Toshiyuki Ohtsuka

Diffuse domain methods (DDMs) have garnered significant attention for approximating solutions to partial differential equations on complex geometries. These methods implicitly represent the geometry by replacing the sharp boundary interface…

Analysis of PDEs · Mathematics 2025-04-25 Toai Luong , Tadele Mengesha , Steven M. Wise , Ming Hei Wong

In this paper, we consider the approximate controllability of partial differential equations with time derivatives of non-integer order via boundary control. We first show the unique existence of the solution under smooth boundary…

Optimization and Control · Mathematics 2015-01-07 Kenichi Fujishiro

Based upon elements of the modern Pseudoanalytic Function Theory, we analyse a new method for numerically approaching the solution of the Dirichlet boundary value problem, corresponding to the two-dimensional Electrical Impedance Equation.…

Mathematical Physics · Physics 2012-02-23 M. P. Ramirez T. , C. M. A. Robles G. , R. A. Hernandez-Becerril

In this paper, we are interested in numerical solution of some linear boundary value problems with Dirichlet boundary part, by the means of simulation of random walks. We use a probabilistic interpretation of solution $u$, assuming that the…

Probability · Mathematics 2013-04-17 Jean-Paul Morillon

Rectified Flow offers a simple and effective approach to high-quality generative modeling by learning a velocity field. However, we identify a limitation in directly modeling the velocity with an unconstrained neural network: the learned…

Machine Learning · Computer Science 2025-10-21 Xixi Hu , Runlong Liao , Keyang Xu , Bo Liu , Yeqing Li , Eugene Ie , Hongliang Fei , Qiang Liu

Flow matching has emerged as a simulation-free alternative to diffusion-based generative modeling, producing samples by solving an ODE whose time-dependent velocity field is learned along an interpolation between a simple source…

Machine Learning · Statistics 2026-04-10 Shivam Kumar , Yixin Wang , Lizhen Lin

We interpret the 4D-var data assimilation problem for a parabolic partial differential equation (PDE) in the context of optimal control and revisit the process of deriving optimality conditions for an initial control problem. This is…

Optimization and Control · Mathematics 2025-07-29 Carmen Gräßle , Jannis Marquardt

We study the numerical performance of a continuous data assimilation (downscaling) algorithm, based on ideas from feedback control theory, in the context of the two-dimensional incompressible Navier--Stokes equations. Our model problem is…

Dynamical Systems · Mathematics 2016-05-04 Masakazu Gesho , Eric Olson , Edriss S. Titi

We consider the problem of minimizing the sum of cost functions pertaining to agents over a network whose topology is captured by a directed graph (i.e., asymmetric communication). We cast the problem into the ADMM setting, via a consensus…

Optimization and Control · Mathematics 2023-04-04 Dingran Yi , Nikolaos M. Freris

The paper is devoted to the study of a new class of optimal control problems governed by discontinuous constrained differential inclusions of the sweeping type with involving the duration of the dynamic process into optimization. We develop…

Optimization and Control · Mathematics 2023-10-18 Giovanni Colombo , Boris S. Mordukhovich , Dao Nguyen , Trang Nguyen

Data assimilation (DA) solves the inverse problem of inferring initial conditions given data and a model. Here we use biophysically motivated Hodgkin-Huxley (HH) models of avian HVCI neurons, experimentally obtained recordings of these…

Neurons and Cognition · Quantitative Biology 2016-08-17 Daniel Breen , Sasha Shirman , Eve Armstrong , Nirag Kadakia , Henry Abarbanel

In this article, we provide a methodology to reconstruct high-Reynolds number turbulent mean-flows from few time-averaged measurements. A turbulent flow over a backward-facing step at Re = 28275 is considered to illustrate the potential of…

Fluid Dynamics · Physics 2020-09-23 Lucas Franceschini , Denis Sipp , Olivier Marquet