Sorry, you need to enable JavaScript to visit this website.
Share

Publications

Publications

The publications of the UMA members are listed in the unit's HAL collection: HAL collection of UMA

The publications appearing in the HAL open archive since 2025 are listed below by year.

2026

  • Waves within a network of slowly time-modulated interfaces: time-dependent effective properties, reciprocity and high-order dispersion
    • Darche Michaël
    • Assier Raphaël
    • Guenneau Sebastien
    • Lombard Bruno
    • Touboul Marie
    , 2026. We consider wave propagation through a 1D periodic network of slowly time-modulated interfaces. Each interface is modelled by time-dependent spring-mass jump conditions, where mass and rigidity interface parameters are modulated in time. Low-frequency homogenisation yields a leading-order model described by an effective time-dependent wave equation, i.e. a wave equation with effective mass density and Young's modulus which are homogeneous in space but depend on time. This means that time-dependent bulk effective properties can be created by an array where only interfaces are modulated in time. The occurrence of k-gaps in case of a periodic modulation is also analysed. Second-order homogenisation is then performed and leads to an effective model which is reciprocal but encapsulates higher-order dispersive effects. These findings and the limitations of the models are illustrated through time-domain simulations.
  • A neural operator framework for solving inverse scattering problems
    • Chenu Victor
    • Haddar Houssem
    • Montanelli Hadrien
    , 2026. We present a neural operator framework for solving inverse scattering problems. A neural operator produces a preliminary indicator function for the scatterer, which, after appropriate rescaling, is used as a regularization parameter within the Linear Sampling Method to validate the initial reconstruction. The neural operator is implemented as a DeepONet with a fixed radial-basis-function trunk, while the noise level required for rescaling is estimated using a dedicated neural network. A neural tangent kernel analysis guides the architectural design, reducing the network tuning to a single discretization parameter, adjustable according to the wavelength. Two-dimensional numerical experiments demonstrate the method's effectiveness, with a Python toolbox provided for reproducibility.
  • Degenerate McKean-Vlasov equations with drift in anisotropic negative Besov spaces
    • Issoglio Elena
    • Pagliarani Stefano
    • Russo Francesco
    • Trevisani Davide
    , 2024. The paper is concerned with a McKean-Vlasov type SDE with drift in anisotropic Besov spaces with negative regularity and with degenerate diffusion matrix under the weak Hörmander condition. The main result is of existence and uniqueness of a solution in law for the McKean-Vlasov equation, which is formulated as a suitable martingale problem. All analytical tools needed are derived in the paper, such as the well-posedness of the Fokker-Planck and Kolmogorov PDEs with distributional drift, as well as continuity dependence on the coefficients. The solutions to these PDEs naturally live in anisotropic Besov spaces, for which we developed suitable analytical inequalities, such as Schauder estimates.
  • Accelerating the Method of Reflections with Domain Decomposition techniques for Boundary Integral Equations in Multiple Scattering
    • Chaillat Stéphanie
    • Darbas Marion
    • Gander Martin J
    • Halpern Laurence
    , 2026. The Method of Reflections was historically introduced to obtain approximate solu-tions as series expansions for the motion of particles in suspension. It can however equally well be used for solving multiple scattering problems numerically. We show for Helmholtz multiple scattering problems that the Method of Reflections, whether applied in its alternating or parallel version, suffers from convergence problems when scatterers are close. We use boundary integral equations to formulate the methods, and then identify them as algebraic Schwarz methods, thereby interpreting them as boundary domain decomposition techniques. This connection allows us to introduce remedies such as overlap (which can be partial, covering only the illuminating region of the obstacles) and coarse spaces from domain decomposition into the Method of Reflections. This leads to substantially accelerated variants, and also naturally makes them suitable preconditioners for GMRES. These new approaches are particularly efficient for closeby obstacles. Moreover, numerical experiments show that the number of iterations remains robust with respect to the wavenumber.
  • A comparative analysis of different carbon cap policies on the economic lot-sizing problem with remanufacturing
    • Vallecilla Andrés
    • Dávila-Gálvez Sebastián
    • Quezada Franco
    International Journal of Production Research, Taylor & Francis, 2026. <div><p>This paper investigates the implementation of carbon cap policies within a remanufacturing production system, focusing on a single-item lot-sizing problem aimed at meeting the demand for end-of-life products under four distinct carbon cap policies. Our study, motivated by the operational dynamics of ECOCITEX, a Chilean textile remanufacturing company, explores the balance between operational costs, carbon emissions, and production levels in response to environmental policies. We introduce a mixed-integer linear programming (MILP) formulation to address economic lot-sizing with considerations for both remanufacturing and carbon emissions constraints. Through extensive computational experiments, we assess the impact of various carbon emissions policies on production and emissions levels and their associated costs, finding that global and rolling-horizon policies offer the best tradeoff between emission reductions and production cost increases. This leads to more environmentally friendly production policies for remanufactured products without compromising financial sustainability. The findings underscore the importance of flexibility in environmental policies for remanufacturing operations, suggesting that stringent carbon caps, while beneficial for emission reductions, may pose challenges to demand fulfillment and cost management. For managers, this highlights the critical need for adaptive policy frameworks that support sustainable production objectives without impeding operational efficiency.</p></div>
  • State-constrained optimal control on Wasserstein spaces over Riemannian manifolds
    • Treumún Ernesto
    • Zidani Hasnaa
    , 2026. We study a state-constrained optimal control problem in Mayer form on the Wasserstein space P 2 (M ) of a complete (possibly non-compact) Riemannian manifold M . The controlled dynamics is given by a nonlocal continuity equation, where the velocity field depends on both the space variable and the evolving probability measure. In the presence of state constraints, the associated value function may fail to be continuous, which prevents a direct characterization through Hamilton-Jacobi-Bellman equations (HJB). Following a level-set approach, we introduce an auxiliary value function defined on an extended space and prove that its zero-sublevel set recovers the epigraph of the original value function. Our main result shows that this auxiliary function is the unique viscosity solution of a suitable HJB equation on P 2 (M ). To prove uniqueness, we develop a comparison principle based on directional differentiability properties of the squared Wasserstein distance. These properties are shown to hold under a geometric assumption on the underlying manifold, satisfied in particular by Cartan-Hadamard manifolds and spaces with sectional curvature bounded from below. This extends previous results obtained in the unconstrained case and in Euclidean or compact settings to the state-constrained framework on general complete Riemannian manifolds.
  • Fluid-structure Green's functions via BEM/BEM coupling for flow induced noise in arbitrary elastic geometries
    • Pacaut Louise
    • Chaillat Stéphanie
    • Mercier Jean-François
    • Serre Gilles
    , 2026. We address the challenge of efficiently simulating the noise generated by the interaction of a turbulent flow noise with complex elastic structures, a coupled fluid/structure interaction (FSI) problem. Current approaches typically separate vibro-acoustic and hydro-acoustic contributions, limiting the accuracy of hydrodynamic noise predictions. To overcome this limitation, we develop a numerical method for computing a Green's function tailored to the coupled FSI problem, enabling a monolithic prediction of the radiated noise without separating the two components. This approach not only improves the accuracy of hydrodynamic noise simulations but also significantly reduces computational costs. The Green's function is constructed using a novel integral formulation and solved numerically via a coupled fast BEM/ BEM solver.
  • Stochastic Optimal Feedforward-Feedback Control for Partially Observable Sensorimotor Systems
    • Berret Bastien
    • Jean Frédéric
    , 2026. Robust control of complex engineered and biological systems hinges on the integration of feedforward and feedback mechanisms. This is exemplified in neural motor control, where feedforward muscle co-contraction complements sensory-driven feedback corrections to ensure stable behaviors. However, deriving a general continuous-time framework to determine such optimal control policies for partially observable, stochastic, nonlinear, and high-dimensional systems remains a formidable computational challenge. Here, we introduce a framework that extends neighboring optimal control by enabling the feedforward plan to explicitly account for feedback uncertainties and latencies. Using statistical linearization, we transform the stochastic problem into an approximately equivalent deterministic optimization within a tractable, augmented state space that retains critical nonlinearities, offering both mechanistic interpretability and theoretical guarantees on approximation fidelity. We apply this framework to human neuromechanics, demonstrating that muscle co-contraction emerges as an optimal adaptation to task demands, given the characteristics of our sensorimotor system. Our results provide a computational foundation for neuromotor control and a generalizable tool for the control of nonlinear stochastic systems.
  • Asymptotic models for time-domain scattering by small particles
    • Savchuk Adrian
    , 2026. In this manuscript, we address the problem of time-dependent wave scattering by multiple small particles of arbitrary shape. To approximate the solution of the associated boundary-value problem, we derive an asymptotic model that achieves a higher convergence rate compared to existing models. Our method relies on a boundary integral formulation, semi-discretized in space using a Galerkin approach, where the main challenge lies in choosing appropriate basis functions for the Galerkin space. We show that using equilibrium densities as basis functions yields a cubic-convergent asymptotic model that ensures a priori stability in the time domain due to the coercivity properties of the single-layer boundary integral operator. Unlike the case of spheres, where entries can be computed explicitly, the generalized method requires double integration, which becomes computationally expensive as the number of particles increases. To address this, we derive a simplified model that preserves the stability and convergence properties of the original formulation, alongside a lower-order but computationally advantageous Born model, providing a rigorous theoretical error analysis for both. When the distance between obstacles decreases with the small parameter, the cubic convergence of the scattered field can no longer be guaranteed. To overcome this limitation, we derive high-order asymptotic models by enriching the basis functions in the Galerkin space to maintain accuracy even for closely clustered particles. Finally, the proposed framework is applied to more complex interactions between a large obstacle and multiple small particles, and is further extended to time-domain electromagnetic scattering by small spheres. Numerical experiments validate the theoretical stability and performance across all proposed models.
  • Metamaterials and Fluid Flows
    • Avallone Francesco
    • Bosia Federico
    • Chen Yi
    • Colombo Giada
    • Craster Richard
    • de Ponti Jacopo Maria
    • Fabbiane Nicolò
    • Haberman Michael
    • Hussein Mahmoud
    • Hwang Wontae
    • Iemma Umberto
    • Juhl Abigail
    • Kadic Muamer
    • Kotsonis Marios
    • Laude Vincent
    • Marquet Olivier
    • Mery Fabien
    • Michelis Theodoros
    • Nouh Mostafa
    • Ragni Daniele
    • Touboul Marie
    • Wegener Martin
    • Krushynska Anastasiia
    Nature Communications, Nature Publishing Group, 2026. (10.1038/s41467-026-70163-2)
    DOI : 10.1038/s41467-026-70163-2
  • Dominance Properties for Fair Electricity Supply Planning in Collective Self-Consumption
    • Jorquera-Bravo Natalia
    • Elloumi Sourour
    • Kedad-Sidhoum Safia
    • Plateau Agnès
    , 2026. <div><p>This study addresses the problem of fair electricity supply planning within collective self-consumption communities, focusing on shared distributed energy sources and a common electricity storage system. The objective is to determine an electricity supply plan that ensures a fair allocation of shared resources. We formulate the electricity supply planning problem as a mixed integer linear programming (MILP) model, subsequently reformulated into a linear programming (LP) model thanks to some dominance properties. We then propose a series of fairness measures for the allocation of green electricity and shared economic benefits, including proportional allocation and max-min fairness. We prove that the dominance properties can be extended in most of these fairness models. We conduct numerical experiments based on a real case study, as well as on a set of generated instances. The results illustrate their impact on the use of green electricity produced, resource allocation, and participant costs. They also underscore the trade-offs between achieving fairness and maintaining operational efficiency, thereby offering insights for the fair management of energy resources in self-consumption communities.</p></div>
  • On the Low Autocorrelation Binary Sequence Problem
    • Elloumi Sourour
    • Palagi Laura
    , 2026. On the Low Autocorrelation Binary Sequence Problem
  • Discretization in multilayered media with high contrasts: is it all about the boundaries?
    • Carvalho Camille
    • Chaillat Stéphanie
    • Tsogka Chrysoula
    • Cortes Elsie A
    , 2026. Wave propagation in multilayered media with high material contrasts poses significant numerical challenges, as large variations in wavenumbers lead to strong reflections and complex transmission of the incoming wave field. To address these difficulties, we employ a boundary integral formulation thereby avoiding volumetric discretization. In this framework, the accuracy of the numerical solution depends strongly on how the material interfaces are discretized. In this work, we demonstrate that standard meshing strategies based on resolving the maximum wavenumber across the domain become computationally inefficient in multilayered configurations, where high wavenumbers are confined to localized subdomains. Through a systematic study of multilayer transmission problems, we show that no simple discretization rule based on the maximum wavenumber or material contrasts emerges. Instead, the wavenumber of the background (exterior) medium plays a dominant role in determining the optimal boundary resolution. Building on these insights, we propose an adaptive approach that achieves uniform accuracy and efficient computation across multiple layers. Numerical experiments for a range of multilayer configurations demonstrate the scalability and robustness of the proposed approach.
  • Htool-DDM: A C++ library for parallel solvers and compressed linear systems.
    • Marchand Pierre
    • Tournier Pierre-Henri
    • Jolivet Pierre
    Journal of Open Source Software, Open Journals, 2026, 11 (118), pp.9279. (10.21105/joss.09279)
    DOI : 10.21105/joss.09279
  • Automated far-field sound field estimation combining robotized acoustic measurements and the boundary elements method
    • Pascal Caroline
    • Marchand Pierre
    • Chapoutot Alexandre
    • Doaré Olivier
    Acta Acustica, EDP Sciences, 2026. The identification and reconstruction of acoustic fields radiated by unknown structures is usually performed using either Sound Field Estimation or Near-field Acoustic Holography techniques. The latter turns out to be especially useful when data is only available close to the source, but information throughout the whole space is needed. Yet, the lack of amendable and efficient implementations of state-of-the-art solutions, as well as the laborious and often lengthy deployment of acoustic measurements continue to be significant obstacles to the practical application of such methods. The purpose of this work is to address both problems. First, a completely automated metrology setup is proposed, in which a robotic arm is used to gather extensive and accurately positioned acoustic data without any human intervention. The impact of the robot on acoustic pressure measurements is cautiously evaluated, and proved to remain limited below 1 kHz. The Sound Field Estimation is then tackled using the Boundary Element Method, and implemented using the FreeFEM software. Numerically simulated measurements have allowed us to assess the method accuracy, which matches theoretically expected results and proves to remain robust against positioning inaccuracies, provided that the robot is carefully calibrated. The overall solution has been successfully tested using actual robotized measurements of an unknown loudspeaker, with a reconstruction error of less than 30 %. (10.1051/aacus/2026017)
    DOI : 10.1051/aacus/2026017
  • Asymptotic analysis at any order of Helmholtz's problem in a corner with a thin layer: an algebraic approach
    • Baudet Cédric
    Asymptotic Analysis, IOS Press, 2026. We consider the Helmholtz equation in an angular sector partially covered by a homogeneous layer of small thickness, denoted ε. We propose in this work an asymptotic expansion of the solution with respect to ε at any order. This is done using matched asymptotic expansion, which consists here in introducing different asymptotic expansions of the solution in three subdomains: the vicinity of the corner, the layer and the rest of the domain. These expansions are linked through matching conditions. The presence of the corner makes these matching conditions delicate to derive because the fields have singular behaviors. Our approach is to reformulate these matching conditions purely algebraically by writing all asymptotic expansions as formal series. By using algebraic calculus we reduce the matching conditions to scalar relations linking the singular behaviors of the fields. These relations have a convolutive structure and involve some coefficients that can be computed analytically. Our asymptotic expansion is justified rigorously with error estimates. (10.1177/09217134251389983)
    DOI : 10.1177/09217134251389983
  • Variational quantum algorithms for permutation-based combinatorial problems: Optimal ansatz generation with applications to quadratic assignment problems and beyond
    • Laplace Mermoud Dylan
    • Simonetto Andrea
    • Elloumi Sourour
    Quantum, Verein zur Förderung des Open Access Publizierens in den Quantenwissenschaften, 2026, 10, pp.1998. We present a quantum variational algorithm based on a novel circuit that generates all permutations that can be spanned by one- and two-qubits permutation gates. The construction of the circuits follows from group-theoretical results, most importantly the Bruhat decomposition of the group generated by the cx gates. These circuits require a number of qubits that scale logarithmically with the permutation dimension, and are therefore employable in near-term applications. We further augment the circuits with ancilla qubits to enlarge their span, and with these we build ansatze to tackle permutation-based optimization problems such as quadratic assignment problems, and graph isomorphisms. The resulting quantum algorithm, QuPer, is competitive with respect to classical heuristics and we could simulate its behavior up to a problem with 256 variables, requiring 20 qubits. (10.22331/q-2026-02-09-1998)
    DOI : 10.22331/q-2026-02-09-1998
  • Wave propagation in the frequency regime in one-dimensional quasiperiodic media -Limiting absorption principle
    • Amenoagbadji Pierre
    • Fliss Sonia
    • Joly Patrick
    , 2026. <div><p>We study the one-dimensional Helmholtz equation with (possibly perturbed) quasiperiodic coefficients. Quasiperiodic functions are the restriction of higher dimensional periodic functions along a certain (irrational) direction. In classical settings, for real-valued frequencies, this equation is generally not well-posed: existence of solutions in L 2 is not guaranteed and uniqueness in L ∞ may fail. This is a well-known difficulty of Helmholtz equations, but it has never been addressed in the quasiperiodic case. We tackle this issue by using the limiting absorption principle, which consists in adding some imaginary part (also called absorption) to the frequency in order to make the equation well-posed in L 2 , and then defining the physically relevant solution by making the absorption tend to zero. In previous work, we introduced a definition of the solution of the equation with absorption based on Dirichlet-to-Neumann (DtN) boundary conditions. This approach offers two key advantages: it facilitates the limiting process and has a direct numerical counterpart. In this work, we first explain why the DtN boundary conditions have to be replaced by Robin-to-Robin boundary conditions to make the absorption go to zero. We then prove, under technical assumptions on the frequency, that the limiting absorption principle holds and we propose a numerical method to compute the physical solution.</p></div>
  • A theoretical and computational framework for three dimensional inverse medium scattering using the linearized low-rank structure
    • Zhou Yuyuan
    • Audibert Lorenzo
    • Meng Shixu
    • Zhang Bo
    , 2026. In this work we propose a theoretical and computational framework for solving the three dimensional inverse medium scattering problem, based on a set of data-driven basis arising from the linearized problem. This set of data-driven basis consists of generalizations of prolate spheroidal wave functions to three dimensions (3D PSWFs), the main ingredients to explore a low-rank approximation of the inverse solution. We first establish the fundamentals of the inverse scattering analysis, including regularity in a customized Sobolev space and new a priori estimate. This is followed by a computational framework showcasing computing the 3D PSWFs and the low-rank approximation of the inverse solution. These results rely heavily on the fact that the 3D PSWFs are eigenfunctions of both a restricted Fourier integral operator and a Sturm-Liouville differential operator. Furthermore we propose a Tikhonov regularization method with a customized penalty norm and a localized imaging technique to image a targeting object despite the possible presence of its surroundings. Finally various numerical examples are provided to demonstrate the potential of the proposed method.
  • Discrete FEM-BEM coupling with the Generalized Optimized Schwarz Method
    • Boisneault Antonin
    • Bonazzoli Marcella
    • Claeys Xavier
    • Marchand Pierre
    , 2026. The present contribution aims at developing a non-overlapping Domain Decomposition (DD) approach to the solution of acoustic wave propagation boundary value problems based on the Helmholtz equation, on both bounded and unbounded domains. This DD solver, called Generalized Optimized Schwarz Method (GOSM), is a substructuring method, that is, the unknowns of an iteration are associated with the subdomains interfaces. We extend the analysis presented in a previous paper of one of the author to a fully discrete setting. We do not consider only a specific set of boundary conditions, but a whole class including, e.g., Dirichlet, Neumann, and Robin conditions. Our analysis will also cover interface conditions corresponding to a Finite Element Method - Boundary Element Method (FEM-BEM) coupling. In particular, we shall focus on three classical FEM-BEM couplings, namely the Costabel, Johnson-Nédélec and Bielak-MacCamy couplings. As a remarkable outcome, the present contribution yields well-posed substructured formulations of these classical FEM-BEM couplings for wavenumbers different from classical spurious resonances. We also establish an explicit relation between the dimensions of the kernels of the initial variational formulation, the local problems and the substructured formulation. That relation especially holds for any wavenumber for the substructured formulation of Costabel FEM-BEM coupling, which allows us to prove that the latter formulation is well-posed even at spurious resonances. Besides, we introduce a systematically geometrically convergent iterative method for the Costabel FEM-BEM coupling, with estimates on the convergence speed.
  • Planning in Branch-and-Bound: Model-Based Reinforcement Learning for Exact Combinatorial Optimization
    • Strang Paul
    • Alès Zacharie
    • Bissuel Côme
    • Juan Olivier
    • Kedad-Sidhoum Safia
    • Rachelson Emmanuel
    , 2025. Mixed-Integer Linear Programming (MILP) lies at the core of many real-world combinatorial optimization (CO) problems, traditionally solved by branch-and-bound (B&amp;B). A key driver influencing B&amp;B solvers efficiency is the variable selection heuristic that guides branching decisions. Looking to move beyond static, hand-crafted heuristics, recent work has explored adapting traditional reinforcement learning (RL) algorithms to the B&amp;B setting, aiming to learn branching strategies tailored to specific MILP distributions. In parallel, RL agents have achieved remarkable success in board games, a very specific type of combinatorial problems, by leveraging environment simulators to plan via Monte Carlo Tree Search (MCTS). Building on these developments, we introduce Plan-and-Branch-and-Bound (PlanB&amp;B), a model-based reinforcement learning (MBRL) agent that leverages a learned internal model of the B&amp;B dynamics to discover improved branching strategies. Computational experiments empirically validate our approach, with our MBRL branching agent outperforming previous state-of-the-art RL methods across four standard MILP benchmarks.
  • Early-Reverberation Imaging Functions for Bounded Elastic Domains
    • Ducasse Eric
    • Rodriguez Samuel
    • Bonnet Marc
    Acta Acustica, EDP Sciences, 2026, 10, pp.2. For the ultrasonic inspection of bounded elastic structures, finite-duration imaging functions are derived in the Fourier-Laplace domain.The signals involved are exponentially windowed, so that early reflections are taken into account more strongly than later ones in the imaging methodology.Applying classical approaches to the general case of anisotropic elasticity, we express the Fréchet derivatives of the relevant data-misfit functional with respect to arbitrary perturbations of the mass density and stiffnesses in terms of forward and adjoint solutions.Their definitions incorporate the exponentially decaying weighting. The proposed finite-duration imaging functions are then defined on that basis.As some areas of the structure are less insonified than others, it is necessary to define normalized imaging functions to compensate for these variations.Our approach in particular aims to overcome the difficulty of dealing with bounded domains containing defects not located in direct line of sight from the transducers and measured signals of long duration.For this initiation work, we demonstate the potential of the proposed method on a two-dimensional test case featuring the imaging of mass and elastic stiffness variations in a region of a bounded isotropic medium that is not directly visible from the transducers. (10.1051/aacus/2025069)
    DOI : 10.1051/aacus/2025069
  • A general-purpose global regularization method for 3D volume integral operators
    • Anderson Thomas G.
    • Bonnet Marc
    • Faria Luiz M.
    • Pérez-Arancibia Carlos
    , 2026. Singular volume integral operators associated with constant-coefficient partial differential operators extend the applicability of potential theory to inhomogeneous problems, for example arising from nonlinearities or variable coefficients. Typically the PDE kernels in these operators give rise to singularities at all O(1/h^3 ) volume discretization/evaluation points in a mesh of characteristic size h, while the slowly-decaying nature of such kernels give rise to long-range interactions that require coupling to fast summation algorithms. The presented method uses Green's identities to regularize a wide variety of both scalar-valued and vector-valued volume integral operators by use of a certain regularizing volume density interpolant. The analysis shows how the regularizing effect of the interpolant is global in the sense that the interpolation quality increases in an exactly compensatory fashion as the distance to the Green's function singularity decreases. High-order convergence estimates with tabulated simplex quadratures are established, including with exact representation of curved domains.
  • Exploring low-rank structure for an inverse scattering problem with far-field data
    • Zhou Yuyuan
    • Audibert Lorenzo
    • Meng Shixu
    • Zhang Bo
    SIAM Journal on Applied Mathematics, Society for Industrial and Applied Mathematics, 2026, 86 (1), pp.160-186. The inverse scattering problem exhibits an inherent low-rank structure due to its ill-posed nature; however developing low-rank structures for the inverse scattering problem remains challenging. In this work, we introduce a novel low-rank structure tailored for solving the inverse scattering problem. The particular low-rank structure is given by the generalized prolate spheroidal wave functions, computed stably and accurately via a Sturm-Liouville problem. We first process the far-field data to obtain a post-processed data set within a disk domain. Subsequently, the post-processed data are projected onto a low-rank space given by the low-rank structure. The unknown is approximately solved in this low-rank space, by dropping higher-order terms. The low-rank structure leads to a H\"{o}lder-logarithmic type stability estimate for arbitrary unknown functions, and a Lipschitz stability estimate for unknowns belonging to a finite dimensional low-rank space. Various numerical experiments are conducted to validate its performance, encompassing assessments of resolution capability, robustness against randomly added noise and modeling errors, and demonstration of increasing stability. (10.1137/24M1663922)
    DOI : 10.1137/24M1663922
  • On some coupled local and nonlocal diffusion models
    • Borthagaray Juan Pablo
    • Ciarlet Patrick
    Mathematical Models and Methods in Applied Sciences, World Scientific Publishing, 2026. We study problems in which a local model is coupled with a nonlocal one. We propose two energies: both of them are based on the same classical weighted $H^1$-semi norm to model the local part, while two different weighted $H^s$-semi norms, with $s \in (0, 1)$, are used to model the nonlocal part. The corresponding strong formulations are derived. In doing so, one needs to develop some technical tools, such as suitable integration by parts formulas for operators with variable diffusivity, and one also needs to study the mapping properties of the Neumann operators that arise. In contrast to problems coupling purely local models, in which one requires transmission conditions on the interface between the subdomains, the presence of a nonlocal operator may give rise to nonlocal fluxes. These nonlocal fluxes may enter the problem as a source term, thereby changing its structure. Finally, we focus on a specific problem, that we consider most relevant, and study regularity of solutions and finite element discretizations. We provide numerical experiments to illustrate the most salient features of the models. (10.1142/S0218202526500442)
    DOI : 10.1142/S0218202526500442