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Juan Pablo Borthagaray

Publications and source records attributed to Juan Pablo Borthagaray.

At least 19 recordsLinked to original sources

Finite element approximation for the Bessel $(p,s)$-Laplacian

We study the finite element approximation of the Dirichlet problem for the Bessel $(p,s)$-Laplacian, $\operatorname{div}^{s} \left(|\nabla^{s} u|^{p-2}\nabla^{s} u\right)$, built from the Riesz fractional gradient $\nabla^s$ and posed on the Bessel potential space $X^{s,p}$, obtained by complex interpolation between $L^p$ and $W^{1,p}$. For $p = 2$ this operator reduces to the fractional Laplacian, while for $p \neq 2$ it differs from the fractional $p$-Laplacian arising from real interpolation. Since a direct Galerkin discretization requires reassembling a dense stiffness matrix at every nonlinear iteration, we propose an augmented Lagrangian formulation based on the projected fractional gradient $B_h = \mathbfΠ_h \nabla^s$, in which the only dense matrix is assembled once and the nonlinearity decouples elementwise. We analyze the resulting consistency error, establish a priori convergence rates in $X^{s,p}$, conditional on a discrete inf-sup condition for the augmented Lagrangian scheme, and present numerical experiments that illustrate the convergence of the method and its ability to deal with degenerate and strongly nonlinear problems.

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Besov regularity of solutions to the Dirichlet problem for the Bessel $(p,s)$-Laplacian

We study the Dirichlet problem for a class of fractional $p$-Laplacian operators of order $s \in (0,1)$ defined through the Riesz fractional gradient, which differs fundamentally from the standard fractional $p$-Laplacian. Our analysis combines the framework of Lions-Calderón spaces, Besov embeddings, and an adaptation of Nirenberg's difference quotient method, originally developed by Savaré, to the fractional Riesz setting. As a main result, we establish global Besov regularity estimates for weak solutions. Concretely, in the superquadratic regime $p \geq 2$, we prove $u \in \dot{B}_{p,\infty}^{s+1/p}(Ω)$ for $s \in [\frac{1}{p'},1)$, and $u \in \dot{B}_{p,\infty}^{s+\frac{s}{p-1}}(Ω)$ for $s \in (0,\frac{1}{p'})$. In the subquadratic case $1<p<2$, we show $u \in \dot{B}_{p,\infty}^{s+1/2}(Ω)$ for $s \in [\frac{1}{2},1)$, and $u \in \dot{B}_{p,\infty}^{2s}(Ω)$ for $s \in (0,\frac12)$, with quantitative bounds depending on the source data.

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A mixed formulation for the fractional Poisson problem

The mixed formulation of the classical Poisson problem introduces the flux as an additional variable, leading to a system of coupled equations. Using fractional calculus identities, in this work we explore a mixed formulation of the fractional Poisson problem and establish its well-posedness. Since a direct discretization of this problem appears to be out of reach, we adapt a stabilized approach by Hughes and Masud, which yields a coercive and well-posed formulation. The coercivity ensures the stability of any conforming finite element discretization. We further prove the convergence of this discretization, derive convergence rates, and discuss implementation aspects. Finally, we present numerical experiments that highlight both the importance of stabilization and the accuracy of our theoretical results.

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A deep first-order system least squares method for the obstacle problem

We propose a deep learning approach to the obstacle problem inspired by the first-order system least-squares (FOSLS) framework. This method reformulates the problem as a convex minimization task; by simultaneously approximating the solution, gradient, and Lagrange multiplier, our approach provides a flexible, mesh-free alternative that scales efficiently to high-dimensional settings. Key theoretical contributions include the coercivity and local Lipschitz continuity of the proposed least-squares functional, along with convergence guarantees via $Γ$-convergence theory under mild regularity assumptions. Numerical experiments in dimensions up to 20 demonstrate the method's robustness and scalability, even on non-Lipschitz domains.

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On some coupled local and nonlocal diffusion models

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.

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Monotone two-scale methods for a class of integrodifferential operators and applications

We develop a monotone, two-scale discretization for a class of integrodifferential operators of order $2s$, $s \in (0,1)$. We apply it to develop numerical schemes, and derive pointwise convergence rates, for linear and obstacle problems governed by such operators. As applications of the monotonicity, we provide error estimates for free boundaries and a convergent numerical scheme for a concave fully nonlinear, nonlocal, problem.

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Quasi-linear fractional-order operators in Lipschitz domains

We prove Besov boundary regularity for solutions of the homogeneous Dirichlet problem for fractional-order quasi-linear operators with variable coefficients on Lipschitz domains $Ω$ of $\mathbb{R}^d$. Our estimates are consistent with the boundary behavior of solutions on smooth domains and apply to fractional $p$-Laplacians and operators with finite horizon. The proof exploits the underlying variational structure and uses a new and flexible local translation operator. We further apply these regularity estimates to derive novel error estimates for finite element approximations of fractional $p$-Laplacians and present several simulations that reveal the boundary behavior of solutions.

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Local energy estimates for the fractional Laplacian

The integral fractional Laplacian of order $s \in (0,1)$ is a nonlocal operator. It is known that solutions to the Dirichlet problem involving such an operator exhibit an algebraic boundary singularity regardless of the domain regularity. This, in turn, deteriorates the global regularity of solutions and as a result the global convergence rate of the numerical solutions. For finite element discretizations, we derive local error estimates in the $H^s$-seminorm and show optimal convergence rates in the interior of the domain by only assuming meshes to be shape-regular. These estimates quantify the fact that the reduced approximation error is concentrated near the boundary of the domain. We illustrate our theoretical results with several numerical examples.

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Finite element approximation of fractional Neumann problems

In this paper we consider approximations of Neumann problems for the integral fractional Laplacian by continuous, piecewise linear finite elements. We analyze the weak formulation of such problems, including their well-posedness and asymptotic behavior of solutions. We address the convergence of the finite element discretizations and discuss the implementation of the method. Finally, we present several numerical experiments in one- and two-dimensional domains that illustrate the method's performance as well as certain properties of solutions.

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Constructive approximation on graded meshes for the integral fractional Laplacian

We consider the homogeneous Dirichlet problem for the integral fractional Laplacian $(-Δ)^s$. We prove optimal Sobolev regularity estimates in Lipschitz domains provided the solution is $C^s$ up to the boundary. We present the construction of graded bisection meshes by a greedy algorithm and derive quasi-optimal convergence rates for approximations to the solution of such a problem by continuous piecewise linear functions. The nonlinear Sobolev scale dictates the relation between regularity and approximability.

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Besov regularity for the Dirichlet integral fractional Laplacian in Lipschitz domains

We prove Besov regularity estimates for the solution of the Dirichlet problem involving the integral fractional Laplacian of order $s$ in bounded Lipschitz domains $Ω$: \[ \begin{aligned} \|u\|_{\dot{B}^{s+r}_{2,\infty}(Ω)} \le C \|f\|_{L^2(Ω)}, & \quad r = \min\{s,1/2\}, & \quad \mbox{if } s \neq 1/2, \\ \|u\|_{\dot{B}^{1-ε}_{2,\infty}(Ω)} \le C \|f\|_{L^2(Ω)}, & \quad ε\in (0,1), & \quad \mbox{if } s = 1/2, \end{aligned} \] with explicit dependence of $C$ on $s$ and $ε$. These estimates are consistent with the regularity on smooth domains and show that there is no loss of regularity due to Lipschitz boundaries. The proof uses elementary ingredients, such as the variational structure of the problem and the difference quotient technique.

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Fractional Elliptic Problems on Lipschitz Domains: Regularity and Approximation

This survey hinges on the interplay between regularity and approximation for linear and quasi-linear fractional elliptic problems on Lipschitz domains. For the linear Dirichlet integral Laplacian, after briefly recalling Hölder regularity and applications, we discuss novel optimal shift theorems in Besov spaces and their Sobolev counterparts. These results extend to problems with finite horizon and are instrumental for the subsequent error analysis. Moreover, we dwell on extensions of Besov regularity to the fractional $p$-Laplacian, and review the regularity of fractional minimal graphs and stickiness. We discretize these problems using continuous piecewise linear finite elements and derive global and local error estimates for linear problems, thereby improving some existing error estimates for both quasi-uniform and graded meshes. We also present a BPX preconditioner which turns out to be robust with respect to both the fractional order and the number of levels. We conclude with the discretization of fractional quasi-linear problems and their error analysis. We illustrate the theory with several illuminating numerical experiments.

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A deep first-order system least squares method for solving elliptic PDEs

We propose a First-Order System Least Squares (FOSLS) method based on deep-learning for numerically solving second-order elliptic PDEs. The method we propose is capable of dealing with either variational and non-variational problems, and because of its meshless nature, it can also deal with problems posed in high-dimensional domains. We prove the $Γ$-convergence of the neural network approximation towards the solution of the continuous problem, and extend the convergence proof to some well-known related methods. Finally, we present several numerical examples illustrating the performance of our discretization.

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Robust BPX Preconditioner for Fractional Laplacians on Bounded Lipschitz Domains

We propose and analyze a robust BPX preconditioner for the integral fractional Laplacian on bounded Lipschitz domains. For either quasi-uniform grids or graded bisection grids, we show that the condition numbers of the resulting systems remain uniformly bounded with respect to both the number of levels and the fractional power. The results apply also to the spectral and censored fractional Laplacians.

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Finite element algorithms for nonlocal minimal graphs

We discuss computational and qualitative aspects of the fractional Plateau and the prescribed fractional mean curvature problems on bounded domains subject to exterior data being a subgraph. We recast these problems in terms of energy minimization, and we discretize the latter with piecewise linear finite elements. For the computation of the discrete solutions, we propose and study a gradient flow and a Newton scheme, and we quantify the effect of Dirichlet data truncation. We also present a wide variety of numerical experiments that illustrate qualitative and quantitative features of fractional minimal graphs and the associated discrete problems.

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Finite element discretizations of nonlocal minimal graphs: convergence

In this paper, we propose and analyze a finite element discretization for the computation of fractional minimal graphs of order~$s \in (0,1/2)$ on a bounded domain $Ω$. Such a Plateau problem of order $s$ can be reinterpreted as a Dirichlet problem for a nonlocal, nonlinear, degenerate operator of order $s + 1/2$. We prove that our numerical scheme converges in $W^{2r}_1(Ω)$ for all $r<s$, where $W^{2s}_1(Ω)$ is closely related to the natural energy space. Moreover, we introduce a geometric notion of error that, for any pair of $H^1$ functions, in the limit $s \to 1/2$ recovers a weighted $L^2$-discrepancy between the normal vectors to their graphs. We derive error bounds with respect to this novel geometric quantity as well. In spite of performing approximations with continuous, piecewise linear, Lagrangian finite elements, the so-called {\em stickiness} phenomenon becomes apparent in the numerical experiments we present.

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The $\mathbf{Q}$-tensor Model with Uniaxial Constraint

This chapter is about the modeling of nematic liquid crystals (LCs) and their numerical simulation. We begin with an overview of the basic physics of LCs and discuss some of their many applications. Next, we delve into the modeling arguments needed to obtain macroscopic order parameters which can be used to formulate a continuum model. We then survey different continuum descriptions, namely the Oseen-Frank, Ericksen, and Landau-deGennes ($\mathbf{Q}$-tensor) models, which essentially model the LC material like an anisotropic elastic material. In particular, we review the mathematical theory underlying the three different continuum models and highlight the different trade-offs of using these models. Next, we consider the numerical simulation of these models with a survey of various methods, with a focus on the Ericksen model. We then show how techniques from the Ericksen model can be combined with the Landau-deGennes model to yield a $\mathbf{Q}$-tensor model that exactly enforces uniaxiality, which is relevant for modeling many nematic LC systems. This is followed by an in-depth numerical analysis, using tools from $Γ$-convergence, to justify our discrete method. We also show several numerical experiments and comparisons with the standard Landau-deGennes model.

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A structure-preserving FEM for the uniaxially constrained $\mathbf{Q}$-tensor model of nematic liquid crystals

We consider the one-constant Landau - de Gennes model for nematic liquid crystals. The order parameter is a traceless tensor field $\mathbf{Q}$, which is constrained to be uniaxial: $\mathbf{Q} = s (\mathbf{n}\otimes\mathbf{n} - d^{-1} \mathbf{I})$ where $\mathbf{n}$ is a director field, $s\in\mathbb{R}$ is the degree of orientation, and $d\ge2$ is the dimension. Building on similarities with the one-constant Ericksen energy, we propose a structure-preserving finite element method for the computation of equilibrium configurations. We prove stability and consistency of the method without regularization, and $Γ$-convergence of the discrete energies towards the continuous one as the mesh size goes to zero. We design an alternating direction gradient flow algorithm for the solution of the discrete problems, and we show that such a scheme decreases the energy monotonically. Finally, we illustrate the method's capabilities by presenting some numerical simulations in two and three dimensions including non-orientable line fields.

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