Litcius/Paper detail

Regularity and numerical approximation of fractional elliptic differential equations on compact metric graphs

David Bolin, Mihály Kovács, Vivek Kumar, Alexandre B. Simas

2023Mathematics of Computation14 citationsDOI

Abstract

The fractional differential equation <inline-formula content-type="math/mathml"> <mml:math xmlns:mml="http://www.w3.org/1998/Math/MathML" alttext="upper L Superscript beta Baseline u equals f"> <mml:semantics> <mml:mrow> <mml:msup> <mml:mi>L</mml:mi> <mml:mi> β </mml:mi> </mml:msup> <mml:mi>u</mml:mi> <mml:mo>=</mml:mo> <mml:mi>f</mml:mi> </mml:mrow> <mml:annotation encoding="application/x-tex">L^\beta u = f</mml:annotation> </mml:semantics> </mml:math> </inline-formula> posed on a compact metric graph is considered, where <inline-formula content-type="math/mathml"> <mml:math xmlns:mml="http://www.w3.org/1998/Math/MathML" alttext="beta greater-than 0"> <mml:semantics> <mml:mrow> <mml:mi> β </mml:mi> <mml:mo>&gt;</mml:mo> <mml:mn>0</mml:mn> </mml:mrow> <mml:annotation encoding="application/x-tex">\beta &gt;0</mml:annotation> </mml:semantics> </mml:math> </inline-formula> and <inline-formula content-type="math/mathml"> <mml:math xmlns:mml="http://www.w3.org/1998/Math/MathML" alttext="upper L equals kappa squared minus nabla left-parenthesis a nabla right-parenthesis"> <mml:semantics> <mml:mrow> <mml:mi>L</mml:mi> <mml:mo>=</mml:mo> <mml:msup> <mml:mi> κ </mml:mi> <mml:mn>2</mml:mn> </mml:msup> <mml:mo> − </mml:mo> <mml:mi mathvariant="normal"> ∇ </mml:mi> <mml:mo stretchy="false">(</mml:mo> <mml:mi>a</mml:mi> <mml:mi mathvariant="normal"> ∇ </mml:mi> <mml:mo stretchy="false">)</mml:mo> </mml:mrow> <mml:annotation encoding="application/x-tex">L = \kappa ^2 - \nabla (a\nabla )</mml:annotation> </mml:semantics> </mml:math> </inline-formula> is a second-order elliptic operator equipped with certain vertex conditions and sufficiently smooth and positive coefficients <inline-formula content-type="math/mathml"> <mml:math xmlns:mml="http://www.w3.org/1998/Math/MathML" alttext="kappa comma a"> <mml:semantics> <mml:mrow> <mml:mi> κ </mml:mi> <mml:mo>,</mml:mo> <mml:mi>a</mml:mi> </mml:mrow> <mml:annotation encoding="application/x-tex">\kappa ,a</mml:annotation> </mml:semantics> </mml:math> </inline-formula> . We demonstrate the existence of a unique solution for a general class of vertex conditions and derive the regularity of the solution in the specific case of Kirchhoff vertex conditions. These results are extended to the stochastic setting when <inline-formula content-type="math/mathml"> <mml:math xmlns:mml="http://www.w3.org/1998/Math/MathML" alttext="f"> <mml:semantics> <mml:mi>f</mml:mi> <mml:annotation encoding="application/x-tex">f</mml:annotation> </mml:semantics> </mml:math> </inline-formula> is replaced by Gaussian white noise. For the deterministic and stochastic settings under generalized Kirchhoff vertex conditions, we propose a numerical solution based on a finite element approximation combined with a rational approximation of the fractional power <inline-formula content-type="math/mathml"> <mml:math xmlns:mml="http://www.w3.org/1998/Math/MathML" alttext="upper L Superscript negative beta"> <mml:semantics> <mml:msup> <mml:mi>L</mml:mi> <mml:mrow class="MJX-TeXAtom-ORD"> <mml:mo> − </mml:mo> <mml:mi> β </mml:mi> </mml:mrow> </mml:msup> <mml:annotation encoding="application/x-tex">L^{-\beta }</mml:annotation> </mml:semantics> </mml:math> </inline-formula> . For the resulting approximation, the strong error is analyzed in the deterministic case, and the strong mean squared error as well as the <inline-formula content-type="math/mathml"> <mml:math xmlns:mml="http://www.w3.org/1998/Math/MathML" alttext="upper L 2 left-parenthesis normal upper Gamma times normal upper Gamma right-parenthesis"> <mml:semantics> <mml:mrow> <mml:msub> <mml:mi>L</mml:mi> <mml:mn>2</mml:mn> </mml:msub> <mml:mo stretchy="false">(</mml:mo> <mml:mi mathvariant="normal"> Γ </mml:mi> <mml:mo> × </mml:mo> <mml:mi mathvariant="normal"> Γ </mml:mi> <mml:mo stretchy="false">)</mml:mo> </mml:mrow> <mml:annotation encoding="application/x-tex">L_2(\Gamma \times \Gamma )</mml:annotation> </mml:semantics> </mml:math> </inline-formula> -error of the covariance function of the solution are analyzed in the stochastic setting. Explicit rates of convergences are derived for all cases. Numerical experiments for <inline-formula content-type="math/mathml"> <mml:math xmlns:mml="http://www.w3.org/1998/Math/MathML" alttext="upper L equals kappa squared minus normal upper Delta comma kappa greater-than 0"> <mml:semantics> <mml:mrow class="MJX-TeXAtom-ORD"> <mml:mi>L</mml:mi> <mml:mo>=</mml:mo> <mml:msup> <mml:mi> κ </mml:mi> <mml:mn>2</mml:mn> </mml:msup> <mml:mo> − </mml:mo> <mml:mi mathvariant="normal"> Δ </mml:mi> <mml:mo>,</mml:mo> <mml:mi> κ </mml:mi> <mml:mo>&gt;</mml:mo> <mml:mn>0</mml:mn> </mml:mrow> <mml:annotation encoding="application/x-tex">{L = \kappa ^2 - \Delta , \kappa &gt;0}</mml:annotation> </mml:semantics> </mml:math> </inline-formula> are performed to illustrate the results.

Topics & Concepts

AlgorithmArtificial intelligenceComputer scienceDifferential Equations and Boundary ProblemsDifferential Equations and Numerical MethodsAdvanced Mathematical Modeling in Engineering