A multiscale approach to the stationary Ginzburg–Landau equations of superconductivity

Abstract In this work, we study the numerical approximation of minimizers of the Ginzburg–Landau free energy, a common model to describe the behavior of superconductors under magnetic fields. The unknowns are the order parameter, which characterizes the density of superconducting charge carriers, and the magnetic vector potential, which allows to deduce the magnetic field that penetrates the superconductor. Physically important and numerically challenging are especially settings which involve lattices of quantized vortices which can be formed in materials with a large Ginzburg–Landau parameter $$\kappa $$ <mml:math xmlns:mml="http://www.w3.org/1998/Math/MathML"> <mml:mi>κ</mml:mi> </mml:math> . In particular, $$\kappa $$ <mml:math xmlns:mml="http://www.w3.org/1998/Math/MathML"> <mml:mi>κ</mml:mi> </mml:math> introduces a severe mesh resolution condition for numerical approximations. In order to reduce these computational restrictions, we investigate a particular discretization which is based on mixed meshes where we apply a Lagrange finite element approach for the vector potential and a localized orthogonal decomposition (LOD) approach for the order parameter. We justify the proposed method by a rigorous a-priori error analysis (in $$L^2$$ <mml:math xmlns:mml="http://www.w3.org/1998/Math/MathML"> <mml:msup> <mml:mi>L</mml:mi> <mml:mn>2</mml:mn> </mml:msup> </mml:math> and $$H^1$$ <mml:math xmlns:mml="http://www.w3.org/1998/Math/MathML"> <mml:msup> <mml:mi>H</mml:mi> <mml:mn>1</mml:mn> </mml:msup> </mml:math> ) in which we keep track of the influence of $$\kappa $$ <mml:math xmlns:mml="http://www.w3.org/1998/Math/MathML"> <mml:mi>κ</mml:mi> </mml:math> in the main error contributions. This allows us to conclude $$\kappa $$ <mml:math xmlns:mml="http://www.w3.org/1998/Math/MathML"> <mml:mi>κ</mml:mi> </mml:math> -dependent resolution conditions for the various meshes and which only impose moderate practical constraints compared to a conventional finite element discretization. While our results only provide information on the approximability of the minimizers, we conclude by further proposing a minimization procedure to illustrate our theoretical findings by numerical experiments.

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Publication Details

Journal
Numerische Mathematik
Published
2026-05-16
DOI
https://doi.org/10.1007/s00211-026-01544-4
Primary Topic
Advanced Thermodynamics and Statistical Mechanics
Type
preprint
Field-Weighted Citation Impact
0.00

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preprint

A multiscale approach to the stationary Ginzburg–Landau equations of superconductivity

Patrick Henning, Christian Döding, Benjamin Dörich
Numerische Mathematik
Advanced Thermodynamics and Statistical Mechanics
preprint

A multiscale approach to the stationary Ginzburg–Landau equations of superconductivity

Patrick Henning, Christian Döding, Benjamin Dörich
preprint en

Abstract

Abstract In this work, we study the numerical approximation of minimizers of the Ginzburg–Landau free energy, a common model to describe the behavior of superconductors under magnetic fields. The unknowns are the order parameter, which characterizes the density of superconducting charge carriers, and the magnetic vector potential, which allows to deduce the magnetic field that penetrates the superconductor. Physically important and numerically challenging are especially settings which involve lattices of quantized vortices which can be formed in materials with a large Ginzburg–Landau parameter $$\kappa $$ <mml:math xmlns:mml="http://www.w3.org/1998/Math/MathML"> <mml:mi>κ</mml:mi> </mml:math> . In particular, $$\kappa $$ <mml:math xmlns:mml="http://www.w3.org/1998/Math/MathML"> <mml:mi>κ</mml:mi> </mml:math> introduces a severe mesh resolution condition for numerical approximations. In order to reduce these computational restrictions, we investigate a particular discretization which is based on mixed meshes where we apply a Lagrange finite element approach for the vector potential and a localized orthogonal decomposition (LOD) approach for the order parameter. We justify the proposed method by a rigorous a-priori error analysis (in $$L^2$$ <mml:math xmlns:mml="http://www.w3.org/1998/Math/MathML"> <mml:msup> <mml:mi>L</mml:mi> <mml:mn>2</mml:mn> </mml:msup> </mml:math> and $$H^1$$ <mml:math xmlns:mml="http://www.w3.org/1998/Math/MathML"> <mml:msup> <mml:mi>H</mml:mi> <mml:mn>1</mml:mn> </mml:msup> </mml:math> ) in which we keep track of the influence of $$\kappa $$ <mml:math xmlns:mml="http://www.w3.org/1998/Math/MathML"> <mml:mi>κ</mml:mi> </mml:math> in the main error contributions. This allows us to conclude $$\kappa $$ <mml:math xmlns:mml="http://www.w3.org/1998/Math/MathML"> <mml:mi>κ</mml:mi> </mml:math> -dependent resolution conditions for the various meshes and which only impose moderate practical constraints compared to a conventional finite element discretization. While our results only provide information on the approximability of the minimizers, we conclude by further proposing a minimization procedure to illustrate our theoretical findings by numerical experiments.

Numerische Mathematik
Karlsruhe Institute of Technology (DE), University of Bonn (DE), Ruhr University Bochum (DE)
Deutsche Forschungsgemeinschaft, Rheinische Friedrich-Wilhelms-Universität Bonn
Openalex Percentile: Top 100%
Advanced Thermodynamics and Statistical Mechanics
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