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Numerical methods for metric graphs = Eigenvalue problems and parabolic partial differential equations /

紀錄類型:	書目-語言資料,印刷品 : Monograph/item
正題名/作者:	Numerical methods for metric graphs/ by Anna Weller.
其他題名:	Eigenvalue problems and parabolic partial differential equations /
作者:	Weller, Anna.
出版者:	Cham :Springer Nature Switzerland : : 2025.,
面頁冊數:	xxi, 190 p. :ill., digital ; : 24 cm.;
Contained By:	Springer Nature eBook
標題:	Graphic methods. -
電子資源:	https://doi.org/10.1007/978-3-032-05011-3
ISBN:	9783032050113

Numerical methods for metric graphs = Eigenvalue problems and parabolic partial differential equations /
Weller, Anna.

Numerical methods for metric graphsEigenvalue problems and parabolic partial differential equations /[electronic resource] :by Anna Weller. - Cham :Springer Nature Switzerland :2025. - xxi, 190 p. :ill., digital ;24 cm. - Lecture notes in mathematics,v. 23821617-9692 ;. - Lecture notes in mathematics ;1943..

Chapter 1. Introduction -- Chapter 2. Background: Graphs and Differential Equations -- Chapter 3. Finite Element Method -- Chapter 4. Spectral Solution Method -- Chapter 5. Computation of Quantum Graph Spectra -- Chapter 6. Numerical Results -- Chapter 7. Comparison of Finite Element and Spectral Galerkin Method -- Chapter 8. Application to the Simulation of Tau Propagation in Alzheimer's Disease -- Chapter 9. Conclusion.

This book discusses the fundamentals of the numerics of parabolic partial differential equations posed on network structures interpreted as metric spaces. These so-called metric graphs frequently occur in the context of quantum graphs, where they are studied together with a differential operator and coupling conditions at the vertices. The two central methods covered here are a Galerkin discretization with linear finite elements and a spectral Galerkin discretization with basis functions obtained from an eigenvalue problem on the metric graph. The solution of the latter eigenvalue problems, i.e., the computation of quantum graph spectra, is therefore an important aspect of the method, and is treated in depth. Further, a real-world application of metric graphs to the modeling of the human connectome (brain network) is included as a major motivation for the investigated problems. Aimed at researchers and graduate students with a practical interest in diffusion-type and eigenvalue problems on metric graphs, the book is largely self-contained; it provides the relevant background on metric (and quantum) graphs as well as the discussed numerical methods. Numerous detailed numerical examples are given, supplemented by the publicly available Julia package MeGraPDE.jl.

ISBN: 9783032050113

Standard No.: 10.1007/978-3-032-05011-3doiSubjects--Topical Terms:

768930
Graphic methods.

LC Class. No.: QA90

Dewey Class. No.: 511.52

Numerical methods for metric graphs = Eigenvalue problems and parabolic partial differential equations /
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520 $a This book discusses the fundamentals of the numerics of parabolic partial differential equations posed on network structures interpreted as metric spaces. These so-called metric graphs frequently occur in the context of quantum graphs, where they are studied together with a differential operator and coupling conditions at the vertices. The two central methods covered here are a Galerkin discretization with linear finite elements and a spectral Galerkin discretization with basis functions obtained from an eigenvalue problem on the metric graph. The solution of the latter eigenvalue problems, i.e., the computation of quantum graph spectra, is therefore an important aspect of the method, and is treated in depth. Further, a real-world application of metric graphs to the modeling of the human connectome (brain network) is included as a major motivation for the investigated problems. Aimed at researchers and graduate students with a practical interest in diffusion-type and eigenvalue problems on metric graphs, the book is largely self-contained; it provides the relevant background on metric (and quantum) graphs as well as the discussed numerical methods. Numerous detailed numerical examples are given, supplemented by the publicly available Julia package MeGraPDE.jl.
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