Numerical Methods for Metric Graphs: Eigenvalue Problems and Parabolic Partial Differential Equations
暫譯: 度量圖的數值方法:特徵值問題與拋物型偏微分方程

Weller, Anna

  • 出版商: Springer
  • 出版日期: 2025-11-22
  • 售價: $4,850
  • 貴賓價: 9.5$4,608
  • 語言: 英文
  • 頁數: 190
  • 裝訂: Quality Paper - also called trade paper
  • ISBN: 3032050103
  • ISBN-13: 9783032050106
  • 相關分類: 數值分析 Numerical-analysis
  • 海外代購書籍(需單獨結帳)

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商品描述

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.

商品描述(中文翻譯)

本書討論了在被解釋為度量空間的網絡結構上,拋物型偏微分方程數值方法的基本原理。這些所謂的度量圖在量子圖的背景下經常出現,並與微分算子及頂點的耦合條件一起進行研究。本書涵蓋的兩個核心方法是使用線性有限元素的Galerkin離散化和基於度量圖上特徵值問題獲得的基函數的譜Galerkin離散化。因此,後者特徵值問題的解,即量子圖譜的計算,是該方法的一個重要方面,並且進行了深入的探討。此外,將度量圖應用於人類連接組(大腦網絡)建模的實際應用作為研究問題的主要動機之一。本書針對對度量圖上的擴散類型和特徵值問題有實際興趣的研究人員和研究生,內容基本自足;它提供了有關度量(和量子)圖及所討論的數值方法的相關背景。書中提供了大量詳細的數值範例,並附有公開可用的Julia套件MeGraPDE.jl。

作者簡介

Anna Weller completed her PhD in applied mathematics at the University of Cologne. In her research, she focused on diffusion problems on network-like structures, as well as their numerical solution and modeling in the human brain. Currently, she is a postdoctoral researcher at the Fraunhofer Institute for Algorithms and Scientific Computing.

作者簡介(中文翻譯)

安娜·韋勒 在科隆大學完成了應用數學的博士學位。她的研究專注於類似網絡結構的擴散問題,以及在人體大腦中的數值解法和建模。目前,她是弗勞恩霍夫算法與科學計算研究所的博士後研究員。