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Автор Yoshiyuki Kabashima
Автор Hisanao Takahashi
Автор Osamu Watanabe
Дата выпуска 2010-06-01
dc.description A methodology to analyze the properties of the first (largest) eigenvalue and its eigenvector is developed for large symmetric random sparse matrices utilizing the cavity method of statistical mechanics. Under a tree approximation, which is plausible for infinitely large systems, in conjunction with the introduction of a Lagrange multiplier for constraining the length of the eigenvector, the eigenvalue problem is reduced to a bunch of optimization problems of a quadratic function of a single variable, and the coefficients of the first and the second order terms of the functions act as cavity fields that are handled in cavity analysis. We show that the first eigenvalue is determined in such a way that the distribution of the cavity fields has a finite value for the second order moment with respect to the cavity fields of the first order coefficient. The validity and utility of the developed methodology are examined by applying it to two analytically solvable and one simple but non-trivial examples in conjunction with numerical justification.
Формат application.pdf
Издатель Institute of Physics Publishing
Копирайт © 2010 IOP Publishing Ltd
Название Cavity approach to the first eigenvalue problem in a family of symmetric random sparse matrices
Тип paper
DOI 10.1088/1742-6596/233/1/012001
Electronic ISSN 1742-6596
Print ISSN 1742-6588
Журнал Journal of Physics: Conference Series
Том 233
Первая страница 12001
Последняя страница 12011
Выпуск 1

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