Hostname: page-component-cd9895bd7-hc48f Total loading time: 0 Render date: 2024-12-27T12:41:02.354Z Has data issue: false hasContentIssue false

EIGENVALUE ESTIMATES FOR THE WEIGHTED LAPLACIAN ON METRIC TREES

Published online by Cambridge University Press:  20 August 2001

K. NAIMARK
Affiliation:
Department of Theoretical Mathematics, The Weizmann Institute of Science, Rehovot 76100, Israel, [email protected], [email protected]
M. SOLOMYAK
Affiliation:
Department of Theoretical Mathematics, The Weizmann Institute of Science, Rehovot 76100, Israel, [email protected], [email protected]
Get access

Abstract

The Laplacian on a metric tree is $\Delta u = u''$ on its edges, with the appropriate compatibility conditions at the vertices. We study the eigenvalue problem on a rooted tree $\Gamma$: $$-\lambda \Delta u = V u \quad \text{on } \Gamma, \qquad u(o)=0.$$ Here $V \ge 0$ is a given ‘weight function’ on $\Gamma$, and $o$ is the root of $\Gamma$. The eigenvalues for such a problem decay no faster than $\lambda_n = O(n^{-2})$, this last case being typical for one-dimensional problems. We obtain estimates for the eigenvalues in the classes $l_p$, with $p > \frac12$, and their weak analogues $l_{p,\infty}$ with $p \ge \frac12$. The results for $p<1$ and $p>1$ are of different character. The case $p<1$ is studied in more detail. To analyse this case, we use two methods; in both of them the problem is reduced to a family of one-dimensional problems. One of the methods is based upon a useful orthogonal decomposition of the Dirichlet space on $\Gamma$. For a particular class of trees and weights, this method leads to the complete spectral analysis of the problem. We illustrate this in several examples, where we were able to obtain the asymptotics of the eigenvalues. 1991 Mathematics Subject Classification: primary 47E05, 05C05; secondary 34L15, 34L20.

Type
Research Article
Copyright
1999 London Mathematical Society

Access options

Get access to the full version of this content by using one of the access options below. (Log in options will check for institutional or personal access. Content may require purchase if you do not have access.)