The Spectrum of the Laplacian in Riemannian Geometry
نویسنده
چکیده
To any compact Riemannian manifold (M, g) (with or without boundary), we can associate a second-order partial differential operator, the Laplace operator ∆, defined by ∆(f) = −div(grad(f)) for f ∈ L(M, g). We will also sometimes write ∆g for ∆ if we want to emphasize which metric the Laplace operator is associated with. The set of eigenvalues of ∆ (the spectrum of ∆, or of M), which we will write as spec(∆) or spec(M, g), then forms a discrete sequence 0 = λ0 ≤ λ1 ≤ λ2 ≤ . . . → ∞. For simplicity, we will assume that M is connected; this will for example imply that the smallest eigenvalue, λ0, occurs with multiplicity 1. Note that the Laplacian also acts on p-forms in addition to functions via the definition ∆ = −(dδ + δd), where δ is the adjoint of d with respect to the Riemannian structure on the manifold. This aspect of the Laplacian will not be treated in this paper, the focus being the ordinary Laplacian acting on functions. With that in mind, there are two broad questions that are at the heart of spectral geometry:
منابع مشابه
Evolution of the first eigenvalue of buckling problem on Riemannian manifold under Ricci flow
Among the eigenvalue problems of the Laplacian, the biharmonic operator eigenvalue problems are interesting projects because these problems root in physics and geometric analysis. The buckling problem is one of the most important problems in physics, and many studies have been done by the researchers about the solution and the estimate of its eigenvalue. In this paper, first, we obtain the evol...
متن کاملA Geometry Preserving Kernel over Riemannian Manifolds
Abstract- Kernel trick and projection to tangent spaces are two choices for linearizing the data points lying on Riemannian manifolds. These approaches are used to provide the prerequisites for applying standard machine learning methods on Riemannian manifolds. Classical kernels implicitly project data to high dimensional feature space without considering the intrinsic geometry of data points. ...
متن کاملLaplacian Energy of a Fuzzy Graph
A concept related to the spectrum of a graph is that of energy. The energy E(G) of a graph G is equal to the sum of the absolute values of the eigenvalues of the adjacency matrix of G . The Laplacian energy of a graph G is equal to the sum of distances of the Laplacian eigenvalues of G and the average degree d(G) of G. In this paper we introduce the concept of Laplacian energy of fuzzy graphs. ...
متن کاملIdentification of Riemannian foliations on the tangent bundle via SODE structure
The geometry of a system of second order differential equations is the geometry of a semispray, which is a globally defined vector field on TM. The metrizability of a given semispray is of special importance. In this paper, the metric associated with the semispray S is applied in order to study some types of foliations on the tangent bundle which are compatible with SODE structure. Indeed, suff...
متن کاملNormalized laplacian spectrum of two new types of join graphs
Let $G$ be a graph without an isolated vertex, the normalized Laplacian matrix $tilde{mathcal{L}}(G)$ is defined as $tilde{mathcal{L}}(G)=mathcal{D}^{-frac{1}{2}}mathcal{L}(G)mathcal{D}^{-frac{1}{2}}$, where $mathcal{D}$ is a diagonal matrix whose entries are degree of vertices of $G$. The eigenvalues of $tilde{mathcal{L}}(G)$ are called as the normalized Laplacian eigenva...
متن کامل