Characterising Graph Drawing with Eigenvectors
نویسنده
چکیده
We consider the problem of embedding a graph on n vertices in Euclidean space R for k n Typically k would be or By posing the problem as minimising the squared norm of the appropriately weighted distance be tween adjacent points subject to natural normalising conditions we arrive at a formulation of the problem for which the optimal solution can be sim ply computed in terms of the eigenvectors of the Laplacian matrix of the weighted graph For the case where the weights are chosen to be unity the solution is independent of the uniform penalty given to non adjacent ver tices In this case and for regular graphs the technique has been applied by Pisanski who demonstrated that the generated drawings are particularly pleasing in the case of Fullerene graphs arising in chemistry The idea of using eigenvectors for drawing graphs was used rst in chemical setting for molecular orbitals see For distance regular graphs with a second eigenvalue of multiplicity at least k the embedding has interesting properties see Godsil This paper demonstrates that a problem that has been traditionally solved by gradient descent techniques used to minimise a measure of poverty of the generated embedding a ords an analytical solution which can be
منابع مشابه
Drawing Graphs by Eigenvectors: Theory and Practice*
K e y w o r d s G r a p h drawing, Laplaclan, Eigenvectors, Fledler vector, Force-directed layout, Spectral graph theory 1. I N T R O D U C T I O N A graph G(V, E) is an abstract structure that is used to model a relation E over a set V of entities. Graph drawing is a standard means for visualizing relational information, and its ultimate usefulness depends on the readability of the resulting l...
متن کاملOn Spectral Graph Drawing
The spectral approach for graph visualization computes the layout of a graph using certain eigenvectors of related matrices. Some important advantages of this approach are an ability to compute optimal layouts (according to specific requirements) and a very rapid computation time. In this paper we explore spectral visualization techniques and study their properties. We present a novel view of t...
متن کاملCharacterizing Graph Drawing with Eigenvectors
Two definitions of the problem of graph drawing are considered, and an analytical solution is provided for each of them. The solutions obtained make use of the eigenvectors of the Laplacian matrix of a related structure. The procedures give good results for symmetrical graphs, and they have already been used for drawing fullerene molecules in the literature. The analysis characterizes precisely...
متن کاملSpectral Graph Drawing: A Survey
We give an overview of graph drawing techniques as discussed by Godsil/Royle, Koren and Pisanski/Shawe-Taylor. These techniques employ the eigenvectors of the Laplacian matrix to create an n-dimensional representation of an undirected graph.
متن کاملACE: A Fast Multiscale Eigenvectors Computation for Drawing Huge Graphs
We present an extremely fast graph drawing algorithm for very large graphs, which we term ACE (for Algebraic multigrid Computation of Eigenvectors). ACE exhibits an improvement of something like two orders of magnitude over the fastest algorithms we are aware of; it draws graphs of millions of nodes in less than a minute. ACE finds an optimal drawing by minimizing a quadratic energy function. T...
متن کامل