A new algorithms for reducing the envelope of a sparse matrix is presented. This algorithm is based on the computation of eigenvectors of the laplacian matrix associated with the graph of the sparse matrix. A recordering of the sparse matrix is determized based on the numerical values of the entries of an eigenvector of the laplatian matrix. Numerical results show that the new recording algorithm can in some cases reduce the envelope by more than a factor of two over the current standard algorithms such as gibbs-poole stockmeyer (GPS) or SPARSPAK's reverse Cuthill-McKee (RCM).