Georgia Institute of Technology College of Sciences

Isospectral Reduction reduces a higher dimension matrix to a lower dimension one while preserving the eigenvalues. This goal is achieved by allowing rational functions of lambda to be the entries of the reduced matrix. It has been shown that isospectral reduction also preserves the eigenvectors. Here we will discuss the conditions under which the generalized eigenvectors also get preserved. We will discuss some sufficient conditions and the reconstruction of the original network.