TITLE: How networks with high largest eigenvalues are more robust?
QUESTION [5 upvotes]: In the literature, it is sometimes indicated that network with high value of largest eigenvalue (either adjacency matrix or its Laplacian counterpart) are more robust against link/node removals. However, these statements are usually NOT accompanied with references. 
I am looking for some explanation on why is this so? Or pointers to some work that investigate/explain this.
I wonder if this statement is simply the result of difference between link density? I doubt its so simplistic. Is there any study on network robustness comparing networks with same link density but different largest eigenvalues (or spectral radius)?

REPLY [4 votes]: The following papers might contain relevant information to your question:
Robustness of networks against viruses: the role of the spectral radius, by
A. Jamakovic, R.E. Kooij, P. Van Mieghem, E.R. van Dam
https://www.nas.ewi.tudelft.nl/people/Rob/telecom/jamakovic.pdf
Epidemic Spreading in Real Networks: An Eigenvalue Viewpoint, by 
Yang Wang, Deepayan Chakrabarti, Chenxi Wang and Christos Faloutsos 
http://www-2.cs.cmu.edu/afs/cs.cmu.edu/user/christos/www/PUBLICATIONS/srds03-virus.pdf