Timeline for limiting empirical spectral distribution of the Laplacian matrix on an Erdos-Renyi graph?
Current License: CC BY-SA 3.0
6 events
| when toggle format | what | by | license | comment | |
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| Apr 19, 2018 at 14:31 | comment | added | linello | Not being a mathematician but a physicist. I prefer the approach of Newman in terms of clarity and direct result. The Chung and Lu paper is more hard. Also take a look at Rao and Edelman software tool (reference 33,34 in the Newman's paper). | |
| Apr 19, 2018 at 13:55 | comment | added | j.c. | OK, I missed that they refer to the Erdős–Rényi random graph as the Poisson random graph. For the normalized Laplacian specifically, they cite a paper of Chung and Vu pnas.org/content/100/11/6313#sec-4 | |
| Apr 19, 2018 at 13:39 | comment | added | linello | If you set $k_i= (n-1)p$ I think yes! Take a look where in the paper they compute the spectral density for a network with only two different degrees(section 5). The whole computation for the laplacian is not done though. | |
| Apr 19, 2018 at 13:21 | comment | added | j.c. | This paper does computations with the configuration model of random graphs. Is it easy to adapt those to the Erdős–Rényi model? | |
| Apr 19, 2018 at 10:43 | review | First posts | |||
| Apr 19, 2018 at 11:28 | |||||
| Apr 19, 2018 at 10:40 | history | answered | linello | CC BY-SA 3.0 |