Description
(5 pts) Implement the DFS to check experimentally the theoretical result for the Poisson random graph with mean degree z = p(n − 1).
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- The fraction S of vertices in the giant component is the largest solution of
S = 1 − exp(−zS);
- Let v be a randomly chosen vertex from a non-giant component. The average size of the component to which v belongs is
1
⟨s⟩= .
1 − z + zS
Proceed as follows. Program the DFS (from scratch). Set the number of vertices n = 1000. Define a grid of values of z ranging between 0 and 4. For each z, generate r = 100 random graphs G(n,p) where p = z/(n − 1). For each graph, use the DFS to find its connected components. Calculate ⟨s(z)⟩ and S(z). Make two figures:
- Figure 1: find numerically and plot the theoretical values S(z) versus z. Also plot the experimentally found values for S(z).
- Figure 2: plot the theoretical value for ⟨s(z)⟩=[1−z +zS(z)]−1 and the experimentally found values for ⟨s(z)⟩.
Comment on your findings. Link files with your codes to the pdf file with your report.
- (5 pts) Implement the BFS to obtain estimates for the average length of shortest paths in the Poisson random graph:
. (1)
Proceed as follows. Program the BFS (from scratch). Set z = 4 so that almost all vertices belong to the giant component. For n = 2p, p = 10,11,12,13, generate a random graph G(n,p). Randomly select r = 100 vertices, and use each of them as a seed for the BFS. Average the found path lengths and find l(n). Plot the found l(n) versus n as well as the theoretical estimate (1). Comment on your observations. Link files with your codes to the pdf file with your report.
- (5 pts) Read Sections II.A, II.C, and II.D in Newman, Strogats, Watts, Random graphs with arbitrary degree distributions and their applications, Phys. Rev. E, 64, 026118. Consider a random graph with a prescribed degree distribution pk. Let v be a randomly chosen vertex from a non-giant component. Write a book report with a
detailed derivation of the formula for the average size of the component to which v belongs to:
⟨s⟩=. (2)



