Answer to Question #191456 in Complex Analysis for Milton

Question #191456

We adopt the following notation: N and L indicate respectively the total number of

nodes and links of the network, Air indicates the generic element of the adjacency

matrix A of the network, ki

indicates the degree of node i and hki indicates the

average degree of the network.

At time t = 1 the network is formed by a n0 = 6 nodes m0 = 6 links.

At every time step t > 1 the network evolves according to the following rules:

- A link (r,s) between a node r and a node s is chosen randomly with uniform

probability

π(r,s) = Ar,s/L

and is removed from the network.

- A single new node joins the network and is connected to the rest of the network

by m links with m fixed to a time-independent integer constant satisfying

2 < m ≤ 6. Each of these new links connects the new node to a generic node j

chosen with probability

Πj =kj/(k)N

.a) Evaluate Π˜

i(t) indicating the expected increase in the number of links of node i

at any given time t and show that it follows the preferential attachment rule.



1
Expert's answer
2021-05-11T11:44:21-0400

"\\Pi_i=\\sum_{r=1}^N \\pi(i,r)=\\sum _{r=1}^N\\dfrac{A_{ir}}{L}"


As we know, "L=\\dfrac{1}{2}\\sum_{j=1}^NK_j"


         and "k_i=\\sum_{r=1}^NA_{ir}"


So, "\\Pi_i=\\sum_{r=1}^N\\dfrac{K_i}{\\frac{1}{2}\\sum_{j=1}^Nk_j}"


"\\Pi_i=\\dfrac{2k_i}{\\sum_{j=1}^NK_j}"


So we have "\\Pi_1,\\Pi_2,\\Pi_3.." .


According to question-


"\\dfrac{dk_i(t)}{dt}=\\Pi_i=\\dfrac{2k_i}{\\sum_{j=1}^NK_j}"


We limit "t\\ge 1" , we have "\\sum _jK_j =2L \\sim ut"


Initilly "K_i(t_i)=6"


So , "k_i(t_i)=6(\\dfrac{t}{t_1})^{0.5}"


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