Rolan Alexander Valle Rey Sánchez

A student is making some simulations about a Barabási–Albert model with different preferential attachment conditions. He is analyzing a particular network model for different scenarios for α=[0, 0.35, 1, 1.6] When the model is in the superlinear attachment, he found that kmax is 20 at the time t0=5. However, when the model is the linear phase at the time 49 kmax is 28 and when the time is 289, kmax=68, find the degree exponent γ He is using. when the model is the sublinear phase at time t0, kmax=2, find kmax at the time 824. γ=2.5 , kmax=18 γ=3 , kmax=19 γ=2.5 , kmax=19 γ=3, kmax=18 None of the above. Original idea by: Alexander Valle Rey

Complete the sentences with RN or SFN in the following statements, When we compare random networks (RN) and scale-free networks (SFN). I) In ___, most nodes have the same number of links. II) In ___, many nodes with only a few links. III) In ___, there are A few hubs with a huge number of links. IV) In ___, there are Not highly connected nodes. V) In ___, the size of the largest node grows logarithmically or slower with N, implying that hubs will be tiny even in a very large ___. VI) In__ the size of the hubs grows polynomially with network size; hence they can grow quite large in ___. VII) A ___ follows a Poisson distribution, quite similar to a bell curve. VIII) In __ the distribution, most nodes have only a few links. A few highly connected hubs hold together these numerous small nodes. A) RN: I, II,IV, VI,VII and SFN:III, V, VIII B) RN: II, III,IV, Vand