Growing random networks under constraints
Puniyani, Amit · Lukose, Rajan
Statistical Mechanics
Disordered Systems and Neural Networks
Soft Condensed Matter
Quantitative Biology
Original · EN
We study the evolution of a random graph under the constraint that the diameter remain constant as the graph grows. We show that if the graph maintains the form of its link distribution it must be scale-free with exponent between 2 and 3. These uniqueness results may help explain the scale-free nature of graphs, of varying sizes, representing the evolved metabolic pathways in 43 organisms.
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