ELFT HÍRADÓ

[Kormányos Andor <andor.kormanyos AT ttk.elte.hu>]

ELTE Fizika Intézet / Institute of Physics

ORTVAY KOLLOKVIUM / ORTVAY COLLOQUIUM
(https://physics.elte.hu/ortvayseminar)


Thursday, 21st April 2022, 15:00


Hybrid format:

Pócza Jenő Classroom,  Physics Building 1.71
Pázmány Péter sétány 1/A, 1117 Budapest

and Microsoft Teams:

https://teams.microsoft.com/l/meetup-join/19%3aE-neA-S4-ucnS9OJ4HUTfwixh2tL4S6JpTbAR919VRE1%40thread.tacv2/1650043633655?context=%7b%22Tid%22%3a%22b366dbcd-4fc3-4451-82d2-e239564302c3%22%2c%22Oid%22%3a%22560bcc66-85b7-4700-9055-41903a3659ca%22%7d


Zoltán  Toroczkai  (University of Notre Dame)

<https://physics.elte.hu/en/content/istvan-b-foldes-wigner-rcp-institute-for-particle-and-nuclear-physics.e.2811>

Modelling real word networks with degree-preserving processes


Modeling real-world networks is a key focus area of Network Science. I will 
first provide a brief overview into the state-of-the-art of network modeling, 
then turn to the discussion of network evolution models. Real-world networks 
evolve over time through the addition or removal of nodes and edges. In 
current network-evolution models, the degree of each node varies or grows 
arbitrarily, yet there are many networks for which a different description is 
required. In some networks, node degree saturates, such as the number of 
active contacts of a person, and in some it is fixed, such as the valence of 
an atom in a molecule. I will introduce a novel family of network growth 
processes that preserve node degree (DPG), resulting in structures 
substantially different from those reported previously. We demonstrated that, 
despite it being an NP (non-deterministic polynomial time)-hard problem in 
general, the exact structure of most real-world networks can be generated 
from degree-preserving growth. We also show that this process can create 
scale-free networks with arbitrary exponents, however, without preferential 
attachment.  If preferential attachment is an effective rich-gets-richer 
mechanism applied to connectivity formation, then degree-preserving growth is 
a type of “tinkering” mechanism, a property observed in many real systems, 
e.g., by the Nobel Laurate F. Jacob in: “Evolution and Tinkering”, Science, 
196, 1161 (1977)). Finally, I will present applications of DPG to epidemics 
control via network immunization, viral marketing, knowledge dissemination, 
the design of molecular isomers with desired properties and to a problem in 
number theory.


Best regards,
Andor Kormányos
coordinator