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[Fizinfo] Ortvay kollokvium/Ortvay colloquium, 21.04.2022

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  • From: Kormányos Andor <andor.kormanyos AT>
  • To: "fizinfo AT" <fizinfo AT>, "ttk-fiz-faculty AT" <ttk-fiz-faculty AT>, "ttk-fiz-kutato AT" <ttk-fiz-kutato AT>, "ttk-fiz-emeritus AT" <ttk-fiz-emeritus AT>, "ttk-fiz-postdoc AT" <ttk-fiz-postdoc AT>, "ttk-fiz-phd-hallgatok AT" <ttk-fiz-phd-hallgatok AT>, "ttk-fiz-alkalmazottak AT" <ttk-fiz-alkalmazottak AT>, Zoltan Toroczkai <toro AT>
  • Subject: [Fizinfo] Ortvay kollokvium/Ortvay colloquium, 21.04.2022
  • Date: Tue, 19 Apr 2022 06:29:26 +0000
  • Accept-language: hu-HU, en-US
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ELTE Fizika Intézet / Institute of Physics


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:

Zoltán Toroczkai (University of Notre Dame)


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

  • [Fizinfo] Ortvay kollokvium/Ortvay colloquium, 21.04.2022, Kormányos Andor, 04/19/2022

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