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SUMMARY:Consensus based approach to modeling of interacting nuclear partic
 le system
DTSTART;VALUE=DATE-TIME:20261027T162500Z
DTEND;VALUE=DATE-TIME:20261027T163000Z
DTSTAMP;VALUE=DATE-TIME:20261023T080307Z
UID:indico-contribution-6478@cern.ch
DESCRIPTION:Speakers: Yury Ivanskiy ()\nFor a system comprised of a large 
 number of particles\, it is extremely difficult to specify their interacti
 ons analytically. The multi-agent approach provides a possibility to const
 ruct a numerical model of a system composed of many particles. Such many-p
 article system stabilizes over time\, and its final state is\, to a certai
 n degree\, independent of the initial conditions. The multi-agent approach
  is actively used in modern computer science and control theory for contro
 l of distributed\, decentralized networks.\n\nThis work employs an approac
 h based on the Vicsek model [1]\, which was proved analytically by Morse [
 2] and subsequently found numerous applications including load balancing [
 3]\, opinion dynamics [4]\, swarm control [5]. Its application to nuclear 
 system modelling was proposed in [6]. In these applications\, the key feat
 ure is the agents' ability to coordinate without external influence. The c
 apacity of such coordination has been recently demonstrated for AI agents 
 [7].\n\nThe implemented algorithm makes it possible to simulate the aggreg
 ation and evolution of proton-neutron system as well as the clustering of 
 nuclear many-particle subsystems\, while accounting for long-range but rel
 atively weak Coulomb-type interactions. At the heart of the algorithm lies
  a consensus mechanism that balances the influence of the mutual attractio
 n and repulsion of particles and models the system's transition to a stabi
 lized state. The multi-agent nature of the proposed model allows evading t
 he problem of specifying a dynamical system that describes many-body inter
 actions. It scales efficiently and allows simulating a many-particle syste
 m with a large number of particles.\n\n1. T. Vicsek\, A. Czirók\, E. Ben-
 Jacob\, I. Cohen\, and O. Shochet (1995) Physical review letters\, 75(6)\,
  1226.\n2. A. S. Morse\, A. Jadbabaie\, J. Lin (2003) IEEE Trans. Autom. C
 ontrol\, 48. p. 988.\n3. E. Borisoglebskaya\, V. Erofeeva\, O. Granichin\,
  Y. Ivanskiy\, and N. Kizhaeva\, (2023) Proc. 9th International Conference
  on Control\, Decision and Information Technologies\, pp. 2032-2036.\n4. N
 . E. Friedkin\, A. V. Proskurnikov\, R. Tempo\, and S. E. Parsegov (2016).
  Science\, 354(6310)\, \npp. 321-326.\n5. R. Olfati-Saber (2006) IEEE Tran
 s. Autom. Control\, 51(3)\, pp. 401-420. \n6. Y. Ivanskiy\, A. Unzhakova (
 2022) Bull. Russ. Acad. Sci.: Phys. 86 (9)\, 1108-1110. \n7. G. De Marzo\,
  C. Castellano\, and D. Garcia (2026) Science Advances\, 12: eaea6091.\n\n
 https://indico.particle.mephi.ru/event/626/contributions/6478/
LOCATION:Sevastopol hotel Conference Hall 1
URL:https://indico.particle.mephi.ru/event/626/contributions/6478/
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