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SUMMARY:Inducing synchronization in complex networks via stochastic resett
 ing in the Kuramoto model
DTSTART;VALUE=DATE-TIME:20260414T220400Z
DTEND;VALUE=DATE-TIME:20260414T221100Z
DTSTAMP;VALUE=DATE-TIME:20260412T125442Z
UID:indico-contribution-330@fisindico.uniandes.edu.co
DESCRIPTION:Speakers: KEVIN PARAMERO ARIAS (UNIVERSIDAD NACIONAL DE COLOMB
 IA)\nCollective synchronization is an emergent phenomenon in physical\, bi
 ological\, and\ntechnological systems\, where local interactions enable dy
 namical adjustment among\noscillators. In complex networks\, the Kuramoto 
 model provides a fundamental framework to study the transition between inc
 oherent and synchronized states\; however\, synchronization typically requ
 ires sufficiently strong coupling\, which limits its controllability in su
 bcritical regimes. In this work\, we investigate an extension based on the
  stochastic resetting of subsystems\, defined as random interruptions that
  restore the phase of a fraction of nodes to a reference value. We analyze
  this dynamics on different network topologies using numerical simulations
  and a mean-field theoretical approach\, evaluating the role of the resett
 ing rate\, the fraction of reset nodes\, and structural heterogeneity in t
 he synchronization transition. \nOur main result shows that stochastic res
 etting can induce synchronization even in regimes where the original dynam
 ics remains incoherent. This mechanism acts as a local realignment process
  that counteracts phase dispersion and reduces the effective coupling thre
 shold. These findings identify resetting as an effective strategy to promo
 te and control collective coherence in complex oscillator networks.\n\nhtt
 ps://fisindico.uniandes.edu.co/event/23/contributions/330/
LOCATION:Universidad Nacional Edificio 564
URL:https://fisindico.uniandes.edu.co/event/23/contributions/330/
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