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SUMMARY:Group avoidance through collective resetting
DTSTART:20261026T143000Z
DTEND:20261026T153000Z
DTSTAMP:20261024T032100Z
UID:indico-event-9893@indico.fysik.su.se
DESCRIPTION:Speakers: Juhee Lee (Umeå University)\n\nStochastic resetting
  is well understood for single particles\, but many problems involve group
 s whose resetting rule is set by the group itself. In computational scienc
 e\, for example\, swarm-search algorithms deploy many walkers that periodi
 cally relocate to the fittest searcher. In artificial selection\, repeated
 ly choosing the subpopulation farthest from an undesired state\, such as a
 ntibiotic resistance\, could keep a microbial population away from that st
 ate. Inspired by these examples\, we study diffusing particles in a confin
 ing potential that all reset at a constant rate to the position of the mos
 t extreme particle.\nTreating the group’s center of mass as an effective
  particle\, we use renewal theory and extreme-value statistics to build a 
 general framework for group resetting. The framework yields analytical sta
 tionary results that agree with many-particle simulations. We apply it to 
 the problem of avoiding an undesired region located at the center of the a
 ttracting potential\, so that the particles constantly drift toward it and
  only resetting can hold them away. We then add an absorbing boundary to s
 tudy first-passage dynamics. Resetting produces hitting-time distributions
  with plateaus spanning several orders of magnitude\, and the mean and mos
 t probable arrival times become widely separated. The system therefore lac
 ks a single characteristic time scale. This shows that controlling collect
 ive resetting requires looking beyond the average.\nZoom link: https://st
 ockholmuniversity.zoom.us/j/622224375\n\nhttps://indico.fysik.su.se/event/
 9893/
LOCATION:Albano Building 3
URL:https://indico.fysik.su.se/event/9893/
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