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UID:20250916T061002EDT-5324L766Ew@132.216.98.100
DTSTAMP:20250916T101002Z
DESCRIPTION:Dynamics of Collective Motion: Experiment\, Topology\, and PDE
 \n\nBiological aggregations such as bird flocks\, fish schools\, and insec
 t swarms are striking examples of self-organized collective motion. The ch
 allenges of collective motion research include determining individual-leve
 l behaviors\, assessing macroscopic group properties\, and elucidating the
  connection between the two. In this talk\, I present representative work 
 addressing each challenge. First\, to determine individual-level behaviors
 \, I perform motion tracking experiments on pea aphids and use the data to
  develop an unbiased correlated random walk model. Second\, to assess grou
 p-level dynamics\, I apply topological data analysis to the influential in
 teracting particle model of Vicsek et al. (1995). This analysis assigns a 
 topological signature to a set of aggregation data and detects dynamical e
 vents that are undetected by standard methods. Third\, I investigate a non
 local PDE model for aggregation. In the PDE modeling framework\, one can s
 pecify individual-level rules and determine the corresponding group behavi
 or. The nonlocal model is well-approximated by a local\, degenerate Cahn-H
 illiard model that is more amenable to analysis and computation. Using the
  Cahn-Hilliard model\, I demonstrate how environmental factors can suppres
 s the aggregation's peak population density\, which is essential for contr
 olling locust outbreaks.\n
DTSTART:20161212T200000Z
DTEND:20161212T200000Z
LOCATION:Room 920\, Burnside Hall\, CA\, QC\, Montreal\, H3A 0B9\, 805 rue 
 Sherbrooke Ouest
SUMMARY:Chad Topaz\, Macalester College
URL:/mathstat/channels/event/chad-topaz-macalester-col
 lege-264667
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