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BEGIN:VEVENT
DTSTAMP:20260629T123746Z
DTSTART;VALUE=DATE-TIME:20111012T163000
DTEND;VALUE=DATE-TIME:20111012T173000
SUMMARY:Prof. Matthew Turner (91¸£Àû)
TZID:Europe/London
UID:20111012-094d439232b9afb20132d44893eb01c5@warwick.ac.uk
CREATED:20111005T133158Z
DESCRIPTION:The Physics of Swarming Swarming is a non-equilibrium phenome
 non observed in several animal species\, including insects\, birds\, fis
 h and mammals. In spite of this our understanding of the process is actu
 ally remarkably undeveloped. To a physicist the ordering is reminiscent 
 of that found elsewhere in nature\, e.g. in liquid crystals. Most models
  involve members of a swarm aligning their velocities with those of thei
 r immediate neighbours’ (plus some noise). However\, both metric-based a
 nd metric-free versions of these local models have fundamental pathologi
 es that are frequently overlooked\, e.g. the swarm evaporates in the abs
 ence of an ad hoc long-range attraction unless confined within an artifi
 cial box. We discuss how individuals might respond to a projection of th
 e swarm and argue why this is biologically plausible. A simple class of 
 candidate models then arises naturally in which there is a single additi
 onal scalar parameter controlling the tendency of all individuals to fly
  in a direction that is characteristic of the particular projection patt
 ern that they see. This naturally leads to swarms that remain localized.
  We identify a surprisingly rich variety of phenotypical behaviour that 
 is reminiscent of birds\, fish and insects. An intriguing emergent prope
 rty also appears - swarms self-select a particular density at which they
  are marginally opaque. We argue that this property is seen in bird floc
 ks. It implies a non-trivial scaling relationship between the swarm dens
 ity and the number of individuals: [latex]\\rho\\sim N^{-1}[/latex] in 2
 D and [latex]\\rho\\sim N^{-1/2}[/latex] in 3D. We argue that some evide
 nce for such scaling already exists. This model therefore makes several 
 experimentally testable predictions. It may even provide a mechanism for
  classifying the behaviour of different swarming animals according to th
 e relative strength of their alignment and projection terms. Finally\, i
 t would also appear to provide emergent biological fitness\, given that 
 marginal opacity provides for rapid\, long-range information transfer\, 
 another feature not present in local models with diffusive dynamics.
LOCATION:PLT
CATEGORIES:Departmental Colloquium
LAST-MODIFIED:20111005T133158Z
ORGANIZER;CN="":
END:VEVENT
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