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VERSION:2.0
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METHOD:PUBLISH
BEGIN:VEVENT
DTSTAMP:20261019T095214Z
LAST-MODIFIED:20140218T210724Z
DTSTART:20140225T160000Z
DTEND:20140225T170000Z
UID:event1246@bu.edu
URL:http://physics.bu.edu/internal/events/show/1246
SUMMARY: Spontaneous Recovery in Dynamical Networks
DESCRIPTION:Featuring Antonio Majdandzik\n\nPart of the Preliminary Oral Ex
	am.\n\nExamining Committee:  H.E. Stanley\, Shlomo Havlin\, Lawrence Sulak\
	, William Skocpol\n\nAbstract:\n\nMany things around us interact and are co
	nnected. While we have a very good understanding of interactions between el
	ementary particles\, atoms or molecules\, it is a difficult task to describ
	e and understand interactions between individual units in complex systems t
	hat we find in biology\, society\, finance\, Internet\, infrastructure\, tr
	affic\, and many others. In the last decade\, physicists working on complex
	 networks have been very much focused on various kinds of spreading phenome
	na (damage spreading\, transport\, activation processes)\, since these yiel
	d phenomena well known in physics - phase transitions are most notable exam
	ple. Of particular interest are abrupt dynamic events that cause networks t
	o irreversibly fail. However\, a remarkable property of many real-world net
	works is that they can sometimes recover spontaneously after they collapseâ
	€”think of traffic jams suddenly easing\, sudden market crashes followed by
	 recoveries\, or people waking from a coma. In some systems such as financi
	al markets or traffic networks\, failures and recoveries are a never-ending
	 sequence. To model this marked network recovery\, we examine the effect of
	 local node recoveries and stochastic contiguous spreading\, and find that 
	they can lead to the spontaneous emergence of macroscopic ‘phase-flipping
	’ phenomena. As the network is of finite size and is stochastic\, the fra
	ction of active nodes z switches back and forth between the two network col
	lective modes characterized by high network activity and low network activi
	ty. Furthermore\, the system exhibits a strong hysteresis behaviour analogo
	us to phase transitions near a critical point. To explain the phase-flippin
	g phenomena fundamentally\, we develop a picture (representation) of the un
	derlying mechanism as the first passage process in the hysteresis region of
	 the phase diagram. We present real-world network data that suggest switchi
	ng behaviour in accord with the predictions of the model.\n\n![Antonio] (/r
	esources/event-image/1246/6f24434_small)
LOCATION:SCI 352\, 590 Commonwealth Avenue\, 02215
STATUS:CONFIRMED
CLASS:PUBLIC
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