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DTSTAMP:20261023T144023Z
LAST-MODIFIED:20151210T143949Z
DTSTART:20151102T180000Z
DTEND:20151102T190000Z
UID:event1523@bu.edu
URL:http://physics.bu.edu/internal/events/show/1523
SUMMARY:First Principles and Effective Theory Approaches in Complex Network
	s
DESCRIPTION:Featuring Nima Dehmamy\n\nPart of the PhD Final Oral Exams.\n\n
	Examining Committee:  H.Eugene Stanley\, Pankaj Mehta\, Shlomo Havlin\, Kev
	in Black\, Irena Vodenska\n\nAbstract:\nThis dissertation concerns modeling
	 two aspects of dynamics of complex networks: (1)\nresponse dynamics and (2
	) growth and formation.\nA particularly challenging class of networks are o
	nes in which both nodes and links are\nevolving over time {the most promine
	nt example is a financial network. In the first part\nof the dissertation w
	e present a model for the response dynamics in networks near a meta-\nstabl
	e point. We start with a Landau-Ginzburg approach and show that the most ge
	neral\nlowest order Lagrangians for dynamical weighted networks can be used
	 to derive conditions\nfor stability under external shocks. Using a closely
	 related model\, which is easier to solve\nnumerically\, we propose a power
	ful and intuitive set of equations for response dynamics\nof financial netw
	orks. We find the stability conditions of the model and find two phases:\n"
	calm" phase\, in which changes are sub-exponential and where the system mov
	es to a new\,\nclose-by equilibrium; "frantic" phase\, where changes are ex
	ponential\, with negative blows\nresulting in crashes and positive ones lea
	ding to formation of "bubbles". We empirically\nverify these claims by anal
	yzing data from Eurozone crisis of 2009-2012 and stock markets.\nWe show th
	at the model correctly identifies the time-line of the Eurozone crisis\, an
	d in the\nstock market data it correctly reproduces the auto-correlations a
	nd phases observed in the\ndata.\nThe second half of the dissertation addre
	sses the following question: Do networks that\nform due to local interactio
	ns (local in real space\, or in an abstract parameter space) have\ncharacte
	ristics dierent from networks formed of random or non-local interactions? U
	sing\ninteracting elds obeying Fokker-Planck equations we show that many ne
	twork character-\nistics such as degree distribution\, degree-degree correl
	ation and clustering can either be\nderived analytically or there are analy
	tical bounds on their behaviour. In particular\, we\nderive recursive equat
	ions for all powers of the ensemble average of the adjacency matrix.\nWe an
	alyze a few real world networks and show that some networks that seem to fo
	rm from\nlocal interactions indeed have characteristics almost identical to
	 simulations based on our\nmodel\, in contrast with many other networks.
LOCATION:SCI 328\, 590 Commonwealth Avenue\, 02215
STATUS:CONFIRMED
CLASS:PUBLIC
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