BEGIN:VCALENDAR
VERSION:2.0
PRODID:-//RLASKEY//CALENDEROUS//EN
CALSCALE:GREGORIAN
METHOD:PUBLISH
BEGIN:VEVENT
DTSTAMP:20170720T204331Z
LAST-MODIFIED:20170316T205746Z
DTSTART:20170328T140000Z
DTEND:20170328T150000Z
UID:event1739@bu.edu
URL:http://physics.bu.edu/events/show/1739
SUMMARY:Percolation and Reinforcement on Complex Networks
DESCRIPTION:Featuring Xian Yuan\n\nPart of the PhD Final Oral Exams.\n\nH.
Eugene Stanley\,Shlomo Havlin\, William Skocpol\, Karl Ludwig\, Kevin Black
\n\nAbstract:\n\nComplex networks appear in almost every aspect of our dail
y life and are widely studied in the fields of physics\, mathematics\, fina
nce\, biology and computer science. This work utilizes percolation theory i
n statistical physics to explore the percolation properties of complex netw
orks and develops a reinforcement scheme on improving network resilience. T
his dissertation covers two major parts of my Ph.D. research on complex net
works: i) probe-in the context of both traditional percolation and \nk-core
percolation-the resilience of complex networks with tunable degree distrib
utions or directed dependency links under random\, localized or targeted at
tacks; ii) develop and propose a \nreinforcement scheme to eradicate catast
rophic collapses that occur very often in interdependent networks. \n \nWe
first use generating function and probabilistic methods to obtain analytic
al solutions to\npercolation properties of interest\, such as the giant com
ponent size and the critical occupation probability. We study uncorrelated
random networks with Poisson\, bi-Poisson\, \npower-law\, and Kronecker-de
lta degree distributions and construct those networks which are based on th
e configuration model. The computer simulation results show remarkable agre
ement\nwith theoretical predictions. \n\nWe discover an increase of network
robustness as the degree distribution broadens and a decrease of network r
obustness as directed dependency links come into play under random attacks.
We also find that targeted attacks exert the biggest damage to the structu
re of both single and interdependent networks in k-core percolation. To str
engthen the resilience of interdependent networks\, we develop and propose
a reinforcement strategy and obtain the critical amount of reinforced nodes
analytically for interdependent Erdos-Renyi networks and numerically for s
cale-free and for random regular networks. \nOur mechanism leads to improve
ment of network stability of the West U.S. power grid. \n\nThis dissertatio
n provides us with a deeper understanding of the effects of structural fea
tures \non network stability and fresher insights into designing resilient
interdependent infrastructure networks.\n\n![Xin](/resources/event-image/17
39/7b2f302_small)
LOCATION:SCI 352\, 590 Commonwealth Avenue\, 02215
STATUS:CONFIRMED
CLASS:PUBLIC
END:VEVENT
END:VCALENDAR