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Random graph dynamics PDF

224 Pages·2007·0.986 MB·English
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P1:JZZ/JZK P2:JZP CUNY570-FM.tex CUNY570/Durrett 0521866561 printer:cupusbw November10,2006 16:25 This page intentionally left blank P1:JZZ/JZK P2:JZP CUNY570-FM.tex CUNY570/Durrett 0521866561 printer:cupusbw November10,2006 16:25 Random Graph Dynamics Thetheoryofrandomgraphsbeganinthelate1950sinseveralpapersby Erdo¨sandRe´nyi.Inthelatetwentiethcentury,thenotionofsixdegreesof separation,meaningthatanytwopeopleontheplanetcanbeconnected by a short chain of people who know each other, inspired Strogatz and Wattstodefinethesmallworldrandomgraphinwhicheachsiteiscon- nectedtokcloseneighbors,butalsohaslong-rangeconnections.Atabout thesametime,itwasobservedinhumansocialandsexualnetworksand ontheInternetthatthenumberofneighborsofanindividualorcomputer hasapowerlawdistribution.ThisinspiredBaraba´siandAlberttodefine thepreferentialattachmentmodel,whichhastheseproperties.Thesetwo papers have led to an explosion of research. While this literature is ex- tensive, many of the papers are based on simulations and nonrigorous arguments.Thepurposeofthisbookistouseawidevarietyofmathe- matical argument to obtain insights into the properties of these graphs. Auniquefeatureofthisbookistheinterestinthedynamicsofprocess takingplaceonthegraphinadditiontotheirgeometricproperties,such asconnectednessanddiameter. Rick Durrett is a Professor of Mathematics at Cornell University. He receivedhisPh.D.inOperationsResearchfromStanfordin1976.After 9 years at UCLA, he moved to Cornell, where his research turned to applicationsofprobability,firsttoecologyand,morerecently,togenetics. Hehaswrittenmorethan150papers,sixotherbooks,andhas33academic descendants. P1:JZZ/JZK P2:JZP CUNY570-FM.tex CUNY570/Durrett 0521866561 printer:cupusbw November10,2006 16:25 CAMBRIDGE SERIES IN STATISTICAL AND PROBABILISTIC MATHEMATICS EditorialBoard: R.Gill,DepartmentofMathematics,UtrechtUniversity B.D.Ripley,DepartmentofStatistics,UniversityofOxford S.Ross,EpsteinDepartmentofIndustrial&SystemsEngineering,Universityof SouthernCalifornia B.W.Silverman,St.Peter’sCollege,Oxford M.Stein,DepartmentofStatistics,UniversityofChicago This series of high-quality upper-division textbooks and expository monographs covers all aspects of stochastic applicable mathematics. The topics range from pure and applied statistics to probability theory, operations research, optimization, and mathematical pro- gramming. The books contain clear presentations of new developments in the field and alsoofthestateoftheartinclassicalmethods.Whileemphasizingrigoroustreatmentof theoreticalmethods,thebooksalsocontainapplicationsanddiscussionsofnewtechniques madepossiblebyadvancesincomputationalpractice. AlreadyPublished 1. BootstrapMethodsandTheirApplication,byA.C.DavisonandD.V.Hinkley 2. MarkovChains,byJ.Norris 3. AsymptoticStatistics,byA.W.vanderVaart 4. WaveletMethodsforTimeSeriesAnalysis,byDonaldB.PercivalandAndrew T.Walden 5. BayesianMethods,byThomasLeonardandJohnS.J.Hsu 6. EmpiricalProcessesinM-Estimation,bySaravandeGeer 7. NumericalMethodsofStatistics,byJohnF.Monahan 8. AUser’sGuidetoMeasureTheoreticProbability,byDavidPollard 9. TheEstimationandTrackingofFrequency,byB.G.QuinnandE.J.Hannan 10. DataAnalysisandGraphicsUsingR,byJohnMaindonaldandJohnBraun 11. StatisticalModels,byA.C.Davison 12. SemiparametricRegression,byD.Ruppert,M.P.Wand,andR.J.Carroll 13. ExercisesinProbability,byLoicChaumontandMarcYor 14. StatisticalAnalysisofStochasticProcessesinTime,byJ.K.Lindsey 15. MeasureTheoryandFiltering,byLakhdarAggounandRobertElliott 16. EssentialsofStatisticalInference,byG.A.YoungandR.L.Smith 17. ElementsofDistributionTheory,byThomasA.Severini 18. StatisticalMechanicsofDisorderedSystems,byAntonBovier 19. TheCoordinate-FreeApproachtoLinearModels,byMichaelJ.Wichura P1:JZZ/JZK P2:JZP CUNY570-FM.tex CUNY570/Durrett 0521866561 printer:cupusbw November10,2006 16:25 Random Graph Dynamics RICK DURRETT CornellUniversity CAMBRIDGEUNIVERSITY PRESS Cambridge, New York, Melbourne, Madrid, Cape Town, Singapore, São Paulo Cambridge University Press The Edinburgh Building, Cambridge CB28RU, UK Published in the United States of America by Cambridge University Press, New York www.cambridge.org Information on this title: www.cambridge.org/9780521866569 © Rick Durrett 2007 This publication is in copyright. Subject to statutory exception and to the provision of relevant collective licensing agreements, no reproduction of any part may take place without the written permission of Cambridge University Press. First published in print format 2006 ISBN-13 978-0-511-34983-6 eBook (NetLibrary) ISBN-10 0-511-34983-1 eBook (NetLibrary) ISBN-13 978-0-521-86656-9 hardback ISBN-10 0-521-86656-1 hardback Cambridge University Press has no responsibility for the persistence or accuracy of urls for external or third-party internet websites referred to in this publication, and does not guarantee that any content on such websites is, or will remain, accurate or appropriate. P1:JZZ/JZK P2:JZP CUNY570-FM.tex CUNY570/Durrett 0521866561 printer:cupusbw November10,2006 16:25 Contents Preface pagevii 1. Overview 1 1.1 IntroductiontotheIntroduction 1 1.2 Erdo¨s,Re´nyi,Molloy,andReed 3 1.3 SixDegrees,SmallWorlds 7 1.4 PowerLaws,PreferentialAttachment 11 1.5 EpidemicsandPercolation 15 1.6 PottsModelsandtheContactProcess 18 1.7 RandomWalksandVoterModels 20 1.8 CHKNSModel 21 2. Erdo¨s–Re´nyiRandomGraphs 27 2.1 BranchingProcesses 27 2.2 ClusterGrowthasanEpidemic 34 2.3 ClusterGrowthasaRandomWalk 37 2.4 DiameteroftheGiantComponent 43 2.5 CLTfortheGiantComponent 46 2.6 CombinatorialApproach 50 2.7 CriticalRegime 56 2.8 ThresholdforConnectivity 62 3. FixedDegreeDistributions 70 3.1 DefinitionsandHeuristics 70 3.2 ProofofPhaseTransition 75 3.3 SubcriticalEstimates 82 3.4 Distances:FiniteVariance 84 3.5 Epidemics 85 4. PowerLaws 90 4.1 Baraba´si-AlbertModel 90 4.2 RelatedModels 93 4.3 MartingalesandUrns 99 4.4 Scale-FreeTrees 105 4.5 Distances:PowerLaws2<β <3 110 v P1:JZZ/JZK P2:JZP CUNY570-FM.tex CUNY570/Durrett 0521866561 printer:cupusbw November10,2006 16:25 vi Contents 4.6 Diameter:Baraba´si-AlbertModel 116 4.7 Percolation,Resilience 121 4.8 SISEpidemic 125 5. SmallWorlds 132 5.1 WattsandStrogatzModel 132 5.2 PathLengths 134 5.3 Epidemics 140 5.4 IsingandPottsModels 144 5.5 ContactProcess 148 6. RandomWalks 153 6.1 SpectralGap 153 6.2 Conductance 156 6.3 FixedDegreeDistribution 159 6.4 PreferentialAttachmentGraph 164 6.5 ConnectedErdo¨s–Re´nyiGraphs 169 6.6 SmallWorlds 171 6.7 OnlyDegrees2and3 175 6.8 HittingTimes 177 6.9 VoterModels 181 7. CHKNSModel 187 7.1 HeuristicArguments 187 7.2 ProofofthePhaseTransition 190 7.3 SubcriticalEstimates 193 7.4 Kosterlitz-ThoulessTransition 197 7.5 ResultsattheCriticalValue 200 References 203 Index 211 P1:JZZ/JZK P2:JZP CUNY570-FM.tex CUNY570/Durrett 0521866561 printer:cupusbw November10,2006 16:25 Preface Chapter 1 will explain what this book is about. Here I will explain why I chose towritethebook,howitiswritten,whenandwheretheworkwasdone,andwho helped. Why.ItwouldmakeagoodstoryifIwasinspiredtowritethisbookbyanimage of Paul Erdo¨s magically appearing on a cheese quesadilla, which I later sold for thousandsofdollarsoneBay.However,thatisnottrue.Thethreemaineventsthat ledtothisbookwere(i)theuseofrandomgraphsinthesolutionofaproblemthat waspartofNathanaelBerestycki’sthesis;(ii)atalkthatIheardSteveStrogatzgive on the CHKNS model, which inspired me to prove some rigorous results about theirmodel;and(iii)abookreviewIwroteonthebooksbyWattsandBaraba´sifor theNoticesoftheAmericanMathSociety. The subject of this book was attractive for me, since many of the papers were outside the mathematics literature, so the rigorous proofs of the results were, in somecases,interestingmathematicalproblems.Inaddition,sinceIhadworkedfor anumberofyearsonthepropertiesofstochasticspatialmodelsonregularlattices, therewasthenaturalquestionofhowthebehaviorofthesesystemschangedwhen one introduced long-range connections between individuals or considered power lawdegreedistributions.Bothofthesemodificationsarereasonableifoneconsiders thespreadofinfluenzainatownwherechildrenbringthediseasehomefromschool, or the spread of sexually transmitted diseases through a population of individuals thathaveawidelyvaryingnumberofcontacts. How. The aim of this book is to introduce the reader to the subject in the same way that a walk through Musee´ d’Orsay exposes the visitor to the many styles of impressionism. We will choose results to highlight the major themes, but we willnotexamineindetaileveryvariationofpreferentialattachmentthathasbeen studied. We will concentrate on the ideas, giving the interesting parts of proofs, and referring the reader to the literature for the missing details. As Tom Liggett saidafterhehadwrittenhisbookInteractingParticleSystems,thereisnopointin havingabookthatisjustaunionofpapers. vii P1:JZZ/JZK P2:JZP CUNY570-FM.tex CUNY570/Durrett 0521866561 printer:cupusbw November10,2006 16:25 viii Preface Throughout we approach the subject with a probabilistic viewpoint. One prag- maticreasonisthat,intheabsenceoffuturisticproceduresliketheoneTomCruise’s characterhadinTheMinorityReport,thesearetheonlyeyesthroughwhichIcan view the world. For connections to computer algorithms and their analysis, you will have to ask someone who knows that story. In addition, we will emphasize topics not found in other mathematical books. I have nothing to add to the treat- mentofrandomregulargraphsinJanson,Luczak,andRucin´sky(2000),soIwill not spend much time on this special case of random graphs with a fixed degree distribution.TheclassicaltheoryofrandomgraphsofErdo¨sandRe´nyiiscovered nicely by Bolloba´s (2001), so I will keep treatment to the minimum necessary to prepareformorecomplicatedexamples. Several reviewers lobbied for an introductory chapter devoted to some of the tools: branching processes, large deviations, martingales, convergence of Markov chains, almost exponentiality of waiting times, etc. Personally I do not think it is necessary (or even desirable) to read the entire Kama Sutra before having sex the first time, so instead I approach the book as I do my Ph.D. students’ research projects.Wewillstartlookingatthesubjectandlearnaboutthetoolsastheyarise. Readers who find these interruptions distracting can note the statement and skip theproof,advicethatcanbeappliedtomostoftheresultsinthebook. When and where. The first version of these notes was written for a graduate seminar, which I gave on the topic at Cornell in the fall of 2004. On the Monday of the first full week of the semester, as I sat at my desk in Malott Hall, my back began to hurt, and I thought to myself that I had worked too hard on notes over the weekend. Two months, new desk chairs, a variety of drugs, physical therapy, and a lot of pain later, an MRI showed my problem was an infected disk. I still remembertheradiologist’sexcitingwords:“Wecan’tletyougohomeuntilweget in touch with your doctor.” Four days in the hospital and four months of sipping coffeeeverymorningwhileanIV-drippedantibioticsintomyarm,thebugsinme had been defeated, and I was back to almost normal. Reading papers on random graphs, figuring out proofs, and organizing the material while lying on my bed helpedmetogetthroughthatordeal. Inthesummerof2005,Irevisedthenotesandaddednewmaterialinpreparation forsixlecturesonthistopic,whichIgaveatthefirstCornellProbabilitySummer School.Severalmoreiterationsofpolishingfollowed.Whenmybraintoldmethat themanuscriptwasingreatshape,severalpaidreviewersshowedmethattherewas stillworktodo.Finally,amonthinParisatE´coleNormaleSupe´rieureinFebruary 2006 provided a pleasant setting for finishing the project. I would like to thank Jean Francois LeGall for the invitation to visit Paris, radio station 92.1 FM for providingthebackgroundmusicwhileItypedinmyapartment,andtherestaurants on and around Rue Mouffetard for giving me something to look forward to at the endoftheday.

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