Bounds for avalanche critical values of the Bak-Sneppen model

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arXiv:math/0508167v2 [math.PR] 30 Mar 2006BoundsforavalanchecriticalvaluesoftheBak-Sneppenmodel

AlexisGillett,RonaldMeesterandMisjaNuyensVrijeUniversiteitAmsterdamTheNetherlands

AbstractWestudytheBak-SneppenmodelonlocallyfinitetransitivegraphsG,inpar-ticularonZdandonT∆,theregulartreewithcommondegree∆.WeshowthattheavalanchesoftheBak-Sneppenmodeldominateindependentsitepercolation,inasensetobemadeprecise.SinceavalanchesoftheBak-Sneppenmodelaredominatedbyasimplebranchingprocess,thisyieldsupperandlowerboundsfortheso-calledavalanchecriticalvaluepBSc(G).Ourmainresultsimplythat1∆−1,andthat12d+1twoneighbours,byindependentanduniform(0,1)randomvariables.Wesaythatavertexwhosefitnessischangedbythisprocedurehasbeenupdated.Itisnotparticularlysignificantthattheunderlyinggraphofthemodelisthecircle,orZinthethermodynamiclimit.Bak-Sneppenmodelscanbedefinedonawiderangeofgraphsusingthesameupdateruleasabove:thevertexwithminimalfitnessanditsneighboursareupdated.Unlikeparticlesystemssuchaspercolationorthecontactprocess,theBak-Sneppenmodelhasnotuningparameter.Therefore,ithasbeendescribedasexhibitingself-organisedcriticalbehaviour,see[7]foradiscussion.OneofthewaystoanalyseBak-Sneppenmodelsistobreakthemdownintoaseriesofavalanches.Anavalanchefromathresholdp,referredtoasap-avalanche,issaidtooccurbetweentimessands+tifattimesallthefitnessesareequaltoorgreaterthanpwithatmostonevertexwhereequalityholds,andtimes+tisthefirsttimeaftersatwhichallfitnessesarelargerthanp.Thevertexwithminimalfitnessattimesiscalledtheoriginoftheavalanche.Ap-avalanchecanbeconsideredasastochasticprocessinitsownright.Thekeyfeatureoftheoriginisthatithastheminimalfitness(asitwillbeupdatedimmediately).Hence,wecanconsideritsfitnesstobeanyvalue,aslongasthisvalueisminimal.Verticeswithfitnessbelowthethresholdarecalledactive,othersarecalledinactive.Notethattheexactfitnessvalueofaninactivevertexisirrelevantfortheavalanche,sincethisvaluecanneverbeminimalduringtheavalanche.Thismotivatesthefollowingformaldefinitionofanavalanche.

Definition1.1Ap-avalanchewithoriginvonagraphG(withvertexsetV(G))isastochasticprocesswithstatespace{[0,p]A,A⊂V(G)}andinitialstatep{v}.TheprocessfollowstheupdaterulesoftheBak-Sneppenmodel.Anyvertexwithafitnesssmallerthanorequaltopisincluded.Anyvertexwithafitnesslargerthanpisnotincluded.Theprocessterminateswhenitistheemptyset.

Studyingavalancheshasconsiderableadvantages.ABak-Sneppenmodelonaninfinitegraphisnotwell-defined:whenthereareinfinitelymanyvertices,theremaynotbeavertexwithminimalfitness.However,Bak-Sneppenavalanchescanbedefinedonanylocallyfinitegraphasfollows:attime0allverticeshavefitness1,apartfromonevertex,theoriginoftheavalanche,whichhasfitnessp.WethenapplytheupdaterulesoftheBak-Sneppen

2model,untilallfitnessesareabovep.Thisisconsistentwithourpreviousnotion,asitisonlythefitnessesupdatedduringtheavalanchethatdeterminetheavalanche’sbehaviour.Theabilitytolookdirectlyatinfinitegraphsisverydesirable,becausethemostinterestingbehaviouroftheBak-Sneppenmodelisobservedinthelimitasthenumberofverticesinthegraphtendstoinfinity.Intheliteraturealternativetypesofavalancheshavebeenproposed,see[5,6].ThedefinitiongivenherecorrespondstothemostcommonlyusednotionofanavalancheandwasintroducedbyBakandSneppen[1].ForamorethoroughcoveragereadersaredirectedtoMeesterandZnamenski[8,9].NotethatunliketheBak-Sneppenmodelitself,theavalanchesdohaveatuningparameter,namelythethresholdp.Inthispaper,welookmainlyattransitivegraphs.Thebehaviourofanavalancheonatransitivegraphisindependentofitsorigin:anavalanchewithoriginatvertexvbehavesthesameasanavalanchewithorigin0.Whenanalysingavalanchesontransitivegraphs,itisthereforenaturaltotalkaboutatypicalp-avalanchewithoutspecifyingitsorigin.Toanalyseavalanches,somedefinitionsareneeded.Thesetofverticesupdatedbyanavalancheisreferredtoasitsrangeset,withtherangebeingthecardinalityofthisrangeset.LettingrBSG(p)denotetherangeofap-avalancheonatransitivegraphG,wedefinethe(avalanche)criticalvalueoftheBak-Sneppenmodelas

pBSc(G)=inf{p:P(rBSG(p)=∞)>0}.(1)Numericalsimulations[1]suggestthatthestationarymarginalfitnessdistributionsfortheBak-SneppenmodelonNsitestendtoauniformdistributionon(pBSc(Z),1),asN→∞.Ithasbeenprovedin[9]thatthisisindeedthecaseifpBSc(Z)=󰀄pBSc(Z),where󰀄pBSc(Z)isanothercriticalvalue,basedontheexpectedrange,andisdefinedas

󰀄pBSc(G)=inf{p:E[rBSG(p)]=∞}.(2)Itiswidelybelieved,butunproven,thatthesetwocriticalvaluesareequal.ItshouldnowbeclearthatknowledgeaboutthevalueofpBSc(G)isvitalindeterminingtheself-organisedlimitingbehaviouroftheBak-Sneppenmodel,eventhoughthereisnotuningparameterinthemodel.Althoughinthispaperwefocusonthecriticalvalue(1),ourboundsforthecriticalvalue(1)alsoholdforthecriticalvalue(2),seeSection6.