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1、REVIEWSOFMODERNPHYSICS,VOLUME82,APRIL–JUNE2010Trackandvertexreconstruction:FromclassicaltoadaptivemethodsAreStrandlie*Gj?vikUniversityCollege,P.O.Box191,N-2802Gj?vik,Norway?RudolfFrühwirthInstituteofHighEnergyPhysicsoftheAustrianAcademyofSciences,NikolsdorferGasse18,A-1050
2、Wien,AustriaPublished7May2010Thispaperreviewsclassicalandadaptivemethodsoftrackandvertexreconstructioninparticlephysicsexperiments.Adaptivemethodshavebeendevelopedtomeettheexperimentalchallengesathigh-energycolliders,inparticular,theCERNLargeHadronCollider.Theycanbechara
3、cterizedbytheobliterationofthetraditionalboundariesbetweenpatternrecognitionandstatisticalestimation,bythecompetitionbetweendifferenthypothesesaboutwhatconstitutesatrackoravertex,andbyahighlevelof?exibilityandrobustnessachievedwithaminimumofassumptionsaboutthedata.Thetheor
4、eticalbackgroundofsomeoftheadaptivemethodsisdescribed,anditisshownthatthereisacloseconnectionbetweenthetwomainbranchesofadaptivemethods:neuralnetworksanddeformabletemplates,ontheonehand,androbuststochasticTlterswithannealing,ontheotherhand.Asbothclassicalandadaptivemethods
5、oftrackandvertexreconstructionpresupposepreciseknowledgeofthepositionsofthesensitivedetectorelements,thepaperincludesanoverviewofdetectoralignmentmethodsandasurveyofthealignmentstrategiesemployedbypastandcurrentexperiments.DOI:10.1103/RevModPhys.82.1419PACSnumbers:02.70.
6、Rr,07.05.Kf,07.05.Mh,29.85.FjCONTENTSD.VertexTtting14291.Least-squaresmethodsforvertexTtting14292.RobustvertexTtting1431I.Introduction14203.VertexTndingbyiteratedTtting1431II.ClassicalMethodsofTrackandVertexIII.AdaptiveMethods1432Reconstruction1421A.HopTeldneuralnetworks14
7、32A.TrackTnding1422B.Elasticnetsanddeformabletemplates14341.Conformalmapping1422C.Gaussian-sumTlter14372.HoughandLegendretransforms1422D.EMalgorithmandadaptivetrackTtting14393.Trackroad1422E.Comparativestudies14414.Trackfollowing1423F.AdaptivevertexTtting1443B.TrackTtting1
8、423IV.DetectorAlignment14451.Trackparametrization1423A.Introduction14452.Trackmodel1423B.
