Abstract
Track and vertex reconstruction in the CMS detector use the information from the silicon pixel and the silicon strip detectors. The track and vertex fitting algorithms are based on the Kalman filter approach. The performance of the tracking procedure is evaluated in terms of efficiency and parameter resolution. The vertex reconstruction performance is reported in terms of primary vertex resolution. Some results obtained with a partial/conditional track reconstruction, used for High-Level Trigger algorithms are also given.
Highlights
High-energy-physics experiments demonstrated, over the past years, that the tracking system plays an important pr¢or¡ loevisiindoeltahhteeidgrheccheoafnfirgscteireduncpctayiorrtnieccoloefnetsrvtaercunkctssticwooninthotafaihn£iign¡ hg-rl&ees¡potlocuhntaisoragnnebddejhtetaetsdr.rtoThnahsnei¤nC¥Mj¡§etS¦ ̈s¥.tr¡Tahc©keetr ̈raicskdee¢rs¡iisg nael(sd¢ot¡ oreirqneuc!ior#en"dst¦%rtou$ c)rteahsnoidglvhtoenearby tracks in a large multiplicity environment and to identify b quarks and ' leptons via secondary vertices.The requirements on the reconstruction software are stringent; pattern recognition algorithms need to be efficient and robust in order to ensure high performance in track and vertex reconstruction, in the presence of multiple scattering, large particle multiplicity and large background due to hits from low momentum tracks, ¤ rays and secondary activities
The CMS tracker [2] is made of an inner silicon pixel detector and a silicon microstrip tracker
The primary vertex reconstruction in the pixel detector leads to a position resolution ranging from 20 to 70 m as shown
Summary
High-energy-physics experiments demonstrated, over the past years, that the tracking system plays an important pr¢or¡ loevisiindoeltahhteeidgrheccheoafnfirgscteireduncpctayiorrtnieccoloefnetsrvtaercunkctssticwooninthotafaihn£iign¡ hg-rl&ees¡potlocuhntaisoragnnebddejhtetaetsdr.rtoThnahsnei¤nC¥Mj¡§etS¦ ̈s¥.tr¡Tahc©keetr ̈raicskdee¢rs¡iisg nael(sd¢ot¡ oreirqneuc!ior#en"dst¦%rtou$ c)rteahsnoidglvhtoenearby tracks in a large multiplicity environment and to identify b quarks and ' leptons via secondary vertices. The requirements on the reconstruction software are stringent; pattern recognition algorithms need to be efficient and robust in order to ensure high performance in track and vertex reconstruction, in the presence of multiple scattering, large particle multiplicity and large background due to hits from low momentum tracks, ¤ rays and secondary activities. The CMS tracker [2] is made of an inner silicon pixel detector and a silicon microstrip tracker. The pixel detector ic( n)&o(%n(02EGsiF s) 1%t)s3£po lfacntmher.eaeTndhcey36l5¢sini l dicrcoimcnadlmoliawcyrneorstsotrii(np78(9tdh02eete@¢bc4at@ or.rreTclhoaevtehrriastdpriaiods4ii.ti4iob, ne7tr.w5eesaoennlud2ti10o0na.2nisdcA m11,#0BDancC mdm.twiTnohthepeabi(arEGsrFIroeH lf)repenlgadino-ecnaaipnsdddii ̈svP§kisdC emadt into an Inner Barrel (TIB), made of four layers of sensors, and an Outer Barrel (TOB) made of six layers.
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