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Transverse momentum spectra of charged particles in proton-proton collisions at√s= 900 GeV with ALICE at the LHC

ALICE Collaboration

K. Aamodtby, N. Abelaq, U. Abeysekarabw, A. Abrahantes Quintanaap, A. Abramyandh, D. Adamovacg,M.M. Aggarwaly, G. Aglieri Rinellaan, A.G. Agocsr, S. Aguilar Salazarbk, Z. Ahammedba, A. Ahmadb, N. Ahmadb,

S.U. Ahnal,1, R. Akimotocu, A. Akindinovbn, D. Aleksandrovbp, B. Alessandrocz, R. Alfaro Molinabk, A. Alici m,E. Almaraz Avinabk, J. Almeh, T. Altaq,2, V. Altini e, S. Altinpinarae, C. Andreiq, A. Andronicae, G. Anellian,

V. Angelovaq,2, C. Ansonaa, T. Anticicdi, F. Antinorian,3, S. Antinorim, K. Antipinaj, D. Antonczykaj, P. Antoniolin,A. Anzobk, L. Aphecetchebs, H. Appelshauseraj, S. Arcellim, R. Arceobk, A. Arendaj, N. Armestocm, R. Arnaldicz,

T. Aronssonbt, I.C. Arseneby,4, A. Asryancs, A. Augustinusan, R. Averbeckae, T.C. Awesbv, J.Aystoaw, M.D. Azmib,S. Bablokh, M. Bachai, A. Badalax, Y.W. Baekal,1, S. Bagnascocz, R. Bailhacheae,5, R. Balacy, A. Baldissericj,

A. Balditz, J. Banbd, R. Barberaw, G.G. Barnafoldir, L. Barnbyl, V. Barretz, J. Bartkeac, F. Barilee, M. Basilem,V. Basmanovco, N. Bastidz, B. Bathenbr, G. Batignebs, B. Batyunyaah, C. Baumannbr,5, I.G. Beardenab, B. Beckert,6,

I. Belikovct, R. Bellwiedag, E. Belmont-Morenobk, A. Belogiannid, L. Benhabibbs, S. Beolecy, I. Berceanuq,A. Bercuciae,7, E. Berdermannae, Y. Berdnikovam, L. Betevan, A. Bhasinav, A.K. Bhatiy, L. Bianchicy, N. Bianchiak,

C. Bianchinbz, J. Bielcıkcb, J. Bielcıkovacg, A. Bilandzicc, L. Bimbotbx, E. Biolcaticy, A. Blancz, F. Blancow,8,F. Blancobi, D. Blaubp, C. Blumeaj, M. Bocciolian, N. Bockaa, A. Bogdanovbo, H. Bøggildab, M. Bogolyubskycd,

J. Bohmcq, L. Boldizsarr, M. Bombarabc, C. Bombonatibz,10, M. Bondilaaw, H. Borelcj, A. Borisovax, C. Bortolinbz,40,S. Boseaz, L. Bosisiocv, F. Bossucy, M. Botjec, S. Bottgeraq, G. Bourdaudbs, B. Boyerbx, M. Brauncs,

P. Braun-Munzingerae,af,2, L. Bravinaby, M. Bregantcv,11, T. Breitneraq, G. Bruckneran, R. Brunan, E. Brunabt,G.E. Brunoe, D. Budnikovco, H. Bueschingaj, P. Buncican, O. Buschar, Z. Butheleziv, D. Caffarribz, X. Caidg,H. Cainesbt, E. Calvobf, E. Camachobl, P. Camerinicv, M. Campbellan, V. Canoa Romanan, G.P. Capitaniak,

G. Cara Romeon, F. Carenaan, W. Carenaan, F. Carminatian, A. Casanova Dıazak, M. Casellean,J. Castillo Castellanoscj, J.F. Castillo Hernandezae, V. Catanescuq, E. Cattaruzzacv, C. Cavicchiolian, P. Cerellocz,

V. Chambertbx, B. Changcq, S. Chapelandan, A. Charpybx, J.L. Charvetcj, S. Chattopadhyayaz, S. Chattopadhyayba,M. Cherneybw, C. Cheshkovan, B. Cheynisdb, E. Chiavassacy, V. Chibante Barrosoan, D.D. Chinellatou, P. Chochulaan,

K. Choicf, M. Chojnackida, P. Christakoglouda, C.H. Christensenab, P. Christiansenbh, T. Chujocx, F. Chumanas,C. Cicalot, L. Cifarellim, F. Cindolon, J. Cleymansv, O. Cobanoglucy, J.-P. Coffinct, S. Colicz, A. Collaan,

G. Conesa Balbastreak, Z. Conesa del Vallebs,12, E.S. Connerdf, P. Constantinar, G. Contincv,10, J.G. Contrerasbl,Y. Corrales Moralescy, T.M. Cormierag, P. Cortesea, I. Cortes Maldonadoce, M.R. Cosentinou, F. Costaan,M.E. Cotallobi, E. Cresciobl, P. Crochetz, E. Cuautlebj, L. Cunqueiroak, J. Cussonneaubs, A. Daineseca,

H.H. Dalsgaardab, A. Danup, I. Dasaz, A. Dashk, S. Dashk, G.O.V. de Barroscn, A. De Carock, G. de Cataldof,J. de Cuvelandaq,2, A. De Falcos, M. De Gaspariar, J. de Grootan, D. De Gruttolack, N. De Marcocz, S. De Pasqualeck,

R. De Remigiscz, R. de Rooijda, G. de Vauxv, H. Delagrangebs, Y. Delgadobf, G. Dellacasaa, A. Deloffdc,V. Demanovco, E. Denesr, A. Deppmancn, G. D’Erasmoe, D. Derkachcs, A. Devauxz, D. Di Barie, C. Di Giglioe,10,

S. Di Libertoci, A. Di Mauroan, P. Di Nezzaak, M. Dialinasbs, L. Dıazbj, R. Dıazaw, T. Dietelbr, R. Diviaan,Ø. Djuvslandh, V. Dobretsovbp, A. Dobrinbh, T. Dobrowolskidc, B. Donigusae, I. Domınguezbj, D.M.M. Donat,

O. Dordicby, A.K. Dubeyba, J. Dubuissonan, L. Ducrouxdb, P. Dupieuxz, A.K. Dutta Majumdaraz,M.R. Dutta Majumdarba, D. Eliaf, D. Emschermannar,14, A. Enokizonobv, B. Espagnonbx, M. Estiennebs, S. Esumicx,

D. Evansl, S. Evrardan, G. Eyyubovaby, C.W. Fabjanan,15, D. Fabrisca, J. Faivreao, D. Falchierim, A. Fantoniak,M. Faselae, O. Fateevah, R. Fearickv, A. Fedunovah, D. Fehlkerh, V. Feketeo, D. Feleap, B. Fenton-Olsenab,16,

G. Feofilovcs, A. Fernandez Tellezce, E.G. Ferreirocm, A. Ferretticy, R. Ferrettia,17, M.A.S. Figueredocn,S. Filchaginco, R. Finif, F.M. Fiondae, E.M. Fioree, M. Floriss,10, Z. Fodorr, S. Foertschv, P. Fokaae, S. Fokinbp,

F. Formentian, E. Fragiacomocw, M. Fragkiadakisd, U. Frankenfeldae, A. Frolovbu, U. Fuchsan, F. Furanoan,C. Furgetao, M. Fusco Girardck, J.J. Gaardhøjeab, S. Gadratao, M. Gagliardicy, A. Gagobf, M. Galliocy, P. Ganotid,

M.S. Gantiba, C. Garabatosae, C. Garcıa Trapagacy, J. Gebeleinaq, R. Gemmea, M. Germainbs, A. Gheataan,M. Gheataan, B. Ghidinie, P. Ghoshba, G. Giraudocz, P. Giubellinocz, E. Gladysz-Dziadusac, R. Glasowbr,19,

P. Glasselar, A. Glennbg, R. Gomez Jimenezad, H. Gonzalez Santosce, L.H. Gonzalez-Truebabk,

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P. Gonzalez-Zamorabi, S. Gorbunovaq,2, Y. Gorbunovbw, S. Gotovaccr, H. Gottschlagbr, V. Grabskibk, R. Grajcarekar,A. Grellida, A. Grigorasan, C. Grigorasan, V. Grigorievbo, A. Grigoryandh, S. Grigoryanah, B. Grinyovax, N. Grioncw,

P. Grosbh, J.F. Grosse-Oetringhausan, J.-Y. Grossiorddb, R. Grossoca, F. Guberbm, R. Guernaneao, C. Guerrabf,B. Guerzonim, K. Gulbrandsenab, H. Gulkanyandh, T. Gunjicu, A. Guptaav, R. Guptaav, H.-A. Gustafssonbh,19,

H. Gutbrodae, Ø. Haalandh, C. Hadjidakisbx, M. Haiducp, H. Hamagakicu, G. Hamarr, J. Hamblenay, B.H. Hancp,J.W. Harrisbt, M. Hartigaj, A. Harutyunyandh, D. Haschak, D. Haseganp, D. Hatzifotiadoun, A. Hayrapetyandh,M. Heidebr, M. Heinzbt, H. Helstrupi, A. Herghelegiuq, C. Hernandezae, G. Herrera Corralbl, N. Herrmannar,K.F. Hetlandi, B. Hicksbt, A. Hieias, P.T. Hilleby,20, B. Hippolytect, T. Horaguchias,21, Y. Horicu, P. Hristovan,

I. Hrivnacovabx, S. Hug, M. Huangh, S. Huberae, T.J. Humanicaa, D. Hutterai, D.S. Hwangcp, R. Ichoubs, R. Ilkaevco,I. Ilkiv dc, M. Inabacx, P.G. Innocentian, M. Ippolitovbp, M. Irfanb, C. Ivanda, A. Ivanovcs, M. Ivanovae, V. Ivanovam,T. Iwasakias, A. Jachołkowskian, P. Jacobsj, L. Jancurovaah, S. Jangalct, R. Janiko, C. Jenak, S. Jenabq, L. Jirdenan,

G.T. Jonesl , P.G. Jonesl , P. Jovanovicl, H. Jungal, W. Jungal, A. Juskol , A.B. Kaidalovbn, S. Kalcheraq,2, P. Kalinakbd,M. Kaliskybr, T. Kalliokoskiaw, A. Kalweitaf, A. Kamalb, R. Kamermansda, K. Kanakih, E. Kangal, J.H. Kangcq,J. Kapitancg, V. Kaplinbo, S. Kapustaan, O. Karavichevbm, T. Karavichevabm, E. Karpechevbm, A. Kazantsevbp,

U. Kebschullaq, R. Keideldf, M.M. Khanb, S.A. Khanba, A. Khanzadeevam, Y. Kharlovcd, D. Kikoladd, B. Kilengi,D.J Kimaw, D.S. Kimal, D.W. Kimal, H.N. Kimal, J. Kimcd, J.H. Kimcp, J.S. Kimal, M. Kimal, M. Kimcq, S.H. Kimal,S. Kimcp, Y. Kimcq, S. Kirschan, I. Kiselaq,4, S. Kiselevbn, A. Kisielaa,10, J.L. Klaycl, J. Kleinar, C. Klein-Bosingan,14,M. Kliemantaj, A. Klovningh, A. Klugean, M.L. Knichelae, S. Kniegeaj, K. Kochar, R. Kolevatovby, A. Kolojvarics,V. Kondratievcs, N. Kondratyevabo, A. Konevskihbm, E. Kornasac, R. Kourl, M. Kowalskiac, S. Koxao, K. Kozlovbp,J. Kralcb,11, I. Kralikbd, F. Krameraj, I. Krausaf,4, A. Kravcakovabc, T. Krawutschkebb, M. Krivdal, D. Krumbhornar,

M. Kruscb, E. Kryshenam, M. Krzewickic, Y. Kucheriaevbp, C. Kuhnct, P.G. Kuijerc, L. Kumary, N. Kumary,R. Kupczakdd, P. Kurashvilidc, A. Kurepinbm, A.N. Kurepinbm, A. Kuryakinco, S. Kushpilcg, V. Kushpilcg,

M. Kutouskiah, H. Kvaernoby, M.J. Kweonar, Y. Kwoncq, P. La Roccaw,22, F. Lackneran, P. Ladron de Guevarabi,V. Lafagebx, C. Lalav, C. Laraaq, D.T. Larsenh, G. Laurentin, C. Lazzeronil, Y. Le Bornecbx, N. Le Brisbs, H. Leecf,

K.S. Leeal, S.C. Leeal, F. Lefevrebs, M. Lenhardtbs, L. Leistaman, J. Lehnertaj, V. Lentif, H. Leonbk, I. Leon Monzonad,H. Leon Vargasaj, P. Levair, X. Lig, Y. Lig, R. Lietaval , S. Lindalby, V. Lindenstruthaq,2, C. Lippmannan, M.A. Lisaaa,

L. Liuh, V. Loginovbo, S. Lohnan, X. Lopezz, M. Lopez Noriegabx, R. Lopez-Ramırezce, E. Lopez Torresap,G. Løvhøidenby, A. Lozea Feijo Soarescn, S. Lug, P. Luettigaj, M. Lunardonbz, G. Luparellocy, L. Luquinbs,

J.-R. Lutzct, K. Madg, R. Mabt, D.M. Madagodahettige-Donat, A. Maevskayabm, M. Mageraf,10, D.P. Mahapatrak,A. Mairect, I. Makhlyuevaan, D. Mal’Kevichbn, M. Malaevam, K.J. Malagalagebw, I. Maldonado Cervantesbj,

M. Malekbx, T. Malkiewiczaw, P. Malzacherae, A. Mamonovco, L. Manceauz, L. Mangotraav, V. Mankobp, F. Mansoz,V. Manzarif, Y. Maodg,24, J. Marescc, G.V. Margagliotticv, A. Margottin, A. Marınae, I. Martashviliay, P. Martinengoan,

M.I. Martınez Hernandezce, A. Martınez Davalosbk, G. Martınez Garcıabs, Y. Maruyamaas, A. Marzari Chiesacy,S. Masciocchiae, M. Maseracy, M. Masettim, A. Masonit, L. Massacrierdb, M. Mastromarcof, A. Mastroserioe,10,Z.L. Matthewsl , A. Matyjaac,34, D. Mayanibj, G. Mazzacz, M.A. Mazzonici, F. Meddich, A. Menchaca-Rochabk,P. Mendez Lorenzoan, M. Meonian, J. Mercado Perezar, P. Mereucz, Y. Miakecx, A. Michalonct, N. Miftakhovam,L. Milanocy, J. Milosevicby, F. Minafrae, A. Mischkeda, D. Miskowiecae, C. Mitup, K. Mizoguchias, J. Mlynarzag,B. Mohantyba, L. Molnarr,10, M.M. Mondalba, L. Montano Zetinabl,25, M. Montenocz, E. Montesbi, M. Morandobz,

S. Morettobz, A. Morschan, T. Moukhanovabp, V. Mucciforaak, E. Mudniccr, S. Muhuriba, H. Mulleran,M.G. Munhozcn, J. Munozce, L. Musaan, A. Mussocz, B.K. Nandibq, R. Nanian, E. Nappif, F. Navache, S. Navinl,

T.K. Nayakba, S. Nazarenkoco, G. Nazarovco, A. Nedosekinbn, F. Nendazdb, J. Newbybg, A. Nianinebp,M. Nicassiof,10, B.S. Nielsenab, S. Nikolaevbp, V. Nikolicdi, S. Nikulinbp, V. Nikulinam, B.S. Nilsenbw,

M.S. Nilssonby, F. Noferinin, P. Nomokonovah, G. Noorenda, N. Novitzkyaw, A. Nyathabq, C. Nygaardab, A. Nyiriby,J. Nystrandh, A. Ochirovcs, G. Odyniecj, H. Oeschleraf, M. Oinonenaw, K. Okadacu, Y. Okadaas, M. Oldenburgan,

J. Oleniaczdd, C. Oppedisanocz, F. Orsinicj, A. Ortiz Velasquezbj, G. Ortonacy, A. Oskarssonbh, F. Osmican,L. Ostermanbh, P. Ostrowskidd, I. Otterlundbh, J. Otwinowskiae, G. Øvrebekkh, K. Oyamaar, K. Ozawacu,

Y. Pachmayerar, M. Pachrcb, F. Padillacy, P. Paganock, G. Paicbj, F. Painkeaq, C. Pajarescm, S. Palaz,27, S.K. Palba,A. Palahal, A. Palmerix, R. Panseaq, V. Papikyandh, G.S. Pappalardox, W.J. Parkae, B. Pastircakbd, C. Pastoref,

V. Paticchiof, A. Pavlinovag, T. Pawlakdd, T. Peitzmannda, A. Pepatoca, H. Pereiracj, D. Peressounkobp, C. Perezbf,D. Perinian, D. Perrinoe,10, W. Perytdd, J. Peschekaq,2, A. Pescin, V. Peskovbj,10, Y. Pestovbu, A.J. Petersan,

V. Petracekcb, A. Petridisd,19, M. Petrisq, P. Petrovl, M. Petroviciq, C. Pettaw, J. Peyrebx, S. Pianocw, A. Piccotticz,M. Piknao, P. Pillotbs, O. Pinazzan,10, L. Pinskyat, N. Pitzaj, F. Piuzan, R. Plattl , M. Płoskonj, J. Plutadd,

2

T. Pocheptsovah,28, S. Pochybovar, P.L.M. Podesta Lermaad, F. Poggiocy, M.G. Poghosyancy, K. Polakcc,B. Polichtchoukcd, P. Polozovbn, V. Polyakovam, B. Pommereschh, A. Popq, F. Posae, V. Pospısilcb, B. Potukuchiav,

J. Pouthasbx, S.K. Prasadba, R. Preghenellam,22, F. Prinocz, C.A. Pruneauag, I. Pshenichnovbm, G. Puddus,P. Pujaharibq, A. Pulvirentiw, A. Puninco, V. Puninco, M. Putisbc, J. Putschkebt, E. Quercighan, A. Rachevskicw,

A. Rademakersan, S. Radomskiar, T.S. Raihaaw, J. Rakaw, A. Rakotozafindrabecj, L. Ramelloa, A. Ramırez Reyesbl,M. Rammlerbr, R. Raniwalaau, S. Raniwalaau, S.S. Rasanenaw, I. Rashevskayacw, S. Rathk, K.F. Readay, J.S. Realao,

K. Redlichdc,41, R. Renfordtaj, A.R. Reolonak, A. Reshetinbm, F. Rettigaq,2, J.-P. Revolan, K. Reygersbr,29, H. Ricaudaf,L. Riccaticz, R.A. Riccibe, M. Richterh, P. Riedleran, W. Riegleran, F. Riggiw, A. Rivetticz, M. Rodriguez Cahuantzice,K. Røedi , D. Rohrichan,31, S. Roman Lopezce, R. Romitae,4, F. Ronchettiak, P. Rosinskyan, P. Rosnetz, S. Rosseggeran,A. Rossicv,42, F. Roukoutakisan,32, S. Rousseaubx, C. Roybs,12, P. Royaz, A.J. Rubio-Monterobi, R. Ruicv, I. Rusanovar,G. Russock, E. Ryabinkinbp, A. Rybickiac, S. Sadovskycd, K. Safarıkan, R. Sahoobz, J. Sainiba, P. Saizan, D. Sakatacx,

C.A. Salgadocm, R. Salgueiro Domingues da Silvaan, S. Salurj , T. Samantaba, S. Sambyalav, V. Samsonovam,L. Sandorbd, A. Sandovalbk, M. Sanocx, S. Sanocu, R. Santobr, R. Santoroe, J. Sarkamoaw, P. Saturniniz,

E. Scapparonen, F. Scarlassarabz, R.P. Scharenbergde, C. Schiauaq, R. Schickerar, H. Schindleran, C. Schmidtae,H.R. Schmidtae, K. Schossmaieran, S. Schreineran, S. Schuchmannaj, J. Schukraftan, Y. Schutzbs, K. Schwarzae,

K. Schwedaar, G. Sciolim, E. Scomparincz, P.A. Scottl , G. Segatobz, D. Semenovcs, S. Senyukova, J. Seoal, S. Sercis,L. Serkinbj, E. Serradillabi, A. Sevcencop, I. Sgurae, G. Shabratovaah, R. Shahoyanan, G. Sharkovbn, N. Sharmay,S. Sharmaav, K. Shigakias, M. Shimomuracx, K. Shtejerap, Y. Sibiriakbp, M. Sicilianocy, E. Sickingan,33, E. Siddit,

T. Siemiarczukdc, A. Silenzim, D. Silvermyrbv, E. Similida, G. Simonettie,10, R. Singarajuba, R. Singhav, V. Singhalba,B.C. Sinhaba, T. Sinhaaz, B. Sitaro, M. Sittaa, T.B. Skaaliby, K. Skjerdalh, R. Smakalcb, N. Smirnovbt, R. Snellingsc,H. Snowl , C. Søgaardab, A. Solovievcd, H.K. Soltveitar, R. Soltzbg, W. Sommeraj, C.W. Soncf, H. Soncp, M. Songcq,

C. Soosan, F. Soramelbz, D. Soykae, M. Spyropoulou-Stassinakid, B.K. Srivastavade, J. Stachelar, F. Staleycj, E. Stanp,G. Stefanekdc, G. Stefaninian, T. Steinbeckaq,2, E. Stenlundbh, G. Steynv, D. Stoccocy,34, R. Stockaj, P. Stolpovskycd,

P. Strmeno, A.A.P. Suaidecn, M.A. Subieta Vasquezcy, T. Sugitateas, C. Suirebx, M. Sumberacg, T. Susadi,D. Swobodaan, J. Symonsj, A. Szanto de Toledocn, I. Szarkao, A. Szostakt, M. Szubadd, M. Tadelan, C. Tagridisd,

A. Takaharacu, J. Takahashiu, R. Tanabecx, J.D. Tapia Takakibx, H. Tauregan, A. Tauroan, M. Tavletan,G. Tejeda Munozce, A. Telescaan, C. Terrevolie, J. Thaderaq,2, R. Tieulentdb, D. Tlustycb, A. Toiaan, T. Tolyhyr,

C. Torcato de Matosan, H. Toriias, G. Torralbaaq, L. Toscanocz, F. Tosellocz, A. Tournairebs,35, T. Traczykdd,P. Tribedyba, G. Trogeraq, D. Truesdaleaa, W.H. Trzaskaaw, G. Tsiledakisar, E. Tsilisd, T. Tsujicu, A. Tumkinco,

R. Turrisica, A. Turveybw, T.S. Tveterby, H. Tydesjoan, K. Tywoniukby, J. Uleryaj, K. Ullalandh, A. Urass, J. Urbanbc,G.M. Urciuolici, G.L. Usais, A. Vacchicw, M. Valaah,9, L. Valencia Palomobk, S. Valleroar, N. van der Kolkc,

P. Vande Vyvrean, M. van Leeuwenda, L. Vannuccibe, A. Vargasce, R. Varmabq, A. Vasilievbp, I. Vassilievaq,32,M. Vasileioud, V. Vechernincs, M. Venaruzzocv, E. Vercellincy, S. Vergarace, R. Vernetw,36, M. Verweijda,

I. Vetlitskiybn, L. Vickoviccr, G. Viestibz, O. Vikhlyantsevco, Z. Vilakaziv, O. Villalobos Bailliel , A. Vinogradovbp,L. Vinogradovcs, Y. Vinogradovco, T. Virgili ck, Y.P. Viyogiba, A. Vodopianovah, K. Voloshinbn, S. Voloshinag,G. Volpee, B. von Halleran, D. Vranicae, J. Vrlakovabc, B. Vulpescuz, B. Wagnerh, V. Wagnercb, L. Walletan,

R. Wandg,12, D. Wangdg, Y. Wangar, Y. Wangdg, K. Watanabecx, Q. Weng, J. Wesselsbr, U. Westerhoffbr, J. Wiechulaar,J. Wikneby, A. Wilk br, G. Wilkdc, M.C.S. Williamsn, N. Willisbx, B. Windelbandar, C. Xudg, C. Yangdg, H. Yangar,

S. Yasnopolskiybp, F. Yermiabs, J. Yicf, Z. Yindg, H. Yokoyamacx, I-K. Yoocf, X. Yuandg,38, V. Yurevichah,I. Yushmanovbp, E. Zabrodinby, B. Zagreevbn, A. Zaliteam, C. Zampollian,39, Yu. Zanevskyah, S. Zaporozhetsah,

A. Zarochentsevcs, P. Zavadacc, H. Zbroszczykdd, P. Zelnicekaq, A. Zenincd, A. Zepedabl, I. Zgurap, M. Zhalovam,X. Zhangdg,1, D. Zhoudg, S. Zhoug, J. Zhudg, A. Zichichim,22, A. Zinchenkoah, G. Zinovjevax, Y. Zoccaratodb,

V. Zychacekcb, M. Zynovyevax

aDipartimento di Scienze e Tecnologie Avanzate dell’Universita del Piemonte Orientale and Gruppo Collegato INFN, Alessandria, ItalybDepartment of Physics Aligarh Muslim University, Aligarh,India

cNikhef, National Institute for Subatomic Physics, Amsterdam, NetherlandsdPhysics Department, University of Athens, Athens, Greece

eDipartimento Interateneo di Fisica ‘M. Merlin’ and SezioneINFN, Bari, ItalyfSezione INFN, Bari, Italy

gChina Institute of Atomic Energy, Beijing, ChinahDepartment of Physics and Technology, University of Bergen, Bergen, Norway

iFaculty of Engineering, Bergen University College, Bergen, NorwayjLawrence Berkeley National Laboratory, Berkeley, CA, United States

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kInstitute of Physics, Bhubaneswar, IndialSchool of Physics and Astronomy, University of Birmingham,Birmingham, United Kingdom

mDipartimento di Fisica dell’Universita and Sezione INFN,Bologna, ItalynSezione INFN, Bologna, Italy

oFaculty of Mathematics, Physics and Informatics, ComeniusUniversity, Bratislava, SlovakiapInstitute of Space Sciences (ISS), Bucharest, Romania

qNational Institute for Physics and Nuclear Engineering, Bucharest, RomaniarKFKI Research Institute for Particle and Nuclear Physics, Hungarian Academy of Sciences, Budapest, Hungary

sDipartimento di Fisica dell’Universita and Sezione INFN,Cagliari, ItalytSezione INFN, Cagliari, Italy

uUniversidade Estadual de Campinas (UNICAMP), Campinas, BrazilvPhysics Department, University of Cape Town, iThemba Laboratories, Cape Town, South Africa

wDipartimento di Fisica e Astronomia dell’Universita and Sezione INFN, Catania, ItalyxSezione INFN, Catania, Italy

yPhysics Department, Panjab University, Chandigarh, IndiazLaboratoire de Physique Corpusculaire (LPC), Clermont Universite, Universite Blaise Pascal, CNRS–IN2P3, Clermont-Ferrand, France

aaDepartment of Physics, Ohio State University, Columbus, OH, United StatesabNiels Bohr Institute, University of Copenhagen, Copenhagen, Denmark

acThe Henryk Niewodniczanski Institute of Nuclear Physics, Polish Academy of Sciences, Cracow, PolandadUniversidad Autonoma de Sinaloa, Culiacan, Mexico

aeResearch Division and ExtreMe Matter Institute EMMI, GSI Helmholtzzentrum fur Schwerionenforschung, Darmstadt, GermanyafInstitut fur Kernphysik, Technische Universitat Darmstadt, Darmstadt, Germany

agWayne State University, Detroit, MI, United StatesahJoint Institute for Nuclear Research (JINR), Dubna, Russia

aiFrankfurt Institute for Advanced Studies, Johann WolfgangGoethe-Universitat Frankfurt, Frankfurt, GermanyajInstitut fur Kernphysik, Johann Wolfgang Goethe-Universitat Frankfurt, Frankfurt, Germany

akLaboratori Nazionali di Frascati, INFN, Frascati, ItalyalGangneung-Wonju National University, Gangneung, South Korea

amPetersburg Nuclear Physics Institute, Gatchina, RussiaanEuropean Organization for Nuclear Research (CERN), Geneva, Switzerland

aoLaboratoire de Physique Subatomique et de Cosmologie (LPSC), Universite Joseph Fourier, CNRS-IN2P3, Institut Polytechnique de Grenoble,Grenoble, France

apCentro de Aplicaciones Tecnologicas y Desarrollo Nuclear(CEADEN), Havana, CubaaqKirchhoff-Institut fur Physik, Ruprecht-Karls-Universitat Heidelberg, Heidelberg, Germany

arPhysikalisches Institut, Ruprecht-Karls-Universitat Heidelberg, Heidelberg, GermanyasHiroshima University, Hiroshima, Japan

atUniversity of Houston, Houston, TX, United StatesauPhysics Department, University of Rajasthan, Jaipur, India

avPhysics Department, University of Jammu, Jammu, IndiaawHelsinki Institute of Physics (HIP) and University of Jyvaskyla, Jyvaskyla, Finland

axBogolyubov Institute for Theoretical Physics, Kiev, UkraineayUniversity of Tennessee, Knoxville, TN, United States

azSaha Institute of Nuclear Physics, Kolkata, IndiabaVariable Energy Cyclotron Centre, Kolkata, India

bbFachhochschule Koln, Koln, GermanybcFaculty of Science, P.J.Safarik University, Kosice, Slovakia

bdInstitute of Experimental Physics, Slovak Academy of Sciences, Kosice, SlovakiabeLaboratori Nazionali di Legnaro, INFN, Legnaro, Italy

bfSeccion Fısica, Departamento de Ciencias, Pontificia Universidad Catolica del Peru, Lima, PerubgLawrence Livermore National Laboratory, Livermore, CA, United States

bhDivision of Experimental High Energy Physics, University of Lund, Lund, SwedenbiCentro de Investigaciones Energeticas Medioambientalesy Tecnologicas (CIEMAT), Madrid, SpainbjInstituto de Ciencias Nucleares, Universidad Nacional Autonoma de Mexico, Mexico City, Mexico

bkInstituto de Fısica, Universidad Nacional Autonoma de M´exico, Mexico City, MexicoblCentro de Investigacion y de Estudios Avanzados (CINVESTAV), Mexico City and Merida, Mexico

bmInstitute for Nuclear Research, Academy of Sciences, Moscow, RussiabnInstitute for Theoretical and Experimental Physics, Moscow, Russia

boMoscow Engineering Physics Institute, Moscow, RussiabpRussian Research Centre Kurchatov Institute, Moscow, Russia

bqIndian Institute of Technology, Mumbai, IndiabrInstitut fur Kernphysik, Westfalische Wilhelms-Universitat Munster, Munster, Germany

bsSUBATECH, Ecole des Mines de Nantes, Universite de Nantes,CNRS-IN2P3, Nantes, FrancebtYale University, New Haven, CT, United States

buBudker Institute for Nuclear Physics, Novosibirsk, RussiabvOak Ridge National Laboratory, Oak Ridge, TN, United States

4

bwPhysics Department, Creighton University, Omaha, NE, United StatesbxInstitut de Physique Nucleaire d’Orsay (IPNO), Universite Paris-Sud, CNRS-IN2P3, Orsay, France

byDepartment of Physics, University of Oslo, Oslo, NorwaybzDipartimento di Fisica dell’Universita and Sezione INFN,Padova, Italy

caSezione INFN, Padova, ItalycbFaculty of Nuclear Sciences and Physical Engineering, Czech Technical University in Prague, Prague, Czech Republic

ccInstitute of Physics, Academy of Sciences of the Czech Republic, Prague, Czech RepubliccdInstitute for High Energy Physics, Protvino, Russia

ceBenemerita Universidad Autonoma de Puebla, Puebla, MexicocfPusan National University, Pusan, South Korea

cgNuclear Physics Institute, Academy of Sciences of the CzechRepublic,Rez u Prahy, Czech RepublicchDipartimento di Fisica dell’Universita ‘La Sapienza’ andSezione INFN, Rome, Italy

ciSezione INFN, Rome, ItalycjCommissariat a l’Energie Atomique, IRFU, Saclay, France

ckDipartimento di Fisica ‘E.R. Caianiello’ dell’Universit`a and Sezione INFN, Salerno, ItalyclCalifornia Polytechnic State University, San Luis Obispo,CA, United States

cmDepartamento de Fısica de Partıculas and IGFAE, Universidad de Santiago de Compostela, Santiago de Compostela, SpaincnUniversidade de Sao Paulo (USP), Sao Paulo, Brazil

coRussian Federal Nuclear Center (VNIIEF), Sarov, RussiacpDepartment of Physics, Sejong University, Seoul, South Korea

cqYonsei University, Seoul, South KoreacrTechnical University of Split FESB, Split, Croatia

csV. Fock Institute for Physics, St. Petersburg State University, St. Petersburg, RussiactInstitut Pluridisciplinaire Hubert Curien (IPHC), Universite de Strasbourg, CNRS-IN2P3, Strasbourg, France

cuUniversity of Tokyo, Tokyo, JapancvDipartimento di Fisica dell’Universita and Sezione INFN,Trieste, Italy

cwSezione INFN, Trieste, ItalycxUniversity of Tsukuba, Tsukuba, Japan

cyDipartimento di Fisica Sperimentale dell’Universita andSezione INFN, Turin, ItalyczSezione INFN, Turin, Italy

daNikhef, National Institute for Subatomic Physics and Institute for Subatomic Physics of Utrecht University, Utrecht,NetherlandsdbUniversite de Lyon, Universite Lyon 1, CNRS/IN2P3, IPN-Lyon, Villeurbanne, France

dcSoltan Institute for Nuclear Studies, Warsaw, PolandddWarsaw University of Technology, Warsaw, Poland

dePurdue University, West Lafayette, IN, United StatesdfZentrum fur Technologietransfer und Telekommunikation (ZTT), Fachhochschule Worms, Worms, Germany

dgHua-Zhong Normal University, Wuhan, ChinadhYerevan Physics Institute, Yerevan, ArmeniadiRudjer Boskovic Institute, Zagreb, Croatia

Abstract

The inclusive charged particle transverse momentum distribution is measured in proton-proton collisions at√

s =900 GeV at the LHC using the ALICE detector. The measurement is performed in the central pseudorapidity region(|η| < 0.8) over the transverse momentum range 0.15 < pT < 10 GeV/c. The correlation between transverse mo-mentum and particle multiplicity is also studied. Results are presented for inelastic (INEL) and non-single-diffractive(NSD) events. The average transverse momentum for|η| < 0.8 is〈pT〉 INEL = 0.483±0.001 (stat.)±0.007 (syst.) GeV/cand〈pT〉 NSD = 0.489± 0.001 (stat.)±0.007 (syst.) GeV/c, respectively. The data exhibit a slightly larger〈pT〉 thanmeasurements in wider pseudorapidity intervals. The results are compared to simulations with the Monte Carlo eventgenerators PYTHIA and PHOJET.

Preprint submitted to Physics Letters B August 20, 2010

1. Introduction

The precise measurement of the transverse momen-tum spectrum of charged particles produced in protoncollisions in the energy range of the Large Hadron Col-lider (LHC) [1] offers unique information about softand hard interactions. Perturbative Quantum Chromo-dynamics (pQCD) is a framework for the quantitativedescription of parton-parton interactions at large mo-mentum transfers, i.e. hard scattering processes. How-ever, a significant fraction of the particles produced inpp collisions do not originate from hard interactions,even at LHC energies. In contrast to hard processes,the description of particle production in soft interactionsis not well-established within QCD. Current models of

hadron-hadron collisions at high energies, such as theevent generators PYTHIA [2] and PHOJET [3], com-bine perturbative QCD for the description of hard par-ton interactions with phenomenological approaches tomodel the soft component of the produced particle spec-trum. Data on charged particle production in hadron-hadron collisions will have to be used to tune these mod-els before they can provide a detailed description of theexisting measurements and predictions for particle pro-duction characteristics inpp collisions at the highestLHC energies. These data include the measurement ofmultiplicity, pseudorapidity (η) and transverse momen-tum (pT) distributions of charged particles and correla-tions, such as the dependence of the average transversemomentum,〈pT〉, on the charged particle multiplicity.

1Also at Laboratoire de Physique Corpusculaire (LPC), Clermont Universite, Universite Blaise Pascal, CNRS–IN2P3, Clermont-Ferrand, France2Also at Frankfurt Institute for Advanced Studies, Johann Wolfgang Goethe-Universitat Frankfurt, Frankfurt, Germany3Now at Sezione INFN, Padova, Italy4Now at Research Division and ExtreMe Matter Institute EMMI,GSI Helmholtzzentrum fur Schwerionenforschung, Darmstadt, Germany5Now at Institut fur Kernphysik, Johann Wolfgang Goethe-Universitat Frankfurt, Frankfurt, Germany6Now at Physics Department, University of Cape Town, iThembaLaboratories, Cape Town, South Africa7Now at National Institute for Physics and Nuclear Engineering, Bucharest, Romania8Also at University of Houston, Houston, TX, United States9Now at Faculty of Science, P.J.Safarik University, Kosice, Slovakia

10Now at European Organization for Nuclear Research (CERN), Geneva, Switzerland11Now at Helsinki Institute of Physics (HIP) and University ofJyvaskyla, Jyvaskyla, Finland12Now at Institut Pluridisciplinaire Hubert Curien (IPHC), Universite de Strasbourg, CNRS-IN2P3, Strasbourg, France13Now at Sezione INFN, Bari, Italy14Now at Institut fur Kernphysik, Westfalische Wilhelms-Universitat Munster, Munster, Germany15Now at: University of Technology and Austrian Academy of Sciences, Vienna, Austria16Also at Lawrence Livermore National Laboratory, Livermore, CA, United States17Also at European Organization for Nuclear Research (CERN),Geneva, Switzerland18Now at Seccion Fısica, Departamento de Ciencias, Pontificia Universidad Catolica del Peru, Lima, Peru19Deceased20Now at Yale University, New Haven, CT, United States21Now at University of Tsukuba, Tsukuba, Japan22Also at Centro Fermi – Centro Studi e Ricerche e Museo Storicodella Fisica “Enrico Fermi”, Rome, Italy23Now at Dipartimento Interateneo di Fisica ‘M. Merlin’ and Sezione INFN, Bari, Italy24Also at Laboratoire de Physique Subatomique et de Cosmologie (LPSC), Universite Joseph Fourier, CNRS-IN2P3, Institut Polytechnique de

Grenoble, Grenoble, France25Now at Dipartimento di Fisica Sperimentale dell’Universita and Sezione INFN, Turin, Italy26Now at Physics Department, Creighton University, Omaha, NE, United States27Now at Commissariat a l’Energie Atomique, IRFU, Saclay, France28Also at Department of Physics, University of Oslo, Oslo, Norway29Now at Physikalisches Institut, Ruprecht-Karls-Universitat Heidelberg, Heidelberg, Germany30Now at Institut fur Kernphysik, Technische Universitat Darmstadt, Darmstadt, Germany31Now at Department of Physics and Technology, University of Bergen, Bergen, Norway32Now at Physics Department, University of Athens, Athens, Greece33Also at Institut fur Kernphysik, Westfalische Wilhelms-Universitat Munster, Munster, Germany34Now at SUBATECH, Ecole des Mines de Nantes, Universite de Nantes, CNRS-IN2P3, Nantes, France35Now at Universite de Lyon, Universite Lyon 1, CNRS/IN2P3, IPN-Lyon, Villeurbanne, France36Now at: Centre de Calcul IN2P3, Lyon, France37Now at Variable Energy Cyclotron Centre, Kolkata, India38Also at Dipartimento di Fisica dell’Universita and Sezione INFN, Padova, Italy39Also at Sezione INFN, Bologna, Italy40Also at Dipartimento di Fisica dell´Universita, Udine, Italy41Also at Wrocław University, Wrocław, Poland42Now at Dipartimento di Fisica dell’Universita and SezioneINFN, Padova, Italy

6

The charged particle pseudorapidity densities andmultiplicity distributions inpp collisions at

√s = 0.9,

2.36 and 7 TeV were presented in recent publicationsby the ALICE collaboration [4, 5, 6]. In this letter,we present a measurement inpp collisions at

√s =

900 GeV of the transverse momentum spectrum ofprimary charged particles and the correlation between〈pT〉 and the charged particle multiplicity. Primaryparticles include particles produced in the collision ortheir decay products, except those from weak decays ofstrange hadrons. The measurement is performed in thecentral rapidity region (|η| < 0.8) and covers apT range0.15 < pT < 10 GeV/c, where both hard and soft pro-cesses are expected to contribute to particle production.The data from the ALICE experiment presented in thisletter serve as a baseline for future studies ofpp colli-sions at higher LHC energies and particle production inheavy-ion collisions [7].

2. Experiment and data collection

The data were collected with the ALICE detec-tor [8] during the startup phase of the LHC in December2009. The ALICE detector, designed to cope with hightrack densities in heavy-ion collisions, provides excel-lent track reconstruction and particle identification ca-pabilities. This also makes the detector well-suited todetailed studies of global characteristics ofpp interac-tions [7].

In this analysis of the firstpp collisions at√

s =900 GeV, charged particle tracking and momentum re-construction are based on data recorded with the TimeProjection Chamber (TPC) and the Inner Tracking Sys-tem (ITS), both located in the central barrel of ALICE.The detectors in the central barrel are operated inside alarge solenoidal magnet providing a uniform 0.5 T field.

The ALICE TPC [9] is a large cylindrical drift de-tector with a central high voltage membrane maintainedat −100 kV and two readout planes at the end-caps.The active volume is limited to 85< r < 247 cm and−250 < z < 250 cm in the radial and longitudinaldirections respectively. The material budget betweenthe interaction point and the active volume of the TPCcorresponds to 11% of a radiation length, averaged in|η| < 0.8. The central membrane atz = 0 divides thenearly 90 m3 active volume into two halves. The ho-mogeneous drift field of 400 V/cm in the Ne-CO2-N2

(85.7%-9.5%-4.8%) gas mixture leads to a maximumdrift time of 94 µs. Ionization electrons produced bycharged particles traversing the TPC drift towards thereadout end-caps composed of 72 multi-wire propor-tional chambers with cathode pad readout. The typi-

cal gas gain is 104. Signals induced on the segmentedcathode planes, comprising a total of 558k readout pads,are transformed into differential semi-gaussian signalsby a charge-sensitive shaping amplifier (PASA). This isfollowed by the ALICE TPC ReadOut (ALTRO) chip,which employs a 10 bit ADC at 10 MHz sampling rateand four digital filtering circuits. These filters also per-form tail cancellation and baseline restoration. They areoptimized for precise position and dE/dx measurementsin the high track density environment of heavy-ion colli-sions. To ensure optimal drift and charge transport prop-erties, the TPC was operated with an overall tempera-ture uniformity of∆T ≈ 60 mK (r.m.s.). The oxygencontamination was less than 5 ppm.

The ITS is composed of high resolution silicontracking detectors, arranged in six cylindrical layers atradial distances to the beam line from 3.9 to 43 cm.Three different technologies are employed.

For the two innermost layers Silicon Pixel Detec-tors (SPD) are used, covering the pseudorapidity ranges|η| < 2 and|η| < 1.4, respectively. A total of 9.8 mil-lion 50× 425 µm2 pixels enable the reconstruction ofthe primary event vertex and the track impact parame-ters with high precision. The SPD was also included inthe trigger scheme for data collection.

The SPD is followed by two Silicon Drift Detec-tor (SDD) layers with a total of 133k readout channels,sampling the drift time information at a frequency of20 MHz. The SDD are operated with a drift field of500 V/cm, resulting in a drift speed of about 6.5µm/nsand in a maximum drift time of about 5.3µs.

The two outermost Silicon Strip Detector (SSD) lay-ers consist of double-sided silicon micro-strip sensorswith 95µm pitch, comprising a total of 2.6 million read-out channels. Strips of the two sensor sides form astereo angle of 35 mrad, providing two-dimensional hitreconstruction.

The design spatial resolutions of the ITS sub-detectors (σrφ × σz) are: 12× 100 µm2 for SPD,35× 25µm2 for SDD, and 20× 830µm2 for SSD. TheSPD and SSD detectors were aligned using survey mea-surements, cosmic muon data [10] and collision data toan estimated accuracy of 10µm for the SPD and 15µmfor the SSD. No alignment corrections are applied to thepositions of the SDD modules, for which calibration andalignment are in progress. The estimated misalignmentof the SDD modules is about 100µm. The TPC andITS are aligned relative to each other to the level of afew hundred micrometers using cosmic-ray andppdataby comparing pairs of track segments independently re-constructed in the two detectors.

The two forward scintillator hodoscopes (VZERO)

7

are included in the trigger. Each detector is segmentedinto 32 scintillator counters which are arranged in fourrings around the beam pipe. They are located at dis-tancesz = 3.3 m andz = −0.9 m from the nominalinteraction point and cover the pseudorapidity ranges:2.8 < η < 5.1 and−3.7 < η < −1.7 respectively. Thetime resolution of about 1 ns of the VZERO hodoscopealso allows for a discrimination against beam-gas inter-actions.

During the startup phase of the LHC in 2009,four proton bunches per beam were circulating in theLHC with two pairs of bunches crossing at the AL-ICE intersection region and protons colliding at

√s =

900 GeV. The detector readout was triggered using theLHC bunch-crossing signals in coincidence with signalsfrom the two upstream beam pick-up counters and aminimum-bias interaction trigger requiring a signal in atleast one of the SPD pixels or one of the VZERO coun-ters [4, 5]. Events with only one bunch or no bunchespassing through ALICE were also recorded to studybeam related and random background.

3. Data analysis

The total inelasticpp cross section is commonlysubdivided into contributions from diffractive and non-diffractive processes. To facilitate comparison withexisting measurements, we perform our analysis fortwo classes of events: inelastic (INEL) and non-single-diffractive (NSD)pp collisions.

In this analysis, 3.44× 105 triggeredpp events at√s = 900 GeV are analyzed. To remove beam related

background events, an offline event selection based onthe VZERO timing signal and the correlation betweenthe number of hits and tracklets in the SPD is applied asin [5], reducing the sample to 2.67× 105 events. Thisevent selection is refered to as MBOR [5].

For the INEL analysis we use the event sample se-lected with the MBOR condition. A subset of theseevents (2.15× 105) is used for the NSD analysis, se-lected offline by requiring a coincidence between thetwo VZERO detectors (the MBAND selection). Thiscondition suppresses a significant fraction of the single-diffractive events and hence reduces the systematic er-rors related to model dependent corrections [5].

The fractions of the different process types con-tributing to the selected event samples are estimated bya Monte Carlo simulation, implementing a descriptionof the ALICE detector response [11] topp collisionsat√

s = 900 GeV from the PYTHIA event generatorversion 6.4.21 tune D6T (109) [12]. The process frac-tions of single-diffractive (SD) and double-diffractive

(DD) events are scaled in Monte Carlo to match thecross sections inpp at

√s = 900 GeV measured by

UA5 [13]. The selection efficiency for INEL events us-ing MBOR and NSD events using MBAND is approxi-mately 96% and 93%, respectively [5].

Charged particle tracks are reconstructed using in-formation from the TPC and ITS detector systems. Sig-nals on adjacent pads in the TPC are connected to parti-cle tracks by employing a Kalman filter algorithm. TheTPC tracks are extrapolated to the ITS and matching hitsin the ITS detector layers are assigned to the track. Inorder to maximize the hit matching efficiency and avoidpossible biases of the track parameters due to the non-uniform degree of alignment of the ITS sub-detectors,the space point uncertainties of the ITS hits are set to100µm for SPD and 1 mm for both SDD and SSD.

The event vertex is reconstructed using the com-bined track information from TPC and ITS. The tracksare extrapolated to the intersection region and the po-sition of the event vertex is fitted, using the measuredaverage intersection profile as a constraint. The profileof the intersection region is determined on a run-by-runbasis in a first pass through the data using the mean andthe spread of the distribution of the reconstructed ver-tices. The event vertex distribution is found to be Gaus-sian with standard deviations of approximately 210µm,250µm, and 4.1 cm, alongx, y (transverse to the beam-axis) andzrespectively. For events where only one trackis found, the vertex is determined from the point of clos-est approach of the track to the beam axis. If no trackis found in the TPC, the event vertex reconstruction isbased on tracklets built by associating pairs of hits of thetwo innermost ITS layers (SPD). An event with a recon-structed vertex positionzv is accepted if|zv−z0| < 10 cm,corresponding to about 2.5 standard deviations of the re-constructed event vertex distribution centered atz0 [5].

The vertex position resolution depends on theevent multiplicity. It can be parametrized as540µm/(NSPD)0.45 in x andy, and 550µm/(NSPD)0.6 inz, whereNSPD corresponds to the number of SPD track-lets. This resolution is consistent with Monte Carlo sim-ulations. The probability of multiple interactions in thesame bunch crossing (pile-up) in the present data set is10−4 and therefore neglected.

The fraction of selected events in theMBOR (MBAND ) sample where an event vertex is suc-cessfully reconstructed is 80% (92%), resulting in asample of 2.13 × 105 INEL (1.98× 105 NSD) eventsused in the present analysis. Events, where no vertexis found, are included when normalizing the results.In order to understand and to subtract possible beam-induced background, the detector was also triggered

8

on bunches coming from either side of the interactionregion, but not colliding with another bunch. Fromthe study of these events we estimate that 21% of thetriggered MBOR and MBAND events without a recon-structed event vertex or with zero selected tracks arebackground, and the number of events used for normal-ization of the final results is corrected accordingly. Theestimated contribution from beam-induced backgroundevents to the event sample, where a vertex was found, isnegligible. From the analysis of empty bunch crossingevents the random contribution from cosmics and noisetriggers is also found to be negligible.

To study the transverse momentum spectrum,charged particle tracks are selected in the pseudorapid-ity range |η| < 0.8. In this range, tracks in the TPCcan be reconstructed with maximal length, and thereare minimal efficiency losses due to detector bound-aries. Additional quality requirements are applied toensure high tracking resolution and low secondary andfake track contamination. A track is accepted if it hasat least 70 out of the maximum of 159 space points inthe TPC, and theχ2 per space point used for the mo-mentum fit is less than 4. Additionally, at least twohits in the ITS must be associated with the track, andat least one has to be in either of the two innermost lay-ers, i.e., in the SPD. The average number of associatedhits per track in the six ITS layers is 4.7, mainly deter-mined by the fraction of inactive channels, and is wellreproduced in Monte Carlo simulations. Tracks withpT < 0.15 GeV/c are excluded because their recon-struction efficiency drops below 50%. Tracks are alsorejected as not associated to the primary vertex if theirdistance of closest approach to the reconstructed eventvertex in the plane perpendicular to the beam axis,d0,satisfiesd0 > 0.35 mm+ 0.42 mm× p−0.9

T , with pT inGeV/c. This cut corresponds to about seven standarddeviations of thepT dependent transverse impact pa-rameter resolution for primary tracks passing the aboveselection. It is tuned to select primary charged particleswith high efficiency and to minimize the contributionsfrom weak decays, conversions and secondary hadronicinteractions in the detector material. The accepted num-ber of charged particles per event which fulfill theseconditions is callednacc.

With this selection, the reconstruction efficiency forprimary charged particles and the remaining contamina-tion from secondaries as a function ofpT are estimatedby Monte Carlo simulation using PYTHIA, combinedwith detector simulation and event reconstruction. Theprocedure estimates losses due to tracking inefficiency,charged particles escaping detection due to weak de-cay, absorption and secondary interaction in the detec-

tor. The inefficiencies of the event selection and of theevent vertex reconstruction are accounted for. The lat-ter two affect mostly low-multiplicity events, which im-poses a bias on the uncorrectedpT spectrum due to thecorrelation between multiplicity and average momen-tum.

effic

ienc

y0.4

0.6

0.8

1

positivesnegatives

(GeV/c)T

p-110 1 10

cont

amin

atio

n

0

0.05

0.1

positivesnegatives

Figure 1: Charged-particle track reconstruction efficiency for primaryparticles (top) and contamination from secondary particles (bottom),for positively and negatively charged particles in|η| < 0.8 as a func-tion of pT . The tracking efficiency is normalized to the number ofgenerated primary particles using PYTHIA. The contamination fromsecondary tracks was scaled in Monte Carlo to match the measuredd0distributions (see text).

The primary charged particle track reconstructionefficiency in the region|η| < 0.8 reaches 75% atpT ∼1 GeV/c, as shown in Fig. 1. The slight decrease of effi-ciency observed forpT > 1.5 GeV/c is a consequence ofthe projective segmentation of the readout plane in az-imuth, causing stiff tracks to remain undetected if theyfall between two adjacent TPC readout sectors. ForpT < 0.6 GeV/c, the reconstruction efficiency decreasesand reaches 50% at 0.15 GeV/c. The losses at lowpT are mainly due to energy loss in the detector ma-terial and to the track bending in the magnetic field. Nosignificant dependence of the track reconstruction effi-ciency on the track density is observed in simulationsfor charged particle multiplicities relevant for this anal-ysis. The contamination from secondary particles such

9

as charged particles from weak decays, electrons fromphoton conversions, and products from secondary inter-actions in the detector material is also shown in Fig. 1.It has a maximum of 9% at the lowestpT and dropsbelow 3% for pT > 1 GeV/c. A comparison of thed0 distributions of data and Monte Carlo tracks indi-cates that the Monte Carlo simulation using PYTHIAunderestimates the particle yield from secondaries by0-50%, depending onpT . This is consistent with thefact that PYTHIA underestimates the strangeness yieldby a similar amount, when compared to previous resultsin pp and pp collisions [14, 15]. For the final correc-tions to the data we scale accordingly the contaminationlevel obtained with PYTHIA, resulting in an additional0-1.5% decrease of the primary particle yields. The un-certainty in the strangeness yield is taken into accountin the evaluation of the overall systematic uncertainties,as discussed below.

The reconstruction efficiency and contamination areconverted topT dependent correction factors used tocorrect the rawpT spectrum. We note that efficiencyand secondary contamination are slightly different forpositively and negatively charged particles, mainly dueto the larger absorption of negatively charged particlesand isospin effects in secondary interactions.

The charged particle transverse momenta are mea-sured in the TPC, taking into account energy loss basedon the PID hypothesis from TPC dE/dx and the mate-rial budget in front of the TPC. The material budget isstudied via the measurement of electron-positron pairsin the TPC from photon conversions. The radial distri-bution of the reconstructed photon conversion points iscompared to Monte Carlo simulations. The sum of allpositive and negative deviations is+4.7% and−7.2%,respectively. The remaining material budget uncertaintyenters into the final systematic uncertainties. In thisanalysis, we use the measurement of the momentum atthe event vertex.

At the present level of calibration, the transversemomentum resolution achieved in the TPC is given by(σ(pT)/pT)2 = (0.01)2+(0.007·pT)2, with pT in GeV/c.The transverse momentum resolution forpT > 1 GeV/cis measured in cosmic muon events by comparing themuon momenta reconstructed in the upper and lowerhalves of the TPC. ForpT < 1 GeV/c, the Monte Carloestimate ofσ(pT)/pT ≈ 1% is cross-checked usingthe measured K0s invariant mass distribution. A MonteCarlo based correction is applied to thepT spectra to ac-count for the finite momentum resolution. The correc-tion increases withpT and reaches 1.2% at 10 GeV/c.

The calibration of the absolute momentum scale isverified employing the invariant mass spectra ofΛ, Λ,

K0s andφ. The reconstructed peak positions agree with

their PDG values within 0.3 MeV/c2. As a cross-check,theq/pT distributions of particles with chargeq in dataand Monte Carlo simulation are compared and the sym-metry of the minimum aroundq/pT = 0 is studied.Based on these studies, we estimate an upper limit onthe systematic uncertainty of the momentum scale of|∆(pT)/pT | < 0.003. Within thepT reach of this study,the effect of the momentum scale uncertainty on the fi-nal spectra is found to be negligible.

For the normalization of the transverse momentumspectra to the number of events, multiplicity depen-dent correction factors are derived from the event selec-tion and vertex reconstruction efficiencies for INEL andNSD events, evaluated with the PYTHIA Monte Carloevent generator.

The fully correctedpT spectra are fitted by the mod-ified Hagedorn function [16]

12πpT

d2Nch

dη dpT∝

pT

mT

(

1+pT

pT,0

)−b

. (1)

For the transverse massmT =

√

m2π + p2

T , the pionmass is assumed for all tracks. At smallpT , the term(

1+ pT

pT,0

)−bbehaves like an exponential inpT with in-

verse slope parameterpT,0/b. This provides a good de-scription of the soft part of the spectrum, allowing foran extrapolation of the measured data topT = 0. To as-sess the tail of the spectrum atpT > 3 GeV/c, a powerlaw fit is performed

12πpT

d2Nch

dη dpT∝ p−n

T , (2)

yielding a very good description of the hard part of thespectrum characterized by the powern.

The calculation of〈pT〉 in all INEL and NSD eventsis performed using the weighted average over the mea-sured points in the range 0.15 < pT < 10 GeV/c com-bined with the result of the Hagedorn fit to extrapolateto pT = 0.

In order to analyze the behaviour of〈pT〉 as functionof multiplicity, the INEL data sample is subdivided intobins ofnacc. The results for〈pT〉 are presented calculat-ing the weighted average over two differentpT ranges,0.15< pT < 4 GeV/c and 0.5 < pT < 4 GeV/c. In addi-tion, results are presented employing the extrapolationto pT = 0 as described above.

To extract the correlation between〈pT〉 and thenumber of primary charged particles (nch) in |η| < 0.8,the following weighting procedure is applied to accountfor the experimental resolution of the measured eventmultiplicities:

10

〈pT〉 (nch) =∑

nacc

〈pT〉 (nacc)R(nch, nacc). (3)

This method employs the normalized response ma-trix R(nch, nacc) from Monte Carlo simulations whichcontains the probability that an event with multiplicitynch is reconstructed with multiplicitynacc. The resultsfrom this approach are consistent with an alternativeMonte Carlo based procedure, where an average mul-tiplicity 〈nch〉 is assigned to every measured multiplictynacc.

4. Systematic uncertainties

In order to estimate the systematic uncertainties ofthe finalpT spectra, the results of the data analysis andof the evaluation of the corrections from Monte Carlosimulations are checked for stability under varying cutsand Monte Carlo assumptions, within reasonable lim-its. In particular we studied a variation of the ratios ofthe most abundant primary charged particles (p,π, K)by ±30% with respect to their PYTHIA values, the rel-ative fractions of diffractive processes corresponding totheir experimental errors [5, 13], the TPC readout cham-ber alignment (±100µm), and track and event qualitycuts in the analysis procedure. Particular attention waspaid to the rejection efficiency of secondary particles us-ing thed0 cut. The stability of the results under vari-ation of thed0 cut value (±3 standard deviations withrespect to the nominal value), the secondary yield fromstrange hadron decays (±30%) and the material budget(±10%) was studied and the systematic uncertainty isestimated accordingly. Systematic uncertainties of theITS and TPC detector efficiencies are estimated by acomparison of the experimental ITS-TPC track match-ing efficiency with the Monte Carlo one. The systematicuncertainty of the VZERO triggering efficiency is stud-ied by varying the calibration and threshold settings inthe data and in the Monte Carlo simulation. The eventgenerator dependence is determined from a comparisonof the PYTHIA results with those obtained using PHO-JET. The total systematic uncertainty on thepT spec-tra derived from this study is 3.0-7.1% for INEL eventsand 3.5-7.2% for NSD events, in thepT range from0.2− 10 GeV/c (see Table 1).

Also listed in Table 1 are the systematic errors in〈pT〉 arising from these contributions. We note thatonly pT dependent errors on thepT spectra contributeto the systematic error in〈pT〉. Additional systematicuncertainties in〈pT〉 arise from the specific choice of

the fit function used for thepT = 0 extrapolation, andthe weighting procedure which is employed to derive〈pT〉 as function ofnch. To estimate the uncertainty inthe extrapolation topT = 0 the results are comparedto those obtained from a fit of the Tsallis function [17],or by fitting the spectral shape predicted by PYTHIAand PHOJET to our lowpT data points. Based on thiscomparison a systematic error of 1% in〈pT〉 is assignedto the pT = 0 extrapolation. The weighting procedure(Eq. 3) was studied using PYTHIA and PHOJET simu-lations. For both models, the true〈pT〉 dependence onnch from Monte Carlo can be recovered within 3% fromthe reconstructed dependence of〈pT〉 on nacc using (3).No significant multiplicity dependence of the system-atic errors on〈pT〉 is observed. The total systematicuncertainties on〈pT〉 are listed in Table 1.

5. Results and discussion

The normalized differential yield in INELpp colli-sions at

√s= 900 GeV and the fit with the parametriza-

tion given in Eq. 1 are shown in Fig. 2. The mod-ified Hagedorn fit provides a good description of thedata forpT < 4 GeV/c. The fit parameters for INELevents arepT,0 = 1.05± 0.01 (stat.)±0.05 (syst.) GeV/cand b = 7.92 ± 0.03 (stat.)±0.02 (syst.). Theaverage transverse momentum including the extrap-olation to pT = 0 is 〈pT〉 INEL = 0.483 ±0.001 (stat.)±0.007(syst.) GeV/c. For NSD events weobtain pT,0 = 1.05 ± 0.01 (stat.)±0.05 (syst.) GeV/c,b = 7.84 ± 0.03 (stat.)±0.02 (syst.) and〈pT〉 NSD =

0.489± 0.001 (stat.)±0.007 (syst.) GeV/c. Restrictionof the modified Hagedorn fit topT < 4 GeV/chas a neg-ligible effect on these results. Fig. 2 also shows the re-sult of a power law fit (Eq. 2) to the INEL data forpT >

3 GeV/c. The power law fit provides a significantly bet-ter description of the highpT tail of the spectrum thanthe modified Hagedorn parametrization. The result ofthe power law fit isn = 6.63± 0.12 (stat.)±0.01 (syst.)for both INEL and NSD events. The power law shapeof the high pT part of the spectrum is suggestive ofpQCD. Estimates of differential cross sections can beobtained using the cross sections derived from the mea-surement by UA5 [13] inpp at

√s= 900 GeV,σINEL =

50.3±0.4 (stat.)±1 (syst.) mb andσNSD = 42.6±1.4 mb(see also [18]).

The transverse momentum distribution for NSDevents is shown in Fig. 3 (left panel) together with datarecently published by ATLAS [19] and CMS [20], mea-sured in larger pseudorapidity intervals. BelowpT =

1 GeV/c the data agree. At higherpT the data areslightly above the other two LHC measurements. The

11

-2)

(GeV

/c)

T d

pη

)/(d

chN2

) (d

T pπ

1/(

2ev

t1/

N -610

-510

-410

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10

| < 0.8η = 900 GeV, | spp, INEL, ALICE datamod. Hagedorn fit

> 3 GeV/cT

power law fit, p

fit /

data

0.5

1

1.5

ALICE systematic uncertaintiesmod. Hagedorn

(GeV/c)T

p

-110 1 10

fit /

data

0.5

1

1.5

ALICE systematic uncertaintiespower law

Figure 2: Normalized differential primary charged particle yield in INELpp collisions at√

s = 900 GeV, averaged in|η| < 0.8. The fit ranges are0.15 < pT < 10 GeV/c for the modified Hagedorn function (Eq. 1) and 3< pT < 10 GeV/c for the power law (Eq. 2). In the lower panels, theratios fit over data are shown. The open symbols indicate heredata points which are not included in the fit. Errors bars are statistical only. Indicatedas shaded areas are the relative systematic data errors.

12

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/c)

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pη

)/(d

chN2

) (d

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| < 2.4ηCMS |

(GeV/c)T

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ratio

0.20.40.60.8

11.21.4

ALICE uncertaintiesATLAS / ALICECMS / ALICE

-2)

(GeV

/c)

T)/

(dy

dpch

N2)

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pπ 1

/(2

evt

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(GeV/c)T

p

-110 1 10

ratio

0.20.40.60.8

11.21.4

ALICE uncertaintiesUA1 / ALICE

Figure 3: Left panel: Normalized differential primary charged particle yield in NSDpp collisions at√

s = 900 GeV, averaged in|η| < 0.8. TheALICE data are compared to results from ATLAS and CMS inppat the same energy [19, 20]. Right panel: Normalized invariant primary chargedparticle yield in NSDpp collisions at

√s= 900 GeV, averaged in|η| < 0.8. The ALICE data are compared to results from UA1 inpp at the same

energy [21]. For the computation of the invariant yield, it has been assumed that all particles are pions. The shaded areas indicate the statistical andsystematic errors added in quadrature.

13

observation of a harder spectrum is related to the differ-ent pseudorapidity windows (see below).

In the right panel of Fig. 3, the normalized invari-ant yield in NSD events is compared to measurementsof the UA1 collaboration inpp at the same energy [21],scaled by their measured NSD cross section of 43.5 mb.As in the previous comparison to ATLAS and CMS, thehigher yield at largepT may be related to the differentpseudorapidity acceptances. The excess of the UA1 dataof about 20% at lowpT is possibly due to the UA1 trig-ger condition, which suppresses events with very lowmultiplicity, as pointed out in [19].

The results for〈pT〉 in INEL and NSD events arecompared to other experiments [20, 21, 22, 23, 24, 25]in Fig. 4. Our results are somewhat higher than pre-vious measurements inpp and pp at the same energy,but in larger pseudorapidity windows. This is consistentwith the comparison of the spectra in Fig. 3. A similartrend exhibiting a larger〈pT〉 in a smaller pseudorapid-ity interval around mid-rapidity is apparent in Fig. 4 atTevatron energies.

(GeV)s

210 310

(G

eV/c

)⟩

T p⟨

0.35

0.4

0.45

0.5

0.55

0.6

ISR INEL | < 2.5η UA1 NSD |

| < 2.4η CMS NSD |

| < 1.0η CDF |

| < 3.25η E735 NSD |

| < 0.8η ALICE INEL |

| < 0.8η ALICE NSD |

Figure 4: Energy dependence of the average transverse momentum ofprimary charged particles inpp and pp collisions. Data from otherexperiments are taken from [20, 21, 22, 23, 24, 25].

Indeed, a decrease of〈pT〉 by about 2% is foundbetween|η| < 0.2 and 0.6 < |η| < 0.8 in a pseudora-pidity dependent analysis of the present data. A consis-

tent decrease of〈pT〉 is also observed in the CMS data,when pseudorapidity is increased [20, 26]. Likewise, adecrease of〈pT〉 by about 5% between|η| < 0.8 and|η| < 2.5 is found at

√s= 900 GeV in PYTHIA.

Charged particle transverse momentum distribu-tions can be used to tune Monte Carlo event gener-ators of hadron-hadron interactions, such as PYTHIAand PHOJET. Recently, PYTHIA was tuned to describethe energy dependence of existing measurements, e.g.with respect to the treatment of multiple parton inter-actions and divergencies of the 2→2 parton scatteringcross-section at small momentum transfers.

-2)

(GeV

/c)

T d

pη

)/(d

chN2

) (d

T pπ

1/(

2ev

t1/

N

-710

-610

-510

-410

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1

10

| < 0.8η = 900 GeV, | spp, INEL, ALICE dataPHOJETPYTHIA D6T (109)PYTHIA ATLAS-CSC (306)PYTHIA Perugia0 (320)

(GeV/c)T

p

-110 1 10

ratio

0.40.60.8

11.21.41.6 ALICE data uncertainties

MC / data

Figure 5: Top: Comparison of the primary charged particle differen-tial yield in INEL ppcollisions at

√s= 900 GeV (|η| < 0.8) to results

from PHOJET and PYTHIA tunes 109 [12], 306 [28] and 320 [27].Bottom: Ratio between the Monte Carlo simulation and the data. Theshaded area indicates the statistical and systematic errors of the AL-ICE data added in quadrature.

In Fig. 5, the results for INEL events are com-pared to PHOJET and different tunes of PYTHIA, D6T(tune 109) [12], Perugia0 (tune 320) [27] and ATLAS-CSC (tune 306) [28]. The best agreement is foundwith the Perugia0 tune, which gives a fair descriptionof the spectral shape, but is approximately 20% belowthe data. The D6T tune is similar to Perugia0 below2 GeV/c but underestimates the data more significantlyat high pT . PHOJET and the PYTHIA ATLAS-CSCtune fail to reproduce the spectral shape of the data.

14

They overestimate the yield below 0.7 GeV/c and fallshort of the data at highpT . We note that PHOJETand ATLAS-CSC agree best with the charged particlemultiplicity distributions at

√s = 0.9, 2.36 and 7 TeV,

respectively [5, 6].Fig. 6 shows thepT spectra in INEL events for three

different multiplicity selections (nacc) along with fits tothe modified Hagedorn function (Eq. 1). A consider-able flattening of the tails of the spectra is visible withincreasing multiplicity. The fit parameterspT,0 and bdrop by more than 50% from the lowest to the highestmultiplicities. The results for the fit parameters in binsof nacc are listed in Table 2, along with the average mul-tiplicity 〈nch〉 assigned to eachnacc as determined fromMonte Carlo simulations.

(GeV/c)T

p0 0.5 1 1.5 2 2.5 3 3.5 4

-1)

(GeV

/c)

T d

pη

)/(d

chN2

(d

evt

1/N

-410

-310

-210

-110

1

10 ALICE, pp, INEL

| < 0.8η = 900 GeV, | s

= 17 (x 200)acc n

= 7 (x 5)acc n

= 3acc n

(GeV/c)T

p-110 1

ratio

1

2 = 14 - 20acc n = 6 - 8acc n = 1 - 5acc n

Figure 6: Upper panel: Transverse momentum spectra of primarycharged particles in INELpp collisions at

√s= 900 GeV (|η| < 0.8),

normalized to the total number of INEL eventsNevt, for three dif-ferent event multiplicities together with the modified Hagedorn fits(Eq. 1) described in the text. The fits are performed in the range0.15 < pT < 4 GeV/c and extrapolated topT = 0. The error bars in-dicate the statistical and systematic errors added in quadrature. Lowerpanel: Ratios of thepT spectra in different multiplicity ranges to theinclusivepT spectrum in INEL events.

Also shown in Fig. 6 are ratios ofpT spectra in dif-ferent multiplicity regions over the inclusivepT spec-trum in INEL events. A very pronounced multiplicitydependence of the spectral shape is manifest, exhibitingenhanced particle production at highpT in high multi-plicity events. AtpT < 0.8 GeV/c the trend is opposite,

albeit with a much weaker multiplicity dependence. Theevolution of the spectral shape with multiplicity mayshed light on different particle production mechanismsin ppcollisions. A qualitatively similar evolution of thepT spectra with multiplicity has been seen inppdata at√

s= 200 GeV [29].The average transverse momentum〈pT〉 as a func-

tion of the multiplicity of accepted particles (nacc) inINEL pp collisions at

√s = 900 GeV is shown in the

left panel of Fig. 7. For all three selectedpT rangesa significant increase of〈pT〉 with multiplicity is ob-served. Most significantly for 0.5 < pT < 4 GeV/c,the slope changes at intermediate multiplicities.

In the right panel of Fig. 7 the same data is shownas a function ofnch after application of the weightingprocedure (Eq. 3). In comparison to model calculations,good agreement with the data for 0.5 < pT < 4 GeV/c isfound only for the PYTHIA Perugia0 tune (Fig. 8, leftpanel). In a wider pseudorapidity interval (|η| < 2.5),similar agreement of the data with Perugia0 was re-ported by ATLAS [19]. For 0.15 < pT < 4 GeV/c, Pe-rugia0 and PHOJET are the closest to the data, as shownin the right panel of Fig. 8, however, none of the modelsgives a good description of the entire measurements.

6. Conclusion

A measurement is presented of the primary chargedparticle transverse momentum spectrum and of themean transverse momentum inpp collisions at

√s =

900 GeV with the ALICE detector at the LHC. Goodagreement with previous results from LHC is found upto pT = 1 GeV/c. At higherpT , the data exhibit a hardermomentum spectrum of primary charged particles thanother measurements inppandpp collisions at the sameenergy. We argue that this is most likely related to thedifferent pseudorapidity intervals studied. The averagetransverse momentum in|η| < 0.8 is〈pT〉 INEL = 0.483±0.001 (stat.)±0.007 (syst.) GeV/c and 〈pT〉 NSD =

0.489± 0.001 (stat.)±0.007 (syst.) GeV/c. None of themodels and tunes investigated simultaneously describesthe pT spectrum and the correlation between〈pT〉 andnch. In particular in the lowpT region, where the bulkof the particles are produced, the models require furthertuning. These measurements will help to improve thephenomenological description of soft QCD processesand the interplay between soft and hard QCD. The pre-sented data demonstrate the excellent performance ofthe ALICE detector for momentum measurement andwill be used as a baseline for measurements at higherLHC energies and for comparison with particle produc-tion in heavy-ion collisions.

15

accn0 5 10 15 20 25 30 35

(G

eV/c

)⟩

T p⟨

0.4

0.5

0.6

0.7

0.8

0.9

1

1.1

< 4 GeV/cT

0.5 < p

< 4 GeV/cT

0.15 < p

< 4 GeV/c (extrapolated)T

0 < p

ALICE, pp, INEL

| < 0.8η = 900 GeV, | s

< 4 GeV/cT

0.5 < p

< 4 GeV/cT

0.15 < p

< 4 GeV/c (extrapolated)T

0 < p

ALICE, pp, INEL

| < 0.8η = 900 GeV, | s

chn0 5 10 15 20 25 30 35 40

(G

eV/c

)⟩

T p⟨

0.4

0.5

0.6

0.7

0.8

0.9

1

1.1

< 4 GeV/cT

0.5 < p

< 4 GeV/cT

0.15 < p

< 4 GeV/c (extrapolated)T

0 < p

ALICE, pp, INEL

| < 0.8η = 900 GeV, | s

Figure 7: The average transverse momentum of charged particles in INEL pp events at√

s = 900 GeV for three differentpT ranges as a functionof nacc (left panel) and as a function ofnch (right panel). The error bars and shaded areas indicate the statistical and systematic errors, respectively.

(G

eV/c

)⟩

T p⟨

0.8

0.9

1

1.1

1.2

1.3ALICE dataPHOJETPYTHIA D6T (109)PYTHIA ATLAS-CSC (306)PYTHIA Perugia0 (320)

| < 0.8η = 900 GeV, | spp, INEL, < 4 GeV/c

T0.5 < p

chn0 5 10 15 20 25 30 35 40

ratio

0.9

1

1.1

(G

eV/c

)⟩

T p⟨

0.5

0.6

0.7

0.8

0.9

1ALICE dataPHOJETPYTHIA D6T (109)PYTHIA ATLAS-CSC (306)PYTHIA Perugia0 (320)

| < 0.8η = 900 GeV, | spp, INEL, < 4 GeV/c

T0.15 < p

chn0 5 10 15 20 25 30 35 40

ratio

0.9

1

1.1

Figure 8: The average transverse momentum of charged particles for 0.5 < pT < 4 GeV/c (left panel) and 0.15 < pT < 4 GeV/c (right panel) inINEL pp events at

√s = 900 GeV as a function ofnch in comparison to models. The error bars and the shaded area indicate the statistical and

systematic errors of the data, respectively. In the lower panels, the ratio Monte Carlo over data is shown. The shaded areas indicate the statisticaland systematic uncertainty of the data, added in quadrature.

16

Table 1: Contributions to the systematic uncertainties on the differential primary charged particle yields 1/Nevt 1/(2πpT ) d2Nch/(dη dpT ) and theaverage transverse momentum〈pT〉 . Ranges are given if the contributions arepT dependent.

1Nevt

12πpT

d2Nchdη dpT

〈pT〉pT range (GeV/c) 0.15− 10 0.5− 4 0.15− 4 0− 4 (extrap.)Track selection cuts 0.2-4% negl. 0.3% 0.5%Contribution of diffraction (INEL) 0.9-1% negl. negl. negl.Contribution of diffraction (NSD) 2.8-3.9% - - -Event generator dependence (INEL) 2.5% negl. negl. negl.Event generator dependence (NSD) 0.5% - - -Particle composition 1-2% 0.1% negl. 0.1%Secondary particle rejection 0.2-1.5% negl. 0.1% 0.2%Detector misalignement negl. negl. negl. negl.ITS efficiency 0-1.6% negl. 0.3% 0.5%TPC efficiency 0.8-4.5% negl. 0.5% 0.7%SPD triggering efficiency negl. negl. negl. negl.VZERO triggering efficiency (INEL) negl. negl. negl. negl.VZERO triggering efficiency (NSD) 0.2% - - -Beam-gas events negl. negl. negl. negl.Pile-up events negl. negl. negl. negl.Total (INEL) 3.0-7.1% 0.1% 0.7% 1.0%Total (NSD) 3.5-7.2% - - -Rweighting procedure 3.0% 3.0% 3.0%Extrapolation topT = 0 - - 1.0%Total 3.0% 3.1% 3.3%

17

Table 2: Parameters of the modified Hagedorn fits (Eq. 1) to thetransverse momentum spectra. The fit range inpT is 0.15− 10 GeV/c for themultiplicity integrated spectra (first two rows) and 0.15− 4 GeV/c for the spectra binned in multiplicity. The errors are statistical and systematicadded in quadrature. Also given are the average multiplicites〈nch〉 of events contributing to thenacc bins, as determined from Monte Carlo.

event class nacc 〈nch〉 pT,0 (GeV/c) bINEL all 1.05± 0.05 7.92± 0.04NSD all 1.05± 0.05 7.84± 0.04INEL 1 2.1± 0.1 2.64± 0.29 16.50± 1.32INEL 2 3.5± 0.1 1.86± 0.15 12.58± 0.69INEL 3 4.8± 0.1 1.49± 0.11 10.56± 0.45INEL 4 6.1± 0.1 1.26± 0.08 9.28± 0.34INEL 5 7.4± 0.1 1.16± 0.07 8.60± 0.28INEL 6 8.7± 0.1 1.04± 0.06 7.87± 0.24INEL 7 10.0± 0.2 1.01± 0.07 7.60± 0.23INEL 8 11.3± 0.2 0.95± 0.05 7.27± 0.21INEL 9 12.6± 0.2 0.97± 0.06 7.28± 0.22INEL 10 13.9± 0.3 0.90± 0.06 6.87± 0.21INEL 11 15.1± 0.3 0.91± 0.06 6.82± 0.21INEL 12 16.4± 0.3 0.90± 0.06 6.80± 0.22INEL 13 17.7± 0.4 0.91± 0.06 6.74± 0.23INEL 14 18.9± 0.5 0.89± 0.06 6.65± 0.24INEL 15 20.1± 0.5 0.96± 0.07 6.88± 0.27INEL 16 21.3± 0.6 0.79± 0.06 6.14± 0.23INEL 17 22.5± 0.5 0.92± 0.08 6.64± 0.30INEL 18 23.7± 0.6 0.84± 0.08 6.29± 0.29INEL 19 24.9± 0.7 0.80± 0.09 6.06± 0.31INEL 20-21 26.6± 0.7 0.79± 0.09 6.03± 0.31INEL 22-24 29.4± 0.8 0.78± 0.09 5.89± 0.32INEL 25-27 33.0± 1.1 0.54± 0.10 5.02± 0.40INEL 28-45 37.1± 1.5 0.59± 0.16 5.42± 0.67

18

Acknowledgements

The ALICE collaboration would like to thank all its engineers and technicians for their invaluable contributionsto the construction of the experiment and the CERN accelerator teams for the outstanding performance of the LHCcomplex.

The ALICE collaboration acknowledges the following funding agencies for their support in building and runningthe ALICE detector:

• Calouste Gulbenkian Foundation from Lisbon and Swiss FondsKidagan, Armenia;

• Conselho Nacional de Desenvolvimento Cientıfico e Tecnol´ogico (CNPq), Financiadora de Estudos e Projetos(FINEP), Fundacao de Amparo a Pesquisa do Estado de Sao Paulo (FAPESP);

• National Natural Science Foundation of China (NSFC), the Chinese Ministry of Education (CMOE) and theMinistry of Science and Technology of China (MSTC);

• Ministry of Education and Youth of the Czech Republic;

• Danish Natural Science Research Council, the Carlsberg Foundation and the Danish National Research Foun-dation;

• The European Research Council under the European Community’s Seventh Framework Programme;

• Helsinki Institute of Physics and the Academy of Finland;

• French CNRS-IN2P3, the ‘Region Pays de Loire’, ‘Region Alsace’, ‘Region Auvergne’ and CEA, France;

• German BMBF and the Helmholtz Association;

• Hungarian OTKA and National Office for Research and Technology (NKTH);

• Departments of Atomic Energy and Science and Technology, Government of India;

• Istituto Nazionale di Fisica Nucleare (INFN) of Italy;

• MEXT Grant-in-Aid for Specially Promoted Research, Japan;

• Joint Institute for Nuclear Research, Dubna;

• Korea Foundation for International Cooperation of Scienceand Technology (KICOS);

• CONACYT, DGAPA, Mexico, ALFA-EC and the HELEN Program (High-Energy physics Latin-American–European Network);

• Stichting voor Fundamenteel Onderzoek der Materie (FOM) and the Nederlandse Organisatie voor Wetenschap-pelijk Onderzoek (NWO), Netherlands;

• Research Council of Norway (NFR);

• Polish Ministry of Science and Higher Education;

• National Authority for Scientific Research - NASR (Autontatea Nationala pentru Cercetare Stiintifica - ANCS);

• Federal Agency of Science of the Ministry of Education and Science of Russian Federation, International Sci-ence and Technology Center, Russian Academy of Sciences, Russian Federal Agency of Atomic Energy, Rus-sian Federal Agency for Science and Innovations and CERN-INTAS;

• Ministry of Education of Slovakia;

19

• CIEMAT, EELA, Ministerio de Educacion y Ciencia of Spain, Xunta de Galicia (Consellerıa de Educacion),CEADEN, Cubaenergıa, Cuba, and IAEA (International Atomic Energy Agency);

• Swedish Reseach Council (VR) and Knut & Alice Wallenberg Foundation (KAW);

• Ukraine Ministry of Education and Science;

• United Kingdom Science and Technology Facilities Council (STFC);

• The United States Department of Energy, the United States National Science Foundation, the State of Texas,and the State of Ohio.

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