Production of pions, kaons and protons in pp collisions at s √ =900 GeV with ALICE at the LHC
aa r X i v : . [ h e p - e x ] S e p EUROPEAN ORGANISATION FOR NUCLEAR RESEARCH (CERN)
CERN-PH-EP-2010-085
Submitted to: EPJC
Production of pions, kaons and protons in pp collisionsat √ s = 900 GeV with ALICE at the LHC ALICE Collaboration
Abstract
The production of π + , π − , K + , K − , p, and p at mid-rapidity has been measured in proton-protoncollisions at √ s = 900 GeV with the ALICE detector. Particle identification is performed using thespecific energy loss in the inner tracking silicon detector and the time projection chamber. In addi-tion, time-of-flight information is used to identify hadrons at higher momenta. Finally, the distinctivekink topology of the weak decay of charged kaons is used for an alternative measurement of thekaon transverse momentum ( p t ) spectra. Since these various particle identification tools give the bestseparation capabilities over different momentum ranges, the results are combined to extract spectrafrom p t = 100 MeV/ c to 2.5 GeV/ c . The measured spectra are further compared with QCD-inspiredmodels which yield a poor description. The total yields and the mean p t are compared with previousmeasurements, and the trends as a function of collision energy are discussed. PJ manuscript No. (will be inserted by the editor)
Production of pions, kaons and protons in pp collisionsat √ s = 900 GeV with ALICE at the LHC ALICE collaboration
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13 xxii ,A. Zinchenko , G. Zinovjev , Y. Zoccarato , V. Zych´aˇcek , and M. Zynovyev Affiliation notes i Also at Laboratoire de Physique Corpusculaire (LPC), Clermont Universit´e, Universit´e Blaise Pascal, CNRS–IN2P3,Clermont-Ferrand, France ii Also at Frankfurt Institute for Advanced Studies, Johann Wolfgang Goethe-Universit¨at Frankfurt, Frankfurt, Germany iii
Now at Sezione INFN, Padova, Italy iv Now at Research Division and ExtreMe Matter Institute EMMI, GSI Helmholtzzentrum f¨ur Schwerionenforschung, Darm-stadt, Germany v Now at Institut f¨ur Kernphysik, Johann Wolfgang Goethe-Universit¨at Frankfurt, Frankfurt, Germany vi Now at Physics Department, University of Cape Town, iThemba Laboratories, Cape Town, South Africa vii
Now at National Institute for Physics and Nuclear Engineering, Bucharest, Romania viii
Also at University of Houston, Houston, TX, United States ix Now at Faculty of Science, P.J. ˇSaf´arik University, Koˇsice, Slovakia x Now at European Organization for Nuclear Research (CERN), Geneva, Switzerland xi Now at Helsinki Institute of Physics (HIP) and University of Jyv¨askyl¨a, Jyv¨askyl¨a, Finland xii
Now at Institut Pluridisciplinaire Hubert Curien (IPHC), Universit´e de Strasbourg, CNRS-IN2P3, Strasbourg, France xiii
Now at Sezione INFN, Bari, Italy xiv
Now at Institut f¨ur Kernphysik, Westf¨alische Wilhelms-Universit¨at M¨unster, M¨unster, Germany xv Now at: University of Technology and Austrian Academy of Sciences, Vienna, Austria xvi
Also at Lawrence Livermore National Laboratory, Livermore, CA, United States xvii
Also at European Organization for Nuclear Research (CERN), Geneva, Switzerland xviii
Now at Secci´on F´ısica, Departamento de Ciencias, Pontificia Universidad Cat´olica del Per´u, Lima, Peru xix
Deceased xx Now at Yale University, New Haven, CT, United States xxi
Now at University of Tsukuba, Tsukuba, Japan xxii
Also at Centro Fermi – Centro Studi e Ricerche e Museo Storico della Fisica “Enrico Fermi”, Rome, Italy xxiii
Now at Dipartimento Interateneo di Fisica ‘M. Merlin’ and Sezione INFN, Bari, Italy xxiv
Also at Laboratoire de Physique Subatomique et de Cosmologie (LPSC), Universit´e Joseph Fourier, CNRS-IN2P3, InstitutPolytechnique de Grenoble, Grenoble, France xxv
Now at Dipartimento di Fisica Sperimentale dell’Universit`a and Sezione INFN, Turin, Italy xxvi
Now at Physics Department, Creighton University, Omaha, NE, United States xxvii
Now at Commissariat `a l’Energie Atomique, IRFU, Saclay, France xxviii
Also at Department of Physics, University of Oslo, Oslo, Norway xxix
Now at Physikalisches Institut, Ruprecht-Karls-Universit¨at Heidelberg, Heidelberg, Germany xxx
Now at Institut f¨ur Kernphysik, Technische Universit¨at Darmstadt, Darmstadt, Germany xxxi
Now at Department of Physics and Technology, University of Bergen, Bergen, Norway xxxii
Now at Physics Department, University of Athens, Athens, Greece xxxiii
Also at Institut f¨ur Kernphysik, Westf¨alische Wilhelms-Universit¨at M¨unster, M¨unster, Germany xxxiv
Now at SUBATECH, Ecole des Mines de Nantes, Universit´e de Nantes, CNRS-IN2P3, Nantes, France xxxv
Now at Universit´e de Lyon, Universit´e Lyon 1, CNRS/IN2P3, IPN-Lyon, Villeurbanne, France xxxvi
Now at: Centre de Calcul IN2P3, Lyon, France xxxvii
Now at Variable Energy Cyclotron Centre, Kolkata, India xxxviii
Also at Dipartimento di Fisica dell’Universit`a and Sezione INFN, Padova, Italy xxxix
Also at Sezione INFN, Bologna, Italy xl Also at Dipartimento di Fisica dell´Universit`a, Udine, Italy xli
Also at Wroc law University, Wroc law, Poland xlii
Now at Dipartimento di Fisica dell’Universit`a and Sezione INFN, Padova, Italy
Collaboration institutes Dipartimento di Scienze e Tecnologie Avanzate dell’Universit`a del Piemonte Orientale and Gruppo Collegato INFN, Alessan-dria, Italy Department of Physics Aligarh Muslim University, Aligarh, India Nikhef, National Institute for Subatomic Physics, Amsterdam, Netherlands Physics Department, University of Athens, Athens, Greece Dipartimento Interateneo di Fisica ‘M. Merlin’ and Sezione INFN, Bari, Italy Sezione INFN, Bari, Italy China Institute of Atomic Energy, Beijing, China Department of Physics and Technology, University of Bergen, Bergen, Norway Faculty of Engineering, Bergen University College, Bergen, Norway Lawrence Berkeley National Laboratory, Berkeley, CA, United States Institute of Physics, Bhubaneswar, India School of Physics and Astronomy, University of Birmingham, Birmingham, United Kingdom Dipartimento di Fisica dell’Universit`a and Sezione INFN, Bologna, Italy Sezione INFN, Bologna, Italy Faculty of Mathematics, Physics and Informatics, Comenius University, Bratislava, Slovakia Institute of Space Sciences (ISS), Bucharest, Romania National Institute for Physics and Nuclear Engineering, Bucharest, Romania KFKI Research Institute for Particle and Nuclear Physics, Hungarian Academy of Sciences, Budapest, Hungary Dipartimento di Fisica dell’Universit`a and Sezione INFN, Cagliari, Italy Sezione INFN, Cagliari, Italy Universidade Estadual de Campinas (UNICAMP), Campinas, Brazil Physics Department, University of Cape Town, iThemba Laboratories, Cape Town, South Africa Dipartimento di Fisica e Astronomia dell’Universit`a and Sezione INFN, Catania, Italy Sezione INFN, Catania, Italy Physics Department, Panjab University, Chandigarh, India Laboratoire de Physique Corpusculaire (LPC), Clermont Universit´e, Universit´e Blaise Pascal, CNRS–IN2P3, Clermont-Ferrand, France Department of Physics, Ohio State University, Columbus, OH, United States Niels Bohr Institute, University of Copenhagen, Copenhagen, Denmark The Henryk Niewodniczanski Institute of Nuclear Physics, Polish Academy of Sciences, Cracow, Poland Universidad Aut´onoma de Sinaloa, Culiac´an, Mexico Research Division and ExtreMe Matter Institute EMMI, GSI Helmholtzzentrum f¨ur Schwerionenforschung, Darmstadt,Germany Institut f¨ur Kernphysik, Technische Universit¨at Darmstadt, Darmstadt, Germany Wayne State University, Detroit, MI, United States Joint Institute for Nuclear Research (JINR), Dubna, Russia Frankfurt Institute for Advanced Studies, Johann Wolfgang Goethe-Universit¨at Frankfurt, Frankfurt, Germany Institut f¨ur Kernphysik, Johann Wolfgang Goethe-Universit¨at Frankfurt, Frankfurt, Germany Laboratori Nazionali di Frascati, INFN, Frascati, Italy Gangneung-Wonju National University, Gangneung, South Korea Petersburg Nuclear Physics Institute, Gatchina, Russia European Organization for Nuclear Research (CERN), Geneva, Switzerland Laboratoire de Physique Subatomique et de Cosmologie (LPSC), Universit´e Joseph Fourier, CNRS-IN2P3, Institut Poly-technique de Grenoble, Grenoble, France Centro de Aplicaciones Tecnol´ogicas y Desarrollo Nuclear (CEADEN), Havana, Cuba Kirchhoff-Institut f¨ur Physik, Ruprecht-Karls-Universit¨at Heidelberg, Heidelberg, Germany Physikalisches Institut, Ruprecht-Karls-Universit¨at Heidelberg, Heidelberg, Germany Hiroshima University, Hiroshima, Japan University of Houston, Houston, TX, United States Physics Department, University of Rajasthan, Jaipur, India Physics Department, University of Jammu, Jammu, India Helsinki Institute of Physics (HIP) and University of Jyv¨askyl¨a, Jyv¨askyl¨a, Finland Bogolyubov Institute for Theoretical Physics, Kiev, Ukraine University of Tennessee, Knoxville, TN, United States Saha Institute of Nuclear Physics, Kolkata, India Variable Energy Cyclotron Centre, Kolkata, India Fachhochschule K¨oln, K¨oln, Germany Faculty of Science, P.J. ˇSaf´arik University, Koˇsice, Slovakia Institute of Experimental Physics, Slovak Academy of Sciences, Koˇsice, Slovakia Laboratori Nazionali di Legnaro, INFN, Legnaro, Italy Secci´on F´ısica, Departamento de Ciencias, Pontificia Universidad Cat´olica del Per´u, Lima, Peru Lawrence Livermore National Laboratory, Livermore, CA, United States Division of Experimental High Energy Physics, University of Lund, Lund, Sweden Centro de Investigaciones Energ´eticas Medioambientales y Tecnol´ogicas (CIEMAT), Madrid, Spain Instituto de Ciencias Nucleares, Universidad Nacional Aut´onoma de M´exico, Mexico City, Mexico Instituto de F´ısica, Universidad Nacional Aut´onoma de M´exico, Mexico City, Mexico Centro de Investigaci´on y de Estudios Avanzados (CINVESTAV), Mexico City and M´erida, Mexico Institute for Nuclear Research, Academy of Sciences, Moscow, Russia Institute for Theoretical and Experimental Physics, Moscow, Russia Moscow Engineering Physics Institute, Moscow, Russia Russian Research Centre Kurchatov Institute, Moscow, Russia Indian Institute of Technology, Mumbai, India Institut f¨ur Kernphysik, Westf¨alische Wilhelms-Universit¨at M¨unster, M¨unster, Germany SUBATECH, Ecole des Mines de Nantes, Universit´e de Nantes, CNRS-IN2P3, Nantes, France Yale University, New Haven, CT, United States Budker Institute for Nuclear Physics, Novosibirsk, Russia Oak Ridge National Laboratory, Oak Ridge, TN, United States Physics Department, Creighton University, Omaha, NE, United States Institut de Physique Nucl´eaire d’Orsay (IPNO), Universit´e Paris-Sud, CNRS-IN2P3, Orsay, France Department of Physics, University of Oslo, Oslo, Norway Dipartimento di Fisica dell’Universit`a and Sezione INFN, Padova, Italy Sezione INFN, Padova, Italy Faculty of Nuclear Sciences and Physical Engineering, Czech Technical University in Prague, Prague, Czech Republic Institute of Physics, Academy of Sciences of the Czech Republic, Prague, Czech Republic Institute for High Energy Physics, Protvino, Russia Benem´erita Universidad Aut´onoma de Puebla, Puebla, Mexico Pusan National University, Pusan, South Korea Nuclear Physics Institute, Academy of Sciences of the Czech Republic, ˇReˇz u Prahy, Czech Republic Dipartimento di Fisica dell’Universit`a ‘La Sapienza’ and Sezione INFN, Rome, Italy Sezione INFN, Rome, Italy Commissariat `a l’Energie Atomique, IRFU, Saclay, France Dipartimento di Fisica ‘E.R. Caianiello’ dell’Universit`a and Sezione INFN, Salerno, Italy California Polytechnic State University, San Luis Obispo, CA, United States Departamento de F´ısica de Part´ıculas and IGFAE, Universidad de Santiago de Compostela, Santiago de Compostela, Spain Universidade de S˜ao Paulo (USP), S˜ao Paulo, Brazil Russian Federal Nuclear Center (VNIIEF), Sarov, Russia Department of Physics, Sejong University, Seoul, South Korea Yonsei University, Seoul, South Korea Technical University of Split FESB, Split, Croatia V. Fock Institute for Physics, St. Petersburg State University, St. Petersburg, Russia Institut Pluridisciplinaire Hubert Curien (IPHC), Universit´e de Strasbourg, CNRS-IN2P3, Strasbourg, France University of Tokyo, Tokyo, Japan
Dipartimento di Fisica dell’Universit`a and Sezione INFN, Trieste, Italy
Sezione INFN, Trieste, Italy
University of Tsukuba, Tsukuba, Japan
Dipartimento di Fisica Sperimentale dell’Universit`a and Sezione INFN, Turin, Italy
Sezione INFN, Turin, Italy
Nikhef and Institute for Subatomic Physics of Utrecht University, Utrecht, Netherlands
Universit´e de Lyon, Universit´e Lyon 1, CNRS/IN2P3, IPN-Lyon, Villeurbanne, France
Soltan Institute for Nuclear Studies, Warsaw, Poland
Warsaw University of Technology, Warsaw, Poland
Purdue University, West Lafayette, IN, United States
Zentrum f¨ur Technologietransfer und Telekommunikation (ZTT), Fachhochschule Worms, Worms, Germany
Hua-Zhong Normal University, Wuhan, China
Yerevan Physics Institute, Yerevan, Armenia
Rudjer Boˇskovi´c Institute, Zagreb, CroatiaReceived: May 28, 2018/ Revised version: date
Abstract.
The production of π + , π − , K + , K − , p, and p at mid-rapidity has been measured in proton-protoncollisions at √ s = 900 GeV with the ALICE detector. Particle identification is performed using the specificenergy loss in the inner tracking silicon detector and the time projection chamber. In addition, time-of-flightinformation is used to identify hadrons at higher momenta. Finally, the distinctive kink topology of theweak decay of charged kaons is used for an alternative measurement of the kaon transverse momentum ( p t )spectra. Since these various particle identification tools give the best separation capabilities over differentmomentum ranges, the results are combined to extract spectra from p t = 100 MeV/ c to 2.5 GeV/ c . Themeasured spectra are further compared with QCD-inspired models which yield a poor description. Thetotal yields and the mean p t are compared with previous measurements, and the trends as a function ofcollision energy are discussed. In pp collisions at ultra-relativistic energies the bulk of theparticles produced at mid-rapidity have transverse mo-menta, p t , below 1 GeV/ c . Their production is not calcu-lable from first principles via perturbative Quantum Chro-modynamics, and is not well modelled at lower collisionenergies. This low p t particle production, and species com-position, must therefore be measured, providing crucialinput for the modelling of hadronic interactions and thehadronization process. It is important to study the bulkproduction of particles as a function of both p t and parti-cle species. With the advent of pp collisions at the LargeHadron Collider (LHC) at CERN a new energy regime isbeing explored, where particle production from hard in-teractions which are predominantly gluonic in nature, isexpected to play an increasing role. Such data will pro-vide extra constraints on the modelling of fragmentationfunctions. The data will also serve as a reference for theheavy-ion measurements.The ALICE detector [1,2] is designed to perform mea-surements in the high-multiplicity environment expectedin central lead-lead collisions at √ s NN = 5.5 TeV at theLHC and to identify particles over a wide range of mo- menta. As such, it is ideally suited to perform these mea-surements also in pp collisions.This paper presents the transverse momentum spectraand yields of identified particles at mid-rapidity from thefirst pp collisions collected in the autumn of 2009, duringthe commissioning of the LHC, at √ s = 900 GeV. Theevolution of particle production in pp collisions with colli-sion energy is studied by comparing to data from previousexperiments.We report π + , π − , K + , K − , p, and p distributions,identified via several independent techniques utilizing spe-cific energy loss, d E /d x , information from the Inner Track-ing System (ITS) and the Time Projection Chamber (TPC),and velocity measurements in the Time-Of-Flight array(TOF). The combination of these methods provides par-ticle identification over the transverse momentum range0 . /c < p t < . /c . Charged kaons, identified viakink topology of their weak decays in the TPC, provide acomplementary measurement over a similar p t range. Allreported particle yields are for primary particles, namelythose directly produced in the collision including the prod-ucts of strong and electromagnetic decays but excludingweak decays of strange particles.The paper is organized as follows: In Section 2, the AL-ICE detectors relevant for these studies, the experimental conditions, and the corresponding analysis techniques aredescribed. Details of the event and particle selection arepresented. In Section 3, the π + , π − , K + , K − , p, and p in-clusive spectra and yields, obtained by combining the var-ious techniques described in Section 2, are presented. Theresults are compared with calculations from QCD-inspiredmodels and the p t -dependence of ratios of particle yields,e.g. K/ π and p/ π , are discussed. Comparisons with datafrom other experiments at different √ s are made and theevolution of the ratio of strange to non-strange hadronswith collision energy is discussed. Finally, in Section 4 theresults are summarized. The ALICE detector and its expected performance aredescribed in detail in [1–3]. For the analyses describedin this paper the following detectors are used: the ITS,the TPC and the TOF detector. These detectors are posi-tioned in a solenoidal magnetic field of B = 0.5 T and havea common pseudo-rapidity coverage of − . < η < . . < η < . − . < η < − . The ITS is the closest of the central barrel detectors to thebeam axis. It is composed of six cylindrical layers of sili-con detectors. The two innermost layers are equipped withpixel detectors (SPD), followed by two layers of drift de-tectors (SDD) and two layers of double-sided silicon stripdetectors (SSD). The innermost layer is at 3.9 cm fromthe beam axis, while the outer layer is at 43.0 cm.The ITS provides high-resolution space points thatallow the extension of tracks reconstructed in the TPCtowards the interaction vertex, thus improving momen-tum and angular resolution. The four layers equipped withSDD and SSD also provide a measurement of the specificenergy loss d E /d x . The SPD yields an on-line measureof the multiplicity by counting the number of chips thathave one or more hits (fast-OR), which is included in theminimum-bias trigger logic [3,4]. The ITS is also used as astand-alone tracker to reconstruct charged particles withmomenta below 200 MeV/ c that are deflected or decaybefore reaching the TPC, and to recover tracks crossingdead regions of the TPC. A detailed description of thethree sub-systems can be found in [3]. The d E /d x mea-surement in the SDD and SSD has been calibrated usingcosmic ray data and pp events [5]. The 2198 ITS moduleshave been aligned using survey information, cosmic-raytracks and pp data with the methods described in [6]. Thefraction of active modules per layer in the present setupis around 80% in the SPD and 90% - 95% both in SDDand SSD. The TPC is the main tracking device. It is a large volume,high granularity, cylindrical detector with an outer radiusof 2.78 m and a length of 5.1 m. The active volume extendsfrom 0.85 m to 2.47 m in radius. It covers 2 π in azimuthand | η | < . | η | < drift volume is filled witha Ne (85.7%), CO (9.5%), and N (4.8%) gas mixture.A high voltage central membrane splits the drift region intwo halves, resulting in a maximal drift time of 94 µ s. Eachof the two read-out planes is composed of 18 inner and 18outer chambers with a total of 159 pad rows, resultingin a total of 557 568 pads which are read out separately.The position resolution in rφ direction varies from 1100 µ m to 800 µ m when going from the inner to the outerradius. Along the beam axis ( z , also the drift direction)the resolution ranges between 1250 µ m and 1100 µ m. Amaximum of 159 clusters can be measured along a trackin the TPC. For a detailed description see [7]. The TOF detector consists of 18 azimuthal sectors, eachcontaining 91 Multi-gap Resistive Plate Chambers (MR-PCs) distributed in five gas-tight modules. It is positionedat 370-399 cm from the beam axis. The region 260 ◦ < φ< ◦ at η ∼ × size), result-ing in a total of 152928 channels. Test beam results demon-strated that the intrinsic time resolution of the detector isbetter than 50 ps, dominated by electronic effects and thetime resolution of the time-to-digital converters [8]. Re-sults from the TOF commissioning with cosmic rays aredescribed in references [9–11]. In the present setup, 9.6%of the readout channels were inactive due to failures inthe high- or low-voltage systems or in the readout elec-tronics. The fraction of noisy channels, identified duringdata taking by online monitoring and excluded from thesubsequent reconstruction, was below 0.1%. The data presented in this paper were collected duringthe commissioning of the LHC at CERN in the autumn of2009, with pp collisions at √ s = 900 GeV. The colliderwas run with four bunches per beam, resulting in twobunch crossings per beam circulation period (89 µ s) atthe ALICE interaction point. The remaining two bunchesper beam were not collided at ALICE, and served to es-timate the contribution of beam-gas interactions. The av-erage event rate was a few Hz, so the fraction of pile-upevents was negligible. The analysis is based on a sample of ∼ N ch / d η | NSD / d N ch / d η | INEL ≃ .
185 [12].PYTHIA and PHOJET simulations indicate that the p t -dependence of the ratio of spectra for NSD and inelasticcollisions is less than 5% in the reported range. Particleratios are found to be insensitive to the conversion frominelastic to non-single-diffractive events. The identified particle spectra were measured indepen-dently with the ITS, TPC and TOF, and combined inthe final stage of the analysis. The rapidity range | y | < . | y | < . | η | < .
9. However, shorter tracks at higher η can still be used for physics analysis, in particular pro-tons with a transverse momentum of p t = 400 MeV/ c and | y | = 0 . | η | = 1 .
1. To ensure hightracking efficiency and d E /d x -resolution, while keepingthe contamination from secondaries and fakes low, tracksare required to have at least 80 clusters, and a χ of themomentum fit that is smaller than 4 per cluster. Since eachcluster in the TPC provides two degrees of freedom andthe number of parameters of the track fit is much smallerthan the number of clusters, the χ cut is approximately2 per degree of freedom. In addition, at least two clustersin the ITS must be associated to the track, out of whichat least one is from the SPD. Tracks are further rejectedbased on their distance-of-closest approach (DCA) to thereconstructed event vertex. The cut is implemented as afunction of p t to correspond to about seven (five) stan-dard deviations in the transverse (longitudinal) coordi-nate, taking into account the p t -dependence of the impactparameter resolution. These selection criteria are tuned toselect primary charged particles with high efficiency whileminimizing the contributions from weak decays, conver-sions and secondary hadronic interactions in the detectormaterial. The DCA resolution in the data is found to bein good agreement with the Monte-Carlo simulations thatare used for efficiency corrections (see next Section).Tracks reconstructed in the TPC are extrapolated tothe sensitive layer of the TOF and a corresponding signalis searched for. The channel with the center closest to thetrack extrapolation point is selected if the distance is lessthan 10 cm. This rather weak criterion results in a highmatching efficiency while keeping the fraction of wronglyassociated tracks below 1% in the low-density environmentpresented by pp collisions.The d E /d x measurements in the ITS are used to iden-tify hadrons in two independent analyses, based on dif-ferent tracking algorithms. One analysis uses the ITS-TPC combined tracking, while the other is based on ITSstand-alone tracks. The combined ITS-TPC tracking re-sult serves as a cross-check of both the ITS stand-aloneand the TPC results in the overlap region. The ITS stand-alone analysis extends the acceptance to lower p t than theTPC or ITS-TPC analyses.The combined ITS-TPC analysis uses the same trackselection criteria as the TPC only analysis, with the ad-ditional requirement of at least four clusters in the ITS,out of which at least one must be in the SPD and at leastthree in SSD+SDD. This further reduces the contamina-tion of secondaries and provides high resolution on trackimpact parameter and optimal resolution on the d E /d x .The ITS stand-alone tracking uses a similar selection, witha different χ selection and a different DCA selection. Inthe current tracking algorithm, ITS clusters are assigneda larger position error to account for residual misalign-ment of the detector. As a result, the χ values are notproperly normalized, but the selection was adjusted to beequivalent to the TPC χ selection by inspecting the dis-tributions. The DCA cut in the ITS analysis uses the same p t -dependent parametrization as for TPC tracks, but withdifferent parameters to account for the different resolution. The efficiency and other correction factors including ac-ceptance (jointly called efficiency in the following discus-sion) used in this paper are calculated from a Monte-Carlo simulation, based on over two million events pro-duced with the PYTHIA 6.4 event generator [15] (tuneD6T [16]), propagated through the detector with the GE-ANT3 [17] transport code. Dead and noisy channels aswell as beam position and spread have been taken intoaccount. A simulation based on the PHOJET event gen-erator [18] is also used as a cross check.GEANT3 is known to reproduce the absorption crosssections of hadrons incorrectly. The transport code FLU-KA contains a more accurate description of these crosssections [19–21], and a dedicated simulation is used tocalculate a correction to the GEANT3 efficiency calcula-tion [22]. This is relevant mainly for antiprotons at low p t , where the correction is on the order of 10%. For otherparticles and at higher p t , the difference between GEANTand FLUKA calculations is negligible. The d E /d x and TOF signals are used for particle iden-tification as a function of the momentum p , whereas thefinal spectra are given as a function of the transverse mo-mentum p t .In the case of the TPC and ITS analyses, particles wereidentified via the specific energy loss d E /d x . Unique iden-tification on a track-by-track basis is possible in regionsof momentum where the bands are clearly separated fromeach other. In overlapping areas, particle identification isstill possible on a statistical basis using fits to the energyloss distribution in each p t -bin. The fits are performed onthe distribution of the difference between the measuredand the expected energy deposition for tracks within theselected rapidity range | y | < /β regionwhich would make the d E /d x -distribution in a simple p t or p -slice non-Gaussian. The calculated expected energyloss depends on the measured track momentum p and theassumed mass for the particle. The procedure is thereforerepeated three times for the entire set of tracks, assumingthe pion, kaon, and proton mass.In the TPC analysis, the difference[d E /d x ] meas − [d E /d x ( pid, p tot )] calc is used. For the ITSthe difference of the logarithm of the measured and calcu-lated energy deposit ln[d E /d x meas ] − ln[d E /d x ( pid , p tot ) calc ]is taken to suppress the non-gaussian tails originating fromthe smaller number of d E /d x measurements.In the case of the TOF, the identification is based onthe time-of-flight information. The procedure for the ex-traction of the raw yields differs slightly from the one usedfor TPC and ITS, and is described in Section 2.5.3. In both the ITS stand-alone and in the ITS-TPC analy-ses, the d E /d x measurement from the SDD and the SSDis used to identify particles. The stand-alone tracking re-sult extends the momentum range to lower p t than can bemeasured in the TPC, while the combined tracking pro-vides a better momentum resolution.The energy loss measurement in each layer of the ITSis corrected for the track length in the sensitive volumeusing tracking information. In the case of SDD clusters, alinear correction for the dependence of the reconstructedraw charge as a function of drift time due to the com-bined effect of charge diffusion and zero suppression isalso applied [5]. For each track, d E /d x is calculated usinga truncated mean: the average of the lowest two pointsin case four points are measured, or a weighted sum ofthe lowest (weight 1) and the second lowest point (weight1/2), in case only three points are measured. momentum [GeV/c] -1
10 1 m ] µ d E [ k e V / pK π Fig. 1. (Color online) Specific energy loss d E /d x vs. momen-tum for tracks measured with the ITS. The solid lines are aparametrization (from [23]) of the detector response based onthe Bethe-Bloch formula. Figure 1 shows the truncated mean d E /d x for the sam-ple of ITS stand-alone tracks along with the PHOBOSparametrization of the most probable value [23].For the ITS stand-alone track sample, the histogramsare fitted with three Gaussians and the integral of theGaussian centered at zero is used as the raw yield of thecorresponding hadron species. In a first step, the peakwidths σ of the peaks are extracted as a function of p t for pions and protons in the region where their d E /d x distributions do not overlap with the kaon (and electron)distribution. For kaons, the same procedure is used at low p t , where they are well separated. The p t -dependence ofthe peak width is then extrapolated to higher p t with thesame functional form used to describe the pions and pro-tons. The resulting parametrizations of the p t dependenceof σ are used to constrain the fits of the ln[d E /d x ] distri-butions to extract the raw yields.For the ITS-TPC combined track sample, a non-Gau-ssian tail is visible. This tail is a remnant of the tail of the calc -ln[dE/dx(K)] meas ln[dE/dx]-3 -2 -1 0 1 2 3 C oun t s [0.300,0.350] GeV/c ∈ T p - K TPC+ITS calc -ln[dE/dx(K)] meas ln[dE/dx]-3 -2 -1 0 1 2 3 C oun t s [0.300,0.350] GeV/c ∈ T p - K ITS stand-alone calc -ln[dE/dx(K)] meas ln[dE/dx]-3 -2 -1 0 1 2 3 C oun t s [0.400,0.450] GeV/c ∈ T p - K TPC+ITS calc -ln[dE/dx(K)] meas ln[dE/dx]-3 -2 -1 0 1 2 3 C oun t s [0.400,0.450] GeV/c ∈ T p - K ITS stand-alone
Fig. 2. (Color online) Distribution of ln[d E /d x ] meas − ln[d E /d x (K)] calc measured with the ITS in the two p t -ranges, 300–350MeV/ c (upper panels) and 400-450 MeV/ c (lower panels), using the kaon mass hypothesis. The left panels show the result forITS-TPC combined tracks, while the right panels show the ITS stand-alone result. The lines indicate fits as described in thetext. Landau distribution for energy loss. It was verified usingsimulations that the shape and size of the tail are com-patible with the expectations for a truncated mean usingtwo out of four samples. The tail is not as pronouncedfor the ITS stand-alone track sample, due to the limitedmomentum resolution. The distribution is fitted with acombination of a Gaussian and an exponential functionfor the main peak and another exponential function todescribe the tail of a background peak. This functionalform provides an accurate description of the peak shapein the detector simulation, as well as the measured shape.Examples of d E /d x distributions are shown in Fig. 2for negative tracks using the kaon mass hypothesis in twodifferent p t intervals for both ITS stand-alone tracks (rightpanels) and ITS-TPC combined tracks (left panels). Efficiency correction
The raw hadron yields extractedfrom the fits to the d E /d x distributions are correctedfor the reconstruction efficiency determined from Monte-Carlo simulations, applying the same analysis criteria tothe simulated events as to the data. Secondary particlesfrom interactions in the detector material and strange par-ticle decays have been subtracted from the yield of bothsimulated and real data. The fraction of secondaries af-ter applying the track impact-parameter cut depends onthe hadron species and amounts to 1-3% for pions and5-10% for protons depending on p t . The secondary-to-primary ratio has been estimated by fitting the measuredtrack impact-parameter distributions with three compo- nents, prompt particles, secondaries from strange particledecays and secondaries produced in the detector materialfor each hadron species. Alternatively, the contaminationfrom secondaries have been determined using Monte-Carlosamples, after rescaling the Λ yield to the measured val-ues [24]. The difference between these two procedures isabout 3% for protons and is negligible for other particles.Figure 3 shows the total reconstruction efficiency forprimary tracks in the ITS stand-alone, including the ef-fects of detector and tracking efficiency, the track selectioncuts and residual contamination in the fitting procedure,as determined from the Monte-Carlo simulation. This ef-ficiency is used to correct the measured raw yields aftersubtraction of the contributions from secondary hadrons.The measured spectra are corrected for the efficiency ofthe primary vertex reconstruction with the SPD usingthe ratio between generated primary spectra in simulatedevents with a reconstructed vertex and events passing thetrigger conditions.Systematic errors are summarized in Table 1. The sys-tematic uncertainty from secondary contamination has beenestimated by repeating the full analysis chain with differ-ent cuts on the track impact parameter and by comparingthe two alternative estimates outlined above. The effect ofthe uncertainty in the material budget has been estimatedby modifying the material budget in the Monte-Carlo sim-ulations by ± E /d x ] meas − ln[d E /d x (i)] calc distributions has been estimated by varying the fit condi- E ff i c i en cy ITS standalone + π + K p (GeV/c) t p0 0.1 0.2 0.3 0.4 0.5 0.6 0.7 0.8 0.9 E ff i c i en cy ITS standalone - π - K p
Fig. 3. (Color online) Efficiency for pions, kaons and protonsfor the ITS stand-alone analysis as obtained from Monte-Carlosimulations.
Table 1.
Summary of systematic errors in the efficiency cor-rection of the ITS analysis.systematic errors π ± K ± p and psecondary contamination negl. negl. negl.from materialsecondary contamination <
1% negl. 3%from weak decaymaterial budgethighest p t bin < <
1% 1%lowest p t bin 5% 2% 3%ITS efficiencyall p t bins 2% 2% 2%lowest p t bin 12% 13% 11%ln(d E /d x ) distr. 1% 5% 3.5%fitting procedure tion and by comparing to an independent analysis usinga track-by-track identification approach based on the dis-tance between the measured and expected d E /d x valuesnormalized to its resolution. The residual imperfections inthe description of the ITS detector modules and dead ar-eas in the simulation introduce another uncertainty in theITS tracking efficiency. This is estimated by varying thecuts on the number of clusters and on the track χ bothin data and in Monte-Carlo simulations.In the lowest p t -bins, a larger systematic error has beenassigned to account for the steep slope of the tracking effi-ciency as a function of the particle transverse momentum(see Fig. 3). Particle identification is based on the specific energy de-posit of each particle in the drift gas of the TPC, shown inFig. 4 as a function of momentum separately for positiveand negative charges. The solid curves show the calibra-tion curves obtained by fitting the ALEPH parametriza-tion of the Bethe-Bloch curve [25] to the data points inregions of clear separation.The calibration parameters have mostly been deter-mined and tested via the analysis of cosmic rays. Thepad-gain factors have been measured using the decay ofradioactive
Kr gas released into the TPC volume (for adetailed description see [7]). (GeV) zpmomentum / charge -2 -1.5 -1 -0.5 0 0.5 1 1.5 2 d E / d x i n T P C ( a . u . ) p + K + π de p - K - π + e Fig. 4. (Color online) Specific energy loss d E /d x vs. momen-tum for tracks measured with the ALICE TPC. The solid linesare a parametrization of the Bethe-Bloch curve [25]. As in the case of the ITS, a truncated-mean procedureis used to determine d E /d x (60% of the points are kept).This reduces the Landau tail of the d E /d x distribution tothe extent that it is very close to a Gaussian distribution.Examples of the d E /d x distribution in some p t binsare shown in Fig. 5. The peak centered at zero is fromkaons and the other peaks are from other particle species.As the background in all momentum bins is negligible, theintegrals of the Gaussian give the raw yields. Efficiency correction
The raw hadron spectra are cor-rected for the reconstruction efficiency, shown in Fig. 6,determined by doing the same analysis on Monte-Carloevents. The efficiency is calculated by comparing the num-ber of reconstructed particles to the number of chargedprimary particles from PYTHIA in the chosen rapidityrange. For transverse momenta above 800 MeV/ c the ef-ficiency saturates at roughly 80%. For kaons, the decayreduces the efficiency by about 30% at 250 MeV/ c and12% at 1.5 GeV/ c . The range with a reconstruction effi-ciency lower than 60% (for pions and protons) is omittedfor the analysis corresponding to a low- p t cut-off of 200 calc (dE/dx) calc - (dE/dx) meas (dE/dx) -1 -0.8 -0.6 -0.4 -0.2 0 0.2 0.4 0.6 0.8 1 C oun t s < 400 MeV t
350 MeV < p sumkaonpionelectron calc (dE/dx) calc - (dE/dx) meas (dE/dx) -1 -0.8 -0.6 -0.4 -0.2 0 0.2 0.4 0.6 0.8 1 C oun t s sumkaonpionelectron < 450 MeV t
400 MeV < p calc (dE/dx) calc - (dE/dx) meas (dE/dx) -1 -0.8 -0.6 -0.4 -0.2 0 0.2 0.4 0.6 0.8 1 C oun t s < 700 MeV t
650 MeV < psumkaonpionelectronproton
Fig. 5. (Color online) Distribution of([d E /d x ] meas − [d E /d x (kaon)] calc )/[d E /d x (kaon)] calc mea-sured with the TPC for several p t -bins showing the separationpower. The solid lines are Gaussian fits to the distributions. MeV/ c for pions, 250 MeV/ c for kaons, and 400 MeV/ c for protons.Protons are corrected for the contamination of sec-ondaries from material and of feed down from weak de-cays. The feed down was determined by two independentmethods. Firstly, the contamination obtained from Monte-Carlo simulation was scaled such that it corresponds tothe measured yield of Λ s in the data [24]. Secondly, theshape of the impact parameter distribution was comparedto the Monte-Carlo simulation. Weak decays produce anon-Gaussian tail in the distribution of primary particleswhereas secondaries from material generate a flat back-ground [22]. The remaining difference between the meth-ods is included in the systematic error. The correction for E ff i c i en cy p + π + K (GeV/c) t p E ff i c i en cy p - π - K Fig. 6. (Color online) Efficiency of charged pions, kaons, andprotons for the spectra extracted with the TPC. weak decays amounts to up to 14% and the correction forsecondaries from material up to 4% for protons with 400MeV/ c < p t <
600 MeV/ c . For other particle species andother transverse momenta the contamination is negligible.The systematic errors in the track reconstruction andin the removal of secondary particles have been estimatedby varying the number of standard deviations in the dis-tance-to-vertex cut, using a fixed cut of 3 cm instead ofthe variable one, and varying the SPD-TPC matching cut.Their impact on the corrected spectra is less than 5%. Theinfluence of the uncertainty in the material budget hasbeen examined by varying it by 7%. This resulted in thesystematic errors given in Table 2. The uncertainty dueto a possible deviation from a Gaussian shape has beenestablished by comparing the multi-Gauss fit with a 3- σ band in well separated regions. The precision of the kinkrejection is estimated to be within 3%.The correction for the event selection bias has beentested with two event generators, PYTHIA [15, 16] andPHOJET [18] and the corresponding uncertainty is lessthan 1%. Particles reaching the TOF system are identified by mea-suring their momentum and velocity simultaneously.The velocity β = L/t
TOF is obtained from the mea-sured time of flight t TOF and the reconstructed flight path L along the track trajectory between the point of closestapproach to the event vertex and the TOF sensitive sur-face. The measured velocities are shown as a function of Table 2.
Summary of systematic errors in the efficiency cor-rection in the TPC analysis.systematic errors π ± K ± p and psecondary contamination negl. negl. < <
4% - < < < < <
3% -non-Gaussianity of negl. negl. negl.dE/dx signalmatching to ITS < momentum p (GeV/c) β π K p
Fig. 7. (Color online) β of tracks of particles measured byTOF vs. their momentum. the momentum p at the vertex in Fig. 7. The bands corre-sponding to charged pions, kaons and protons are clearlyvisible. The width of the bands reflects the overall time-of-flight resolution of about 180 ps, which depends on theTOF timing signal resolution, the accuracy of the recon-structed flight path and the uncertainty of the event starttime, t ev . This last contribution is related to the uncer-tainty in establishing the absolute time of the collision.In the present sample this fluctuated with respect to thenominal time signal from the LHC with a σ of about 140ps due to the finite size of the bunches.To improve the overall time-of-flight resolution, theTOF information itself is used to determine t ev in eventshaving at least three tracks with an associated TOF sig-nal. This is done with a combinatorial algorithm whichcompares the TOF times with the calculated times of thetracks for each event for different mass hypotheses. Us-ing this procedure, the start-time has been improved for44% of the tracks having an associated TOF signal andis rather independent on the momentum of the tracks. Inthis way the precision on the event start-time is about 85ps on average. Finally, tracks whose particle identity as determinedfrom the TOF information is not compatible with the oneinferred from the d E /d x signal in the TPC within five σ have been removed. This TOF-TPC compatibility crite-rion rejects about 0.6% of the tracks and further reducesthe small contamination coming from tracks incorrectlyassociated with a TOF signal. (ps) TOF /2 - t calc ) K +t π (t -5000 -4000 -3000 -2000 -1000 0 1000 2000 C oun t s <1.10 GeV/c t (ps) TOF /2 - t calc ) K +t π (t -3000 -2000 -1000 0 1000 C oun t s <1.50 GeV/c t (ps) TOF /2 - t calc ) K +t π (t -2500 -2000 -1500 -1000 -500 0 500 1000 C oun t s <1.80 GeV/c t Fig. 8. (Color online) Distribution of the time difference be-tween the measured TOF signal and the average of the cal-culated times for pions and kaons for several p t -bins for posi-tively charged particles. The fits are performed using Gaussianshapes.4 For each particle species i , the expected time of flight t i calc is calculated by summing up the time-of-flight incre-ments ∆t k = ∆l k p p k + m i /p k at each tracking step, with p k being the local value of the track momentum, m i themass of the particle, and ∆l k the track-length incrementalong its trajectory. The yields of π , K and p are obtainedfrom the simultaneous fit of the distribution of the timedifference S between measured t TOF and the average be-tween the calculated time for pions and kaons S = ( t π + t K ) calc / − t TOF . (1)The symmetric treatment of kaons and pions in the defi-nition of S ensures that the kaon and pion peak are bothGaussian. Extracting the yield for different species in a si-multaneous fit guarantees that the resulting number of pi-ons, kaons and protons matches the total number of tracksin the given momentum bin.The distribution of the variable S is shown in Fig. 8 forthree different transverse momentum bins for positive par-ticles. The curves show the results of the three-Gaussianfit used to extract the raw yields. The integral of the fitresult has been constrained to the number of entries in thedistribution, and the means and the widths are allowed tovary within 5% and 10%, respectively, of their nominalvalues. The only free parameters in the fit are thereforethe relative normalizations between the Gaussians.The raw yields are extracted in different p t -bins usinga rapidity selection | y p | < .
5, where y p is the rapiditycalculated with the proton mass. For pions and kaons,this condition results in a larger y -acceptance and in bothcases, the fraction outside of | y | < . p t -bin taking into account the y -distribution of theyields within the pions and kaons peaks. Efficiency correction
Since the track selection used in theTOF analysis is the same as the one described in theTPC analysis (subsection 2.5.2), the same tracking andfeed-down corrections are applied. In the case of the TOFanalysis, an additional correction is needed in order to takeinto account the fraction of the particles reconstructed bythe TPC with an associated signal in TOF. This matchingefficiency includes all sources of track losses in the propa-gation from the TPC to the TOF (geometry, decays andinteractions with the material) and its matching with aTOF signal (the TOF intrinsic detector efficiency, the ef-fect of dead channels and the efficiency of the track-TOFsignal matching procedure). The TOF matching efficiencyhas been derived from Monte-Carlo events as the fractionof TPC reconstructed tracks having an associated TOFsignal and is shown in Fig. 9 for each hadron species. Themain factors limiting the TOF matching efficiency are theloss due to geometrical acceptance ( ≈ ≈ ≈ E /d x in the TPC to identify the particles.Good agreement between the efficiencies obtained from T O F m a t c h i ng e ff i c i en cy positivepionskaonsprotons (GeV/c) t p T O F m a t c h i ng e ff i c i en cy negativepionskaonsprotons Fig. 9. (Color online) The TOF matching efficiency is shownfor the three particles, separately, for (top) positive and (bot-tom) negative particles.
Table 3.
Summary of systematic errors in the TOF analysis.systematic errors π ± K ± p and pTOF < < < p t > /c )efficiency < p t = 0 . /c )PID procedure < < < the data and from Monte-Carlo simulations is observed incase of pions and kaons, with deviations at the level of,at most, 3% and 6% respectively, over the full transverse-momentum range. The observed differences are assignedas systematic errors, see Table 3. In the case of protonsand antiprotons, larger differences are observed at p t be-low 0.7 GeV/ c , where the efficiency varies very rapidlywith momentum. This region is therefore not consideredin the final results (see Table 3).Other sources of systematic errors related to the TOFPID procedure have been estimated from Monte-Carlosimulations and cross-checked with data. They include theeffect of the residual contribution from tracks wrongly as-sociated with TOF signals, and the quality and stabilityof the fit procedure used for extracting the yields. Table 3summarizes the maximal value of the systematic errors ob-served over the full transverse momentum range relevantin the analysis, for each of the sources mentioned above. In this section, the determination of the yields of chargedkaons identified by their weak decay (kink topology) insidethe TPC detector is described. These tracks are rejected in the previously described TPC analysis. This procedureallows an extension of the study of kaons to intermedi-ate momenta, on a track-by-track level, although in thisanalysis the p t reach is limited by statistics.The kinematics of the kink topology, measured as asecondary vertex with one mother and one daughter trackof the same charge, allows the separation of kaon decaysfrom the main source of background kinks coming fromcharged pion decays. The decay channels with the highestbranching ratio (B.R.) for kaons are the two-body decays(1) K ± → µ ± + ν µ , (B.R. 63.55%)(2) K ± → π ± + π , (B.R. 20.66%).Three-body decays with one charged daughter track(B.R. 9.87%) as well as three-body decays into three char-ged pions (B.R. 5.6%) are also detected.The algorithm for reconstructing kinks as secondaryvertices is applied inside a fiducial volume of the TPC withradius 120 cm < R <
210 cm in order to have a minimumnumber of clusters for reconstructing both the mother anddaughter tracks. Inside this volume a sufficient number ofkinks can be found since the cτ of kaon and pion decaysare 3.7 m and 7.8 m, respectively. The mother track ofthe kink has been selected with similar criteria to thoseof the TPC tracks used for the d E /d x analysis, exceptthat the minimum required number of clusters per trackis 30, because the kink mother track does not traverse theentire TPC. The relation between the number of clustersper mother track and the radius R of the kink is used asa quality check of the kink reconstruction procedure.The identification of kaons from kink topology and itsseparation from pion decay is based on the decay kine-matics. The transverse momentum of the daughter withrespect to the mother’s direction, q t , has an upper limitof 236 MeV/ c for kaons and 30 MeV/ c for pions for thetwo-body decay to µ + ν µ . The corresponding upper limitfor the two-body decay (2) K → π + π is 205 MeV/ c .All three limits can be seen as peaks in Fig. 10 (a), whichshows the q t distribution of all measured kinks inside theselected volume and rapidity range | y | < q t >
40 MeV/ c removes the majority of π -decays as shown by the dashed (before) and solid (after)histograms.The invariant mass for the decay into µ ± + ν µ is cal-culated from the measured difference between the motherand daughter momentum, their decay angle, assuming zeromass for the neutrino. Figure 10 (b) shows the invariantmass for the full sample of kinks (dashed line) and forthe sample after applying the preceding cuts (full line).The masses of pions and kaons are reconstructed at theirnominal values. The third peak at 0.43 GeV/ c originatesfrom the K → π + π decay for which the invariant massis calculated with wrong mass assumptions for the daugh-ter tracks. The broad structure originates from three-bodydecays of kaons.At this stage, we have a rather clean sample of kaonsas demonstrated in Fig. 10 (c) showing the d E /d x vs. themother momentum. Most of the tracks are within a 3 . σ band with respect to the corresponding Bethe-Bloch curve (GeV/c) t q C oun t s a) ) ) (GeV/c νµ ( inv M C oun t s b) p(GeV/c) d E / d x ( a r b . u i n t s ) K, full-line, dashed-line σ Fig. 10. (Color online) (a) q t distribution of the daugh-ter tracks with respect to mother momentum for all recon-structed kinks inside the analyzed sample. The dashed(solid)histograms show the distribution before (after) applying the q t >
40 MeV/ c cut. (b) Invariant mass of the two-body decaysK ± /π ± → µ ± + ν µ for candidate kaon kinks. Solid curve: afterapplying q t >
40 MeV/ c ; dashed curve: without this selection(hence also showing the pion decays). (c) d E /d x of kinks as afunction of the mother momentum, after applying the full listof selection criteria for their identification. of kaons. The few tracks outside these limits are at mo-menta below 600 MeV/ c (less than 5%) and they havebeen removed in the last analysis step. Efficiency and acceptance
The total correction factor in-cludes both the acceptance of kinks and their efficiency (mother) (GeV/c) t p A cc ep t an c e (mother) (GeV/c) t p E ff i c i en cy Fig. 11. (Color online) Upper panel: The acceptance of kaonsdecaying in the fiducial volume of the TPC as a function of thekaon p t for K + (full-triangles) and K − (open-squares). Lowerpanel: The efficiency of reconstructed kaons from kinks as afunction of the p t (mother), separately for K + (full-triangles)and K − (open-squares). The contamination from wrongly as-sociated kinks is also plotted for both charges (lower set ofpoints). (reconstruction and identification). The study has beenperformed for the rapidity interval | y | < p t . It reaches about 60% at 0.7 GeV/ c and decreases gradually at higher transverse momenta, asthe angle between mother and daughter tracks becomessmaller. The decay angle of kaon kinks allows their iden- tification up to high momenta, e.g. at p t of 5 GeV/ c thevalues are between 2 ◦ and 15 ◦ .The contamination due to random associations of pri-mary and secondary charged tracks has been establishedusing Monte-Carlo simulations and it is systematicallysmaller than 5% in the studied p t -range as also shownin Fig. 11. Hadronic interactions are the main source ofthese fake kinks (65%).The systematic error due to the uncertainty in the ma-terial budget is about 1% as for the TPC analysis. Thequality cuts remove about 8% of all real kaon kinks, whichleads to a systematic error of less than 1%. The main un-certainty originates from the efficiency of the kink findingalgorithm which has an uncertainty of 5%. Figure 12 shows a comparison between the results from thedifferent analyses. The spectra are normalized to inelasticcollisions, as explained in Sec. 2.2. The kaon spectra ob-tained with various techniques, including K s spectra [24],are compared in Fig. 13. The very good agreement demon-strates that all the relevant efficiencies are well reproducedby the detector simulation.The spectra from ITS stand-alone, TPC and TOF arecombined in order to cover the full momentum range. Theanalyses from the different detectors use a slightly differ-ent sample of tracks and have largely independent sys-tematics (mainly coming from the PID method and thecontamination from secondaries). The spectra have beenaveraged, using the systematic errors as weights. From thisweighted average, the combined, p t -dependent, systematicerror is derived. The combined spectra have an additionaloverall normalization error, coming primarily from the un-certainty on the material budget (3%, Sec. 2.5) and fromthe normalization procedure (2%, Sec. 2.2).The combined spectra shown in Fig. 14 are fitted withthe L´evy (or Tsallis) function (see e.g. [26, 27])d N d p t d y = p t × d N d y ( n − n − nC ( nC + m ( n − (cid:18) m t − m nC (cid:19) − n (2)with the fit parameters C , n and the yield d N/ d y . Thisfunction gives a good description of the spectra and hasbeen used to extract the total yields and the h p t i , summa-rized in Table 4. The χ /degree-of-freedom is calculatedusing the total error. Due to residual correlations in thepoint-by-point systematic error, the values are less than 1.Also listed are the lowest measured p t -bin and the fractionof the yield contained in the extrapolation of the spectra tozero momentum. The extrapolation to infinite momentumgives a negligible contribution. The systematic errors takeinto account the contributions from the individual detec-tors, propagated to the combined spectra, the overall nor-malization error and the uncertainty in the extrapolation.The latter is evaluated using different fit functions (mod-ified Hagedorn [28] and the UA1 parametrization [29]) orusing a Monte-Carlo generator, matched to the data for (GeV/c) t p - ( G e V / c ) t N / d y dp d e v / N -2 -1 (TPC) + π (TOF) + π (ITS standalone) + π (ITS-TPC) + π (TPC) + K (TOF) + K (ITS standalone) + K (ITS-TPC) + K p (TPC)p (TOF)p (ITS standalone)p (ITS-TPC) (GeV/c) t p - ( G e V / c ) t N / d y dp d e v / N -2 -1 (TPC) - π (TOF) - π (ITS standalone) - π (ITS-TPC) - π (TPC) - K (TOF) - K (ITS standalone) - K (ITS-TPC) - K (TPC)p (TOF)p (ITS standalone)p (ITS-TPC)p Fig. 12. (Color online) Transverse momentum spectrad N/ (d p t d y ) for | y | < p t < /c (PYTHIA [15], with tunes D6T [16], CSCand Perugia0 [30], or PHOJET [18]). While none of thesealternative extrapolations provides a description as goodas the one from the L´evy fit, we estimate from this pro-cedure an uncertainty of about 25% of the extrapolatedpart of the yield.The ratios of π + / π − and K + /K − as a function of p t areclose to unity within the errors, allowing the combinationof both spectra in the L´evy fits. The p/p ratio as a functionof p t has been studied with high precision in our previouspublication [22]. It is p t -independent with a mean value of (GeV/c) t p - ( G e V / c ) t N / d y dp d e v / N -3 -2 -1 , ITS+TPC+TOF - + K + K 2 × K , Kinks - + K + K Fig. 13. (Color online) Comparison of charged kaon spectra,obtained from the combined ITS stand-alone, TPC, TOF anal-ysis, from the kink topology and K s spectra from Ref. [24]. Only statistical errors are shown. . ± . ± . p t . The errors have beendetermined as for the individual fits.Our values on yield and h p t i given in Table 4 and 5agree well with the results from pp collisions at the same √ s [31]. Figure 15 compares the h p t i with measurementsin pp collisions at √ s = 200 GeV [32, 33] and in pp re-actions at √ s = 900 GeV [31]. The mean p t rises verylittle with increasing √ s despite the fact that the spectralshape clearly shows an increasing contribution from hardprocesses. It was already observed at RHIC that the in-crease in mean p t at √ s = 200 GeV compared to studies at √ s = 25 GeV is small. The values obtained in pp collisionsare lower than those for central Au+Au reactions at √ s =200 GeV [32].The spectra presented in this paper are normalizedto inelastic events. In a similar study by the STAR Col-laboration the yields have been normalized to NSD colli-sions [32]. In order to compare these two results, the yieldsin Table 4 have been scaled to NSD events, multiplying by1.185 (see Section 2.2). The yields of pions increase from √ s = 200 GeV to 900 GeV by 23%, while K + rises by 45%and K − by 48%.Figure 16 shows the K/ π ratio as a function of √ s bothin pp (full symbols, [32, 34, 35]) and in pp (open symbols,[36–38]) collisions. For most energies, (K + +K − )/( π + + π − )is plotted, but for some cases only neutral mesons weremeasured and K /π is used instead. The p t -integrated(K + +K − )/( π + + π − ) ratio shows a slight increase from √ s = 200 GeV (K/ π = 0 . ± . √ s = 900 GeV(K/ π =0 . ± . ± . Table 4.
Integrated yield d N /d y ( | y | < .
5) with statistical and systematic errors, and h p t i , as obtained from the fit with theL´evy function together with the lowest p t experimentally accessible, the fraction of extrapolated yield and the χ /ndf of the fit(see text). The systematic error of d N /d y and of the h p t i includes the contributions from the systematic errors of the individualdetectors, from the choice of the functional form for extrapolation and from the absolute normalization.Particle d N /d y h p t i (GeV/ c ) Lowest p t (GeV/ c ) Extrapolation χ /ndf π + . ± . ± .
074 0 . ± . ± .
10 10% 14.23/30 π − . ± . ± .
074 0 . ± . ± .
10 10% 12.46/30K + . ± . ± .
015 0 . ± . ± .
20 13% 12.71/24K − . ± . ± .
015 0 . ± . ± .
20 13% 6.23/24p 0 . ± . ± .
006 0 . ± . ± .
35 21% 13.79/21p 0 . ± . ± .
006 0 . ± . ± .
35 21% 13.46/21
Table 5.
Results of the L´evy fits to combined positive and negative spectra. See text and the caption of Table 4 for details onthe systematic errors.Particle d N /d y C (GeV) n h p t i (GeV/ c ) χ /ndf π + + π − . ± . ± .
15 0 . ± . ± .
001 7 . ± . ± . . ± . ± .
02 19.69/30K + + K − . ± . ± .
03 0 . ± . ± .
005 6 . ± . ± . . ± . ± .
05 8.46/24p + p 0 . ± . ± .
012 0 . ± . ± .
007 7 . ± . ± . . ± . ± .
07 15.70/21 the K/ π ratio keeps rising slowly as a function of √ s orsaturates.Protons and antiprotons in Table 4 have been cor-rected for feed down (mainly from Λ ), while the resultsfrom the STAR Collaboration are not. The proton spec-tra measured by PHENIX, on the other hand, have a lower p t -cut of 0.6 GeV/ c . This makes a direct comparison withRHIC data difficult.Figure 17 shows a comparison of the measured pion,kaon and proton spectra with several tunes of the PYTHIAevent generator [15] and with PHOJET [18]. The PYTHIACSC 306 [39] tune provides a very poor description of theparticle spectra for all species. Similar deviations werealready seen for the unidentified charged hadron spec-tra [13]. The other PYTHIA tunes, Perugia0 [30] andD6T [16], and PHOJET give a reasonable description ofthe charged pion spectra, but show large deviations in thekaon and proton spectra. The measured kaon p t -spectrumfalls more slowly with increasing p t than the event genera-tors predict. A similar trend is seen for the proton spectra,except for PYTHIA tune D6T, which describes the protonspectra reasonably well.The upper panel of Figure 18 shows the p t -dependenceof the K/ π and also the measurements by the E735 [36]and STAR Collaborations [32]. It can be seen that theobserved increase of K/ π with p t does not depend stronglyon collision energy.A comparison with event generators shows that at p t > c , the measured K/ π ratio is larger than any ofthe model predictions. It is interesting to note that whilethe spectra in the CSC tune are much steeper than theother tunes, the p t -dependence of the K/ π ratio is verysimilar. In the models, the amount of strangeness produc-tion depends on the production ratios of gluons and thedifferent quark flavours in the hard scattering and on thestrangeness suppression in the string breaking. The latter could probably be tuned to better describe the data. Asimilar disagreement between measured strangeness pro-duction and PYTHIA predictions was found at RHIC en-ergies [40].In the bottom panel of Figure 18, the measured p/ π ratio is compared to results at √ s = 200 GeV from thePHENIX Collaboration [41]. Both measurements are feed-down corrected. At low p t , there is no energy-dependenceof the p /π ratio visible, while at higher p t > c , thep/ π ratio is larger at √ s = 900 GeV than at √ s = 200 GeVenergy.Event generators seem to separate into two groups,one with high p/ π ratio (PYTHIA CSC and D6T), whichagree better with the data and one group with a lowerp/ π ratio (PHOJET and PYTHIA Perugia0), which areclearly below the measured values. These comparisons canbe used for future tunes of baryon production in the eventgenerators. We present the first analysis of transverse momentum spec-tra of identified hadrons, π + , π − , K + , K − , p, and p in ppcollisions at √ s = 900 GeV with the ALICE detector. Theidentification has been performed using the d E /d x of theinner silicon tracker, the d E /d x in the gas of the TPC,the kink topology of the decaying kaons inside the TPCand the time-of-flight information from TOF. The combi-nation of these techniques allows us to cover a broad rangeof momentum.Agreement in the K/ π ratio is seen when comparingto pp collisions at the Tevatron and SppS. Comparing ourresults with a similar measurement from the STAR Col-laboration using pp collisions at √ s = 200 GeV the shapeof the spectra shows an increase of the hard component, (GeV/c) t p - ( G e V / c ) t N / d y dp d e v / N -3 -2 -1 Positive + π + Kp (GeV/c) t p - ( G e V / c ) t N / d y dp d e v / N -3 -2 -1 Negative - π - Kp Fig. 14. (Color online) Transverse momentum spectra of pos-itive (top) and negative (bottom) hadrons from pp collisionsat √ s = 900 GeV. Grey bands: total p t -dependent error (sys-tematic plus statistical); normalization systematic error (3.6%)not shown. The curves represent fits using a L´evy function. but we observe only a slight increase of the mean p t -values.Whether the fraction of strange to non-strange particlesrises with increasing √ s remains open until data at 7 TeVbecome available. ) M (GeV/c ( G e V / c ) 〉 t p 〈 = 900 GeVsALICE, pp, = 900 GeVsp, pUA5, = 200 GeVsSTAR/PHENIX, pp, π K p
Fig. 15. (Color online) Mean p t as a function of the mass of theemitted particle in pp collisions at 900 GeV (ALICE, red solidcircles, statistical and systematic errors) compared to resultsat √ s = 200 GeV (star markers, average values of the resultsfrom the STAR and the PHENIX Collaborations [32, 33]) andpp reactions at √ s = 900 GeV [31] (open squares). Some datapoints are displaced for clarity. (GeV)s π K / Fig. 16. (Color online) Ratios (K + +K − )/( π + + π − ) and K /π as a function of √ s . Data (full symbols) are from pp collisions,(at √ s = 17.9 GeV by NA49 [34, 35], at √ s = 200 GeV bySTAR [32] and at √ s = 900 ALICE, present work) and (opensymbols) from pp interaction (at √ s = 560 GeV by UA5 [37]and at the TEVATRON by E735 [36, 38]).0 - ( G e V / c ) t N / d y dp d e v / N -2 -1 DataPhojetPythia - CSC 306Pythia - D6T 109Pythia - Perugia0 - 320 - π + + π (GeV/c) t p D a t a / M C - ( G e V / c ) t N / d y dp d e v / N -2 -1 DataPhojetPythia - CSC 306Pythia - D6T 109Pythia - Perugia0 - 320 - +K + K (GeV/c) t p D a t a / M C - ( G e V / c ) t N / d y dp d e v / N -2 -1 DataPhojetPythia - CSC 306Pythia - D6T 109Pythia - Perugia0 - 320 pp+ (GeV/c) t p D a t a / M C Fig. 17. (Color online) Comparison of measured pion, kaonand proton spectra at √ s = 900 GeV (both charges combined)with various tunes of event generators. Statistical errors only.See text for details. ) - π + + π ) / ( - + K + ( K PhojetPythia - CSC 306Pythia - D6T 109Pythia - Perugia0 - 320 = 900 GeVsALICE, = 200 GeVsSTAR, = 1800 GeVsE735, ) - π + + π ) / ( p ( p + PhojetPythia - CSC 306Pythia - D6T 109Pythia - Perugia0 - 320 = 900 GeVsALICE, = 200 GeVsPHENIX,
Fig. 18. (Color online) Ratios of (K + + K − )/( π + + π − ) (up-per panel) and (p + p) / ( π + + π − ) (lower panel) as a functionof p t from pp collisions at √ s = 900 GeV (statistical errorsonly). Values from the E735 Collaboration [36] and the STARCollaboration [32](upper part) and from the PHENIX Collabo-ration [41] (lower part) also are given. The dashed and dottedcurves refer to calculations using PYTHIA and PHOJET at √ s = 900 GeV.1 Acknowledgements
The ALICE collaboration would like to thank all its en-gineers and technicians for their invaluable contributionsto the construction of the experiment and the CERN ac-celerator teams for the outstanding performance of theLHC complex.The ALICE collaboration acknowledges the following fund-ing agencies for their support in building and running theALICE detector:Department of Science and Technology, South Africa;Calouste Gulbenkian Foundation from Lisbon and SwissFonds Kidagan, Armenia;Conselho Nacional de Desenvolvimento Cient´ıfico e Tec-nol´ogico (CNPq), Financiadora de Estudos e Projetos (FINEP),Funda¸c˜ao de Amparo `a Pesquisa do Estado de S˜ao Paulo(FAPESP);National Natural Science Foundation of China (NSFC),the Chinese Ministry of Education (CMOE) and the Min-istry of Science and Technology of China (MSTC);Ministry of Education and Youth of the Czech Republic;Danish Natural Science Research Council, the CarlsbergFoundation and the Danish National Research Founda-tion;The European Research Council under the European Com-munity’s Seventh Framework Programme;Helsinki Institute of Physics and the Academy of Finland;French CNRS-IN2P3, the ‘Region Pays de Loire’, ‘RegionAlsace’, ‘Region Auvergne’ and CEA, France;German BMBF and the Helmholtz Association;Hungarian OTKA and National Office for Research andTechnology (NKTH);Department of Atomic Energy and Department of Scienceand Technology of the Government of India;Istituto Nazionale di Fisica Nucleare (INFN) of Italy;MEXT Grant-in-Aid for Specially Promoted Research, Ja-pan;Joint Institute for Nuclear Research, Dubna;National Research Foundation of Korea (NRF);CONACYT, DGAPA, M´exico, ALFA-EC and the HELENProgram (High-Energy physics Latin-American–EuropeanNetwork);Stichting voor Fundamenteel Onderzoek der Materie (FOM)and the Nederlandse Organisatie voor WetenschappelijkOnderzoek (NWO), Netherlands;Research Council of Norway (NFR);Polish Ministry of Science and Higher Education;National Authority for Scientific Research - NASR (Au-toritatea Nat¸ional˘a pentru Cercetare S¸tiint¸ific˘a - ANCS);Federal Agency of Science of the Ministry of Educationand Science of Russian Federation, International Scienceand Technology Center, Russian Academy of Sciences,Russian Federal Agency of Atomic Energy, Russian Fed-eral Agency for Science and Innovations and CERN-INTAS;Ministry of Education of Slovakia;CIEMAT, EELA, Ministerio de Educaci´on y Ciencia ofSpain, Xunta de Galicia (Conseller´ıa de Educaci´on), CEA-DEN, Cubaenerg´ıa, Cuba, and IAEA (International AtomicEnergy Agency); Swedish Reseach Council (VR) and Knut & Alice Wallen-berg Foundation (KAW);Ukraine Ministry of Education and Science;United Kingdom Science and Technology Facilities Coun-cil (STFC);The United States Department of Energy, the United StatesNational Science Foundation, the State of Texas, and theState of Ohio.
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