Studies of the jet fragmentation in p+p collisions in STAR Elena Bruna Yale University STAR Collaboration meeting, June

OUTLINE Jets in p+p at STAR Jet reconstruction: Jet Finding Algorithm Theoretical and Experimental Issues in Jet Finding Performance Fragmentation functions on p+p events Conclusions 2 Elena Bruna, Yale University

HIGH-p T AT RHIC 3 Elena Bruna, Yale University p+p collisions

JETS IN p+p COLLISIONS Hard probes  early times Calculable in pQCD: factorization theorem 4 Elena Bruna, Yale University pp a, x a b, x b σ ab c, x c d, x d D D Jet cross section:

JET RECONSTRUCTION Jet = collimated spray of high energy hadrons Interplay between theory and experiment: THEORY: “calculate” the real jet EXPERIMENT: measure the jet 5 Elena Bruna, Yale University Why reconstruct jets? Full knowledge of jet properties: jet shape, fragmentation functions, energy, … IDEA: going from tracks and EMC towers to jets  Jet Finding Theoretical and experimental issues in Jet Finding Jet Finding Algorithms Cone algorithms K T algorithms

THEORETICAL ISSUES Required THEORETICAL features in a jet finding algorithm: Collinear safety : the algorithm should be insensitive to any collinear radiation.  Example A: if the energy is split among soft particles, and each tower is under a threshold, the jet is lost 6 Elena Bruna, Yale University OK BAD: 2 jets are merged in one A  Example B: if the energy of a parton is split in two towers, and the algorithm starts with the particles with highest E, a different jet may be found B Infrared safety : the algorithm should not be sensitive to soft radiation

EXPERIMENTAL ISSUES Required EXPERIMENTAL features in a jet finding algorithm: Detector independence : the performance of the jet algorithm should not be dependent on detector segmentation, energy resolution, … Stability with luminosity : jet finding should not be strongly affected by multiple hard scatterings at high beam luminosities. Fast Efficient : the jet algorithm should find as many physically interesting jets as possible 7 Elena Bruna, Yale University

CONE ALGORITHM A ‘ seed ’ defines the approximate jet direction  seed = track with E>E threshold Tracks which are within a radius of R<R cone are taken (R=√( Δ Φ 2 + Δ η 2 )) The centroid of the cone is given by summing the momenta of the particles inside the cone The centroid becomes the new seed : procedure iterated until the seed position is stable 8 Elena Bruna, Yale University R cone seed R cone centroid = new seed tracks or towers

PART I: searching midpoint Search for missing jets using the midpoint of all the pairs of found jets as seed PART II: splitting/merging This stage starts once stable cones have been found (see previous slide) IDEA: disentangle jets which share common towers in the calorimeter MIDPOINT CONE ALGORITHM 9 Elena Bruna, Yale University midpoint JET #1 p Tjet1 >p Tjet2 JET #2 1. Take the lower-p T jet (#2) 2. f =E shared /E jet#2 3. if f>50% then MERGE jet#1 and jet#2 else SPLIT the jets

K T JET ALGORITHM Start with a list of preclusters, i.e. 4-vectors of tracks, and calorimeter towers. Each precluster is defined by: E, p, y. Calculate: For each precluster i : For each pair ( i,j ) of preclusters: ( D is a parameter of the jet algorithm) Find the minimum of all the d i and d ij and label it d min If d min is a d ij, remove preclusters i and j from the list and replace them with a new merged precluster If d min is a d i, the precluster i is not “mergeable” and it can be added to the list of jets. Repeat the procedure until the list of preclusters is empty, i.e. all the jets have been found 10 Elena Bruna, Yale University

RECENT RESULTS AND PERSPECTIVES Inclusive differential cross section for p+p  jet + X measured by STAR with polarized proton beams. Increased L in 2006: High-p T jets PID of jet fragments GOALS for STAR: 11 Elena Bruna, Yale University data Study of the fragmentation functions for particles inside jets in p+p for different jet energies and opening angles Measure jets in Au+Au Study the hadrochemical modifications of jets in the nuclear medium

MIDPOINT CONE JET FINDING IN p+p IN STAR Performance study DATA: p+p PYTHIA events (2006) Jet Finder applied to: PYTHIA particles  PYTHIA Jets (no detector effects) Reconstructed tracks and calorimeter towers  RECO Jets (detector effects) SETUP for the Jet Finder: R=0.7 ( ϑ c ~ 0.49 rad), |η jet |<0.3 R=0.5 ( ϑ c ~ 0.35 rad), |η jet |<0.5 R=0.4 ( ϑ c ~ 0.28 rad), |η jet |<0.6 seed: E T >0.5 GeV PYTHIA Jets vs RECO Jets Only the leading RECO Jets are considered 12 Elena Bruna, Yale University η=-1 η=+1 JET z R=0.7  jet =0.3

ENERGY RESOLUTION (1 of 2) 13 Elena Bruna, Yale University 10<E(PYTHIA)<10.3 GeV20<E(PYTHIA)<20.5 GeV 30<E(PYTHIA)<30.5 GeV BLACK = RECO jet RED = PYTHIA jet BLACK = RECO jet RED = PYTHIA jet BLACK = RECO jet RED = PYTHIA jet R=0.7

ENERGY RESOLUTION (2 of 2) 14 Elena Bruna, Yale University R=0.7

15 Elena Bruna, Yale University 10<E(PYTHIA)<10.3 GeV20<E(PYTHIA)<20.5 GeV 30<E(PYTHIA)<30.5 GeV MULTIPLICITY OF JET FRAGMENTS (1 of 2) BLACK = RECO jet RED = PYTHIA jet R=0.7

MULTIPLICITY OF JET FRAGMENTS (2 of 2) 16 Elena Bruna, Yale University 10<E(PYTHIA)<10.3 GeV BLACK = RECO jet RED = PYTHIA jet R=0.7 all particles charged particles neutral particles

JETS IN VACUUM 17 MLLA (modified leading logarithmic approximation) formalism provides a good description of fragmentation functions in e+e- and ppbar collisions. e+e-√s=29 GeV H. Aihara et al. (TPC/2  coll.), PRL 52, 577 (1984) STAR p+p 2006 data: Measure fragmentation functions in p+p at 200 GeV as baseline for Au+Au test pQCD models (MLLA, …) phphphph1 5.4 GeV/c Gev/c GeV/c GeV/c GeV/c

JET QUENCHING IN HOT NUCLEAR MATTER Signatures: Modification of jet energy distributions Modification of jet fragmentation functions Modification of the hadrochemical composition of the jet fragments [Sapeta, Wiedemann arXiv: ] Medium-modified MLLA (includes hadrochemistry predictions): IDEA: in-medium gluon radiation implies an enhancement of the parton splitting MODEL: the parton splitting functions are enhanced by a common factor [Sapeta, Wiedemann arXiv: ] 18 Elena Bruna, Yale University

MODEL PREDICTIONS 19 Elena Bruna, Yale University [Sapeta, Wiedemann arXiv: ] Full jet reconstruction and PID inside jets in both p+p and A-A is required

JETS ON REAL DATA: p+p (2006) p+p 2006 data set: Luminosity ~8.7 pb M Jet Patch events STAR Triggers: MinBias:  Beam-Beam-Counter (BBC) High Tower:  BBC + 1 tower (0.05  x 0.05  with E T >5.4 GeV Jet Patch :  BBC+ 20x20 towers (patch, 1  x 1  ) withE T >8 GeV 20 Elena Bruna, Yale University

ξDISTRIBUTIONS FOR CHARGED HADRONS (1 of 2) 2 jet energies: 30<E jet <40 GeV 40<E jet <50 GeV  distributions compared with PYTHIA simulations 21 Elena Bruna, Yale University Very good agreement between data and PYTHIA

ξ FOR CHARGED HADRONS (1 of 2) 22 Elena Bruna, Yale University

SUMMARY AND OUTLOOK Full jet reconstruction in p+p at RHIC is needed as a baseline to study hadrochemical modifications of jets in Au+Au collisions The standard jet finding algorithm (midpoint cone) has been tested on PYTHIA events with different settings of the parameters (seed, Radius) Test other algorithms: K T, … Analysis on p+p (run 2006): in progress Fragmentation functions: charged particles, p, K, π, e, Λ, … 23 Elena Bruna, Yale University

EXTRA SLIDES 24 Elena Bruna, Yale University

TRIGGER BIAS: JET PATCH VS HIGH TOWER 25 Elena Bruna, Yale University