1. Vasundhara Chetluru December 17, 2015 University of Illinois, Chicago Antiparticle to particle ratios measurement using the PHOBOS detector

2. 2 Vasundhara Chetluru 12/17/2015 Contents Motivation for studying particle ratios is heavy ion collisions PHOBOS @ RHIC  Detector description Like particle ratios analysis  Analysis details  Results & discussion

3. Motivation for studying particle ratios is heavy ion collisions 3 Vasundhara Chetluru 12/17/2015 Initial Geometry Parton Production Hadron Formation Chemical Freezeout Thermal Freezeout 0 fm/c ~2 fm/c ~7 fm/c>7fm/c Time Antiparticle to particle ratios probe hadron formation & chemical freeze-out stages. In p+p & d+Au collisions little re-interaction is expected thus the ratios should reflect the initially produced yields. Do these different conditions influence the measured particle ratios in Cu+Cu and Au+Au?

4. Relativistic Heavy Ion Collider 2.5 miles circumference 4 Experiments 5 years and more of running

5. Relativistic Heavy Ion Collider 5 Vasundhara Chetluru 12/17/2015 Au+Au: 19.6, 56, 62.4, 130, 200 GeV p+p: 200, 410 GeV Cu+Cu: 22, 62.4, 200 GeV d+Au: 200 GeV

6. PHOBOS Experiment

7. PHOBOS 7 Vasundhara Chetluru 12/17/2015 UIC has led the effort of Building of Octagon, Vertex and the Ring detectors. Designing and maintaining of the trigger and its electronics, from 2000 forward.  Scintillator Paddles + Zero Degree  Calorimeter for triggering  TOF wall for high-momentum PID  96000 Silicon Pad channels  4π Multiplicity Array  Mid-rapidity Spectrometer Millions of events to tape

8. Run V (2005) Cu+Cu data joined the group Onsite Trigger support Calibrating and maintaining the T0 vertex trigger

9. Collision Centrality 9 Vasundhara Chetluru 12/17/2015 Magnitude of signals in paddle counters determines centrality Negative Paddles Positive Paddles ZDC NZDC P Au x z PP PN Paddle signal (a.u.)‏ Data Counts Larger signal = more central collision. Central Collision:  Large N part Peripheral Collision:  Small number of participating nucleons “side” view of colliding nuclei Slide from David Hofman’s talk

10. Like antiparticle to particle ratios Analysis description

11. Definition 11 Vasundhara Chetluru 12/17/2015 I dentified anti-particle/particle count per event

12. Definition 12 Vasundhara Chetluru 12/17/2015 I dentified anti-particle/particle count per event As a function of centrality of the collisions and transverse momentum of the particles.

13. PHOBOS Spectrometer 13 Vasundhara Chetluru 12/17/2015 Schematic Diagram near mid-rapidity Z B1B1 Cartoon Two symmetric spectrometer arms give two independent measurements. Outer 9 layers of the 15 layers are located in 2T magnetic field Coverage near mid-rapidity and Tracking within 10 cm of interaction point. PHOBOS magnet polarity is changed every couple of days. Two independent measurements are taken for each polarity.

14. Acceptance Z Z 12/17/2015 14 Vasundhara Chetluru Cu+Cu 200 GeV data

15. Magnetic field settings For a given bending direction and opposite field settings Ratios are measured independently for different bending directions. 12/17/2015 15 Vasundhara Chetluru near mid-rapidity Z B1B1 Z B2B2 2 Arms X 2 Bending-directions = 4 Measurements

16. Particle ratios and acceptance 16 Vasundhara Chetluru 12/17/2015 Forward Bending Backward Bending

17. Tracking – momentum determination. Particle identification. Measuring particle ratios 17 Vasundhara Chetluru 12/17/2015

18. Tracking in the PHOBOS Spectrometer 1. Road-following algorithm finds straight tracks in field-free region 2. Curved tracks in B-field found by clusters in (1/p,  ) space 3. Match pieces by , consistency in dE/dx and fit in yz-plane 4. Covariance Matrix Track Fit for momentum reconstruction and ghost rejection 18 Vasundhara Chetluru 12/17/2015

19. Tracking in the PHOBOS Spectrometer 1. Road-following algorithm finds straight tracks in field-free region 2. Curved tracks in B-field found by clusters in (1/p,  ) space 3. Match pieces by , consistency in dE/dx and fit in yz-plane 4. Covariance Matrix Track Fit for momentum reconstruction and ghost rejection 19 Vasundhara Chetluru 12/17/2015

20. Tracking in the PHOBOS Spectrometer 1. Road-following algorithm finds straight tracks in field-free region 2. Curved tracks in B-field found by clusters in (1/p,  ) space 3. Match pieces by , consistency in dE/dx and fit in yz-plane 4. Covariance Matrix Track Fit for momentum reconstruction and ghost rejection 20 Vasundhara Chetluru 12/17/2015

21. Tracking in the PHOBOS Spectrometer 1. Road-following algorithm finds straight tracks in field-free region 2. Curved tracks in B-field found by clusters in (1/p, ∆  ) space 3. Match pieces by , consistency in dE/dx and fit in yz-plane 4. Covariance Matrix Track Fit for momentum reconstruction and ghost rejection 21 Vasundhara Chetluru 12/17/2015

22. Tracking in the PHOBOS Spectrometer 1. Road-following algorithm finds straight tracks in field-free region 2. Curved tracks in B-field found by clusters in (1/p, ∆  ) space 3. Match pieces by , consistency in dE/dx and fit in yz-plane 4. Covariance Matrix Track Fit for momentum reconstruction and ghost rejection 22 Vasundhara Chetluru 12/17/2015 Momentum determined with resolution of ~1% ∆∆

23. Uses momentum and the energy loss Particle identification

24. Particle identification (PID) 24 Vasundhara Chetluru 12/17/2015 Cu+Cu 200 GeV MC The hits that particles produce provide both momentum information (determined from the position of the hit) and energy loss information (determined from the ionization produced by the particle). The different energy loss characteristics of pions, kaons, and protons can be used conjointly with momentum to identify the particle type of a track.

25. Particle identification (PID) 25 Vasundhara Chetluru 12/17/2015 dE/dx slice for Momentum=0.5 Bin Pions Kaons Protons Cu+Cu 200 GeV MC

26. PID Bands Limit in momentum is obtained by 3-σ limit of the over lapping bands 12/17/2015 26 Vasundhara Chetluru Cu+Cu 200 GeV MC

27. Raw Ratios 27 Vasundhara Chetluru 12/17/2015 Cu+Cu 200 GeV Data

28. Raw Ratios 28 Vasundhara Chetluru 12/17/2015 Cu+Cu 200 GeV Data

29. The yield of the produced (primary) particles is changed due to a variety of reasons, by the time they hit detector material. Corrections to the measured particles ratios (which are called raw ratios) are applied to account for this change. Corrections to the obtained raw ratios

30. General formula correction 30 Vasundhara Chetluru 12/17/2015 Let h represent the yield and ∆h change in the yield due detector effects or feed- down. This change can be positive or negative. Then h+ ∆h represents the measured yield (ignoring the efficiency correction). c represents the correction factor. This is usually obtained using HIJING monte-carlo generator.

31. Feed-down 12/17/2015 31 Vasundhara Chetluru Accounts for hyperon decay products. Mainly effects the proton ratio. Lambda’s account for the most significant feed-down contribution to the proton yields. As  (  ) = 0.26 ns and c  (  ) = 7.89 cm  Spectrometer ~10 cm from interaction point.  Apply strict distance of closest approach cut to each track. Cu+Cu 200 GeV MC MC Feed-down

32. Secondary Corrections As the primary collision products pass through the beam pipe and detector materials, secondary particles are produced. Those which pass through the spectrometer may be reconstructed along with the primary particles. The effect of secondaries is negligible is kaons. While the protons and pions have 2% and 1% correction effectively. 12/17/2015 32 Vasundhara Chetluru

33. Absorption Correction As the collision products pass through the detector, some of them are absorbed. This results in a loss of anti-particles versus particles and a decrease in the anti-particle to particle ratio. Correction is obtained by studying the effect of hadronic interactions in the detector using HIJING. 5%,0.05% and 1% for protons, pions and kaons respectively. 12/17/2015 33 Vasundhara Chetluru p T GeV/C Absorption co-efficient Protons Antiprotons Cu+Cu 200 GeV MC

34. Band-width, Beam-Orbit, DCA cut Paddle-time Difference Track fit probability, Vertex in Z Systematic error study

35. Systematic uncertainties, which arise from event selection, particle identification cuts, and the three correction factors are studied. No single uncertainty (parameter) dominates the final systematic error, typically the smallest contribution comes from the PID cuts and the largest from either the event selection or, in the case of the proton ratios, the feed-down correction. The final systematic uncertainty for a given centrality is determined from the statistically weighted average of the uncertainty determined for each parameter for different arms and bending directions. A thorough investigation of the track selection χ 2 probability cut has shown a variation independent of the species and arm, but dependent on the bending direction. Hence, this effect yields a scale systematic uncertainty that, for each collision energy, is independent of both centrality and particle species. 35 Vasundhara Chetluru 12/17/2015

36. Plot with systematic studies 36 Vasundhara Chetluru 12/17/2015 Pions have the smallest systematic variations. Track-fit probability has the largest contribution for all 3 species. Systematic errors are studied as a function of centrality bin. Systematic errorProtonsKaonsPions Cu+Cu 62.4 GeV0.030.020.03 Cu+Cu 200 GeV0.040.020.03

37. Results

38. Discussion of results 38 Vasundhara Chetluru 12/17/2015 No strong dependence on centrality is observed for the Cu+Cu data. The final values for the antiparticle to particle ratios of pions, kaons and protons appear to be primarily driven by the collision energy and, within current systematic uncertainties, are largely independent of the colliding system. A detailed comparison of the central Cu+Cu results at 200 GeV to results from p+p, d+Au, and central Au+Au collisions at RHIC indicates that the antiparticle to particle ratios are, for the most part, insensitive to the collision species. Average p T Cu+CuProtonKaonPion 200 GeV0.310.370.51 62.4 GeV0.310.360.50 Open (closed) circles represent √s NN = 62.4 GeV (200 GeV) data. The error bars represent the combined (1 σ ) statistical and systematic uncertainties

39. Discussion of results 39 Vasundhara Chetluru 12/17/2015 Thermal models Make the assumption that the initial state has time to thermalize and this “chemical” thermal nature is preserved during hadronization. Can fit each energy with a common chemical “freeze-out” temperature, T ch, and baryon chemical potential m B. Suggests a high degree of chemical equilibrium (and thermalization) at the point where particles are “frozen-out” (created). Baryon transport Participating nucleons experience multiple collisions Causes loss of incident momentum and energy Can lead to “stopping” of nucleon in CM frame; ie. transport to  = 90° w.r.t. beam axis. Open (closed) circles represent √s NN = 62.4 GeV (200 GeV) data. The error bars represent the combined (1 σ ) statistical and systematic uncertainties

40. Backup

41. Phase diagram 41 Vasundhara Chetluru 12/17/2015 BB Temperature (MeV) Abigail Bickley’s talk

42. Thermal Models 42 Vasundhara Chetluru 12/17/2015  Only µ B and T are free parameters if look at production. Make the assumption that the initial state has time to thermalize and this “chemical” thermal nature is preserved during hadronization. Have a chemical potential m for every conserved quantum number Constrain parameters with conservation laws Grand Canonical Ensemble Braun-Munzinger, Redlich, Stachel - nucl-th/0304013; Stachel – Trento - 2004

43. Thermal Model 43 Vasundhara Chetluru 12/17/2015 CTEQ 2006 Phys Lett. B. 518, 41 (2001); J. Phys G28, 1745 (2002) Can fit each energy with a common chemical “freeze-out” temperature, T ch, and baryon chemical potential m B. Suggests a high degree of chemical equilibrium (and thermalization) at the point where particles are “frozen-out” (created).

44. Baryon transport Proton yield from transport and pair production Antiprotons generated via pair production 44 Vasundhara Chetluru 12/17/2015 The pair production mechanism is symmetric,

45. 45 Analysis Flow Chart Vasundhara Chetluru 12/17/2015

46. 46 Vasundhara Chetluru 12/17/2015 RHIC other experiments

47. Trigger studies 47 Vasundhara Chetluru 12/17/2015

48. Charged particle spectra 48 Vasundhara Chetluru 12/17/2015 Au+Au: PRL 94, 082304 (2005), PLB 578, 297 (2004) d+Au: Phys. Rev. Lett. 91, 072302 (2003) preliminary 62.4 GeV 200 GeV Cu+Cu d+Au Au+Au PHOBOS centrality

49. Flow 49 Vasundhara Chetluru 12/17/2015 Au+Au 19.6 GeV62.4 GeV130 GeV 200 GeV preliminary PHOBOS Cu+Cu Au+Au: PRL 94 122303 (2005) Au+Au preliminary PHOBOS

50. 50 Vasundhara Chetluru 12/17/2015 Rapidity & Transport Rapidity:  Longitudinal motion  Used if PID and p known Pseudorapidity:   = polar angle to beam axis  Used if PID and p not known Mid-Rapidity:  = 90°, p || = 0  y,  0 @ mid-rapidity  Particles measured at mid-rapidity Generated in collision Transported from beam rapidity Au mid forward

51. Beam-orbit study 51 Vasundhara Chetluru 12/17/2015 Beam-orbit – Mean reconstructed vertex position of the collision in the transverse plane for a given run. Steady beam-orbit ensures acceptance and efficiency cancellation for different polarities. Data over the whole run range is classified depending on shifts in the beam-orbit. Ratios are calculated independently for each steady beam-orbit region.

52. Data quality studies Careful checking the data for any kind of anomalous behavior. Plot below is an example of the average number of tracks per event study. 52 Vasundhara Chetluru 12/17/2015 Different colors represent different magnetic field settings

53. Spectrometer Performance 53 Vasundhara Chetluru 12/17/2015 Data Sample Production Run 2001(200 GeV) 7.8 M Au+Au Events, Min. Bias Trigger 32 M reconstructed particles Acceptance Momentum Resolution

54. Energy Loss 54 Vasundhara Chetluru 12/17/2015 The probability of interaction is statistical and can be characterized by the average amount of energy lost per unit path length, dE/dx. Experimentally dE/dx is measured in units of minimum ionizing particles, MIPS. A MIP is defined as the minimum value of the dE/dx for a given material and is applicable to particles traveling at relativistic velocities, ≥ 0.9c. Particles studied have momenta below the “relativistic rise”.

55. Bethe-Bloch function 55 Vasundhara Chetluru 12/17/2015 β= v / c vvelocity of the particle Eenergy of the particle xdistance travelled by the particle cspeed of light particle charge echarge of the electronelectron meme rest mass of the electron nelectron density of the target Imean excitation potential of the target permittivitypermittivity of free space

56. Technique II - For PID band determination 56 Vasundhara Chetluru 12/17/2015 Bethe-Bloch parameterization is used to represent the data.

57. Technique II - For PID band determination 57 Vasundhara Chetluru 12/17/2015 Correction function to the Bethe- Bloch is obtained

58. Trigger callibration

59. TAC Plot 59 Vasundhara Chetluru 12/17/2015 Triggering on the time difference between the T0 hits on both sides. It essentially narrows the collision vertex range, ensuring good data quality. Calibration and efficiency studies are the essential parts of running this trigger. Time T0P (ns) Time T0N (ns)

60. TAC Plot 60 Vasundhara Chetluru Triggering on the time difference between the T0 hits on both sides. It essentially narrows the collision vertex range, ensuring good data quality. Calibration and efficiency studies are the essential parts of running this trigger. 12/17/2015 Time T0P (ns) Time T0N (ns)

61. Triggered hadron correlations Tracking tuning for heavy ions CMS Effort 61 Vasundhara Chetluru 12/17/2015

62. Triggered Hadron Correlatrions Jets are being used as tomographic probes to explore the medium created in ultra relativistic heavy ion collisions. At RHIC, tomographic probes provided the evidence of strongly interacting matter. Evolution of triggered correlation functions indicated additional physics phenomenon. We intend to utilize these techniques to explore the matter properties in the energy domain at LHC where the properties of the created matter remains a mystery. 62 Vasundhara Chetluru 12/17/2015 hadrons q q leading particle leading particle Schematic diagram of a di-jet in a heavy ion collision.

63. Motivation 63 Vasundhara Chetluru 12/17/2015 4 < p T (trig) < 6 GeV/cp T (assoc) > 2 GeV/c Away side jet is suppressed for central Au+Au collisions. Evidence of jet medium interactions, partial thermalization of the medium.

64. Signal + Background 64 Vasundhara Chetluru 12/17/2015 Signal + Background : Δη-Δφ correlation with respect to the trigger particle (leading particle) in a given event. Normalized by the total triggers. Background estimated by mixed events technique: Δη-Δφ correlation correlation with respect to the trigger particle from a different event with a similar p T. Hydjet Pb-Pb 5500GeV, |η| 2.0 0-10 % central collisions. Trigger – 15<p T <20

65. Tracking tuning for high pT 65 Vasundhara Chetluru 12/17/2015 Algorithmic efficiency Closed symbols – Effiency Open symbols – Fake-rate Tuning tracking reconstruction algorithm for high pT tracks.