Exclusive p  Electro-production from the Neutron

1. Exclusive pElectro-production from the Neutron Jixie Zhang Old Dominion University (BoNuS, CLAS Collaboration)

2. Outline • Goal: Neutron resonances • Why neutron? • Experiment setup • Data Analysis • Summary

3. Motivation • Electron excitation of the proton resonances have been studied in detail with high statistics. • Neutron resonances are also very interesting. They are necessary to understand the isospin structure of the resonances. • However, we have almost no electron scattering data from the neutron yet because there are no free neutron targets. • Most of the data we have were taken with deuteron targets. We need to deal with binding, Fermi motion and off-shell effects. p+ production from the proton:differentialcross-section s vs. W for 1 bin in Q2, cosq* andf* K.Park,et al.,CLAS collaboration, Phys. Rev. C. 77, 015208 (2008).

4. pT = 0 Modification of the off-shell scattering amplitude (Thomas, Melnitchouk et al.) Color delocalizationClose et al. Suppression of “point-like configurations”Frankfurt, Strikman et al. 939 MeV 905 MeV 823 MeV 694 MeV “Off-shell” mass of the nucleon M* Ps = 0 0.09 0.17 0.25 0.32 0.39 GeV/c Deviations from free structure function: Off-shell Effects

5. Ciofi degli Atti and Kopeliovich, Eur. Phys. J. A17(2003)133 Deviations from the simple “spectator” picture: Final State Interaction The ratio of spectral functions with and without FSI corrections is shown as a function of spectator momentum ps and θpq (the angle between spectator proton and the virtual photon). For low spectator momenta (ps<100 MeV/c), the effects at backward angles (θpq >120o) are quite small (about 5%). Requiring low ps and large θpq allows us to ignore the FSI.

6. e` p- g* n p p e ps Solution Detect at least ONE of the two final state protons in D(e,e’p-pps) to ensure exclusivity, and select events where the “spectator” proton has low, backwards momentum. Conservation of energy and momentum allows us to determine the initial state of the neutron. d Low momentum spectator proton Novel approach by the BoNuS collaboration: detectthe spectator proton directly.

7. E,k w,q E,k Leptonic plane Exclusive virtual photon cross-section: the response functions Ri(Q2,W,q*) are bilinear combinations of the helicity amplitudes;  and eL are defined as p- f* q* n p Hadronic plane p-Production Kinematics g* n p- p Q2 = -(qµ)2 = 4sin2(qe/2) W2 = (qµ + nµ )2 = (qµ + dµ - psµ)2 q* = angle between the emitted and the virtual photon in C.M. frame f* = angle between the leptonic and hadronic planes

8. Jefferson Lab Experiment E03-012Barely off-shell Nucleon Structure (BoNuS) Electron beam energies: 2.1, 4.2, 5.3 GeV Spectator protons were detected by the newly built Radial Time Projection Chamber (RTPC) Scattered electrons and other final state particles were detected by CEBAF Large Acceptance Spectrometer (CLAS) Target: 7 atm D2 gas, 20 cm long Data were taken from Sep. to Dec. in 2005

9. CLAS in Jefferson Lab, Hall B

10. Torus Magnet

11. Drift Chamber

12. Cherenkov Counter

13. Scintillation Counter

14. Electromagnetic Calorimeter

15. Faraday Cup

16. Radial Time Projection Chamber (RTPC)

17. Sensitive to protons with momenta of 67-250 MeV/c 3 layers of GEM foils 3200 pads (channels) 5 Tesla B field Particles ID by dE/dx 7Atm. D2 gas target, 20 cm in length Trigger Electron 3-D tracking: time of drift -> r pad position -> f, z Helium/DME at 80/20 ratio 140 µm dE/dX BoNuS RTPC Detector

18. The Drift Path of An Ionized Electron A MAGBOLTZ simulation of the crossed E and B fields, together with the drift gas mixture, determines the drift path and the drift velocity of the electrons. • The red lines show the drift path of each ionization electron that would appear on a given channel. • In green is the spatial reconstruction of where the ionization took place. • In reconstruction, hits which are close to each other in space are linked together and fit to a helical trajectory. • This resulting helix tells us the vertex position and the initial three momentum of the particle.

19. FC RTPC Sits in the Center of CLAS BoNuS RTPC CLAS

20. Data analysis Simulation Overview Event generator (fsgen) Gsim post processing Energy loss correction ( one of the input for momentum correction) Acceptance correction Data set selection (quality checks) Particle identification (electron, pion, proton, kaon) Calibrations and corrections D(e, e p- pclasps) event selection and preliminary results D(e, e ps)X preliminary results Future BoNuS experiments

21. + Simulation Overview Evgen (fsgen or other event generators) RTPC(Geant4) CLAS(gsim) Gsim Post Processing (gpp)  Reconstruction  Skim Higher LevelAnalysis • What can be done using simulation? • Help to design the detector and choose the best configurations of HV and Drift gas • Debug/optimize reconstruction code of RTPC • Generate energy loss correction tables, radiation length tables • Detector’s acceptance and efficiency study

22. EventGenerator • We use FSGEN to generate D(e,ep-psp) events. • It generates scattered electron under the user-defined W and Q2 distribution. • The Fermi motion of the initial neutron is modeled using the deuteron momentum distribution obtained from the Bonn potential. • It generates the g* n p- p events uniformly in the center-of-mass frame, or according to a user-defined distribution. • It can generate other channels too, e.g. D(e, eps). • Disadvantage: no information on the cross-section is included. • Other event generator • GENEV: includes cross-section information, frequently used at Jlab.Mostly use for proton target reactions, can be used for deuteron target too after updated by K. Hafidi,.

23. RTPC Simulation • We used Magboltz to simulation the drift path of the ionized electron, then parameterized them to create the drift path package. This package will be used in digitization and reconstruction. • BONUS is a stand alone program, does not depend on CLAS Software packages at all, which is very helpful for those who want to use RTPC detector only. • BONUS can create BOS banks, which is identical to the real data from CLAS DAQ, these files can be used as input to CLAS simulation. Basing on Geant4 and ROOT packages, I have developed a program, named BONUS, to simulate to RTPC detector.

24. CLAS Simulation • Since RTPC simulation is based on Geant4 and ROOT, it is impossible to merge it into GSIM. It doesn’t worth to rewrite the RTPC simulation code in FORTRAN neither. • My solution is modifying the GSIM to take over whatever comes out from the BONUS. And also need to modify the reconstruction code (USER_ANA) to adopt this feature. • Our NEW GSIM and USER_ANA now can keep 2 sets of thrown information. One set are the at the vertex, another set are at the boundary of the RTPC detector. GSIM is the program we used to simulation CLAS detector. It is based on geant3 and CERNLIB packages.

25. Gsim Post Processing (GPP) • What is GPP? • GPP is a program taking the simulation data as input to change the timing and spatial resolution of DC and SC, and also knock out dead channels using the DC efficiency map. • Why? • In GSIM, each component of CLAS detector works in the designed way with 100% efficiency. This can never be achieved in experiment. • What are needed to run gpp? • Generate the efficiency map for each wire of DC using the real data • Scan the smear scale for SC • Scan the smear scale for DC region 1 , region 2 and region 3

26. Radlen = ∑path_length_material_i / radlength_material_i S 70 60 30 20 3 70 60 30 20 3 Radlen z -100 110 S (distance to z axis at z=110mm) Radiation Length for Trigger Electronsin RTPC

27. Energy loss correction The energy loss of final state particles in the BoNuS experiment is not negligible. Therefore I ran the simulation to obtain a tablel of energy losses for the scattered electron, pions, kaons, CLAS proton and RTPC proton. Here is the procedure: • Carefully bin the data in q,f,z • Choose a GOOD function which can be use for all particles, strong mathematic and particle physics backgrounds will save a lot of time • Predict parameters’ range and initial fitting value for each particle. This can save lot of time and effort • Run simulation to generate enough statistics in each bin • For each bin, determine a fit to the energy loss as a function of momentum

28. Acceptance correction • Binned by W(30 MeV each bin), Q2 (15 bins), cos(q*) (10 bins) and f*(15 bins) • Acceptance is the ratio of the number of events detected in a given bin to the number of simulated events in the same bin • Need to generate tables for D(e,e)X, D(e,eps)X,D(e,ep-ps)pCLASandD(e,ep-pCLAS)ps • Acceptance correction needs to be applied event by event. • Using FSGEN, I have generated and analyzed 150 M exclusive p- events for each beam energy. But statistics are still not enough due to the production rate is fairly low… • A good event generator can save lot of computer time

29. dQ/dx proton Deuteron Helium Nuclei protons RTPC Proton Identification Real data

30. Difference Between the Vertex z, q and f Measured in CLAS and the RTPC In calibration runs, the gain in the RTPC was turned up so that minimum ionizing particles (i.e. the trigger electron or a high momentum proton) would leave a signal. This enables us to compare the same tracks in CLAS and the RTPC. s(Dz) = 7.77 mm s(Dq) = 0.06 deg s(Df) = 1.08 deg

31. Missing Mass, E = 5.3 GeV, No acceptance correction yet Require e andp-be detected by CLAS. Top right: One proton was detected by CLAS; Bottom left: One proton was detected by the RTPC; Bottom right: Protons have been detected in both the RTPC and CLAS. The purple area is under the proton mass cut from 0.840 to 1.036 GeV.

32. Kinematics coverage of D(e,ep-p)p

33. Invariant Mass of p- and fast proton N(1520)D13, N(1535)S11 D(1232)P33 D(1620)S31, N(1650)S11 N(1675)D15, N(1680)D15 D(1700)D33, N(1710)P11 N(1720)P13 PRELIMINARY Baryonic resonances, D(e,ep-p)pE = 5.3 GeV, No acceptance correction yet

34. E = 4.223 GeV <Q2> = 1.19 (GeV/c)2 preliminary W (red) and W(black) (GeV) Invariant Mass of D(e, eps)n Compare the invariant mass with and without using RTPC proton information. The position of the peak is closer to the correct neutron mass value, and the width of the peak significantly decreases once the spectator proton taken into account.

35. F2n/F2p in BoNuS F2n/F2p BoNuS PRELIMINARY

36. dEdX Vs P for 3H(black), 3He(green) and 4He(blue) Simulation data The Next BoNuS Experiment E08-024, “Deeply Virtual Compton Scattering off 4He” (eg6) • Contact and spokesperson: K. Hafidi • Detector: BoNuS + Inner-Calorimeter + CLAS • This experiment is going to measured 4He(e, eg4Hes) and 4He(e, e gps), where the spectator 4Hes and ps will be measured by a newly built BoNuS detector. It is schedule to run in Oct.2009 • Good news: the RTPC DAQ hardware has be upgraded, which would increase the readout rate up to 2 kHz (our original one was just about 500Hz).

37. Jlab 12 GeV Upgrade add Hall D (and beam line) Upgrade magnets and power supplies CHL-2 Enhance equipment in existing halls

38. BoNuS @ CLAS 12 GeV

39. Summary • The BoNuS RTPC detector, together with CLAS, allows us to study the neutron resonances clearly • We have taken data for D(e,ep-p)p over a large kinematic range in q* and f*, Q2 and W • We presented preliminary results for the p-p invariant mass showing resonance structure • Acceptance corrections still need to be applied • Additional analysis underway for cross sections • More BoNuS experiments are planned

40. Thank you!

41. Meson spectrum, E = 5.3 GeV, Acceptance and momentum not corrected yet D(e,ep-prtpcpCLAS)X PRELIMINARY p0 0 r0/ w0

42. Data on the proton - nothing comparable exists for the neutron p(e,ep+)n CLAS

43. 5 µm 140 µm 50 µm 55 µm 70 µm RTPC – Gaseous Electron Multiplier 300-500 V, Gain 100-200

44. real data simulation data Gsim Post Processing (cont.) To determine SC smear value, we need to match the sigma of good trigger electron’s dt distribution of simulation data to experiment data dt = measured_time - calculated_time

45. simulation data real data Gsim Post Processing (cont.) To determine DC smear value, we need to use elastic events, match the sigma of W distribution of simulation data to experiment data real data

46. Electron Identification • rtr • Negative charge. • Number of photo electrons (Nphe) > 1.5 • E_inner > 0.06 and 0.016*P+0.15 < E_total/P < 0.34 • Pass Osipenko cut (geometry matching between SC and CC)

47. Proton and Kaon Identification I am using dt to identify particles which have heavier mass than the mass of a pion. Good protons (kaons): plot the dt distribution for proton (kaons) candidates by setting m equal to the known mass (0.938 GeV or 0.494 GeV), then fit it with a gaussian function. All candidates under the 2 sigma cut will be good proton (kaons).

48. dt/t Vs p2 for p- candidates p- Identification • p- candidates: • Negative charge. • Can not pass good electron cut • Can not pass good K- cut Define the upper limit and lower limit for dt/t, where Upper_limit = 90% * f(m=0.494 GeV) Lower_limit = 35%* f(m=0.000511 MeV). All candidates locate in between these 2 limits are good pions.

49. 4 sigma cut 4 sigma cut Quality Checks El_Ratio is the number of D(e, e´)X counts normalized to the beam charge during a 20-seconds time interval (we call this time interval as an EPICS event).

50. RTPC Resolution in Simulation (proton)