1. CEBAF The Continuous Electron Beam Accelerating Facility(CEBAF) is the central particle accelerator at JLab. CEBAF is capable of producing electron beams up to 6 GeV. The accelerator is about 7/8 of a mile around and is 25 feet underground. The electron beam is accelerated through the straight sections and magnets are used to make the beam travel around the bends(See Fig. 1). An electron beam can travel around the accelerator up to five times near the speed of light. The beam is sent to one of three halls where it collides with a target and causes particles to scatter into the detectors. CLAS Simulations for the E5 Data Set R.Burrell, K.Gill, G.P.Gilfoyle University of Richmond, Physics Department Introduction The Thomas Jefferson National Accelerator Facility (JLab) in Newport News, Virginia, is used to understand the fundamental properties of matter in terms of quarks and gluons. We describe here how we simulate the performance of one of the detectors to better understand its response. Hall B Fig. 1 JLab Accelerator and Halls A, B, and C CLAS The CEBAF Large Acceptance Spectrometer(CLAS), located in Hall B, is used to detect electrons, protons, pions and other subatomic particles. CLAS is able to detect most particles created in a nuclear reaction, because it covers a large solid angle. The particles go through each region of CLAS leaving behind information that is collected and stored on tape. The event rate is high (about 3000 Hz), so the initial data analysis is done at JLab, and we analyze more deeply those results at the University of Richmond. There are six different layers of CLAS that produce electrical signals and provide information on velocity, mass, and energy, allowing us to identify and separate different subatomic particles. The drift chambers make up the first three layers, which measures the path of different particles. The paths of the particles are bent in a large, toroidal magnet to measure momentum. The data here were collected during the E5 running period at beam energies 2.6 GeV and 4.2 GeV on deuterium and hydrogen. Physics Motivation The CLAS detector is a large (10-m diameter, 45-ton) spectrometer designed to measure and identify the debris from a nuclear collision. The first three layers of CLAS, the drift chambers, consist of high-voltage wires that send signals when a charged particle scatters near them to capture a ‘snapshot’ of the particle’s trajectory. Wire misalignments and sag can effect the quality of our data. To understand the response of CLAS, we simulate its performance with a software package called GSIM. We can see how much of what we observe is from real physics or artifacts of the detector. We can then correct for these artifacts. Perl Scripts and Simulating CLAS In order to separate real physics results from artifacts of the detector we simulate the performance of CLAS. A Perl script executes a sequence of commands to run different programs, manage files, etc. The scripts are executed on the 34-node supercomputing cluster in the University of Richmond nuclear physics laboratory. An outline of this script is below. 1.QUEEG- (Quasi-Elastic Electron Generator) creates electron 4- vectors (events). 2.txt2part – converts QUEEG output to BOS files (part bank 4- vectors). 3.GSIM – CLAS simulation program (main program). 4.gppjlab – removes dead components. 5.RECSIS – event reconstruction program (reconstructs tracks). 6. nt10maker – convert EVNT and PART BOS banks to hbook ntuples (software package for physics analysis) 7. h2root – convert hbook ntuples to root ntuples 8. eod5root – local code for final analysis to extract histograms, asymmetries, etc. Simulation Analysis Asymmetries In a D(e,e’p)n reaction, we look to measure the out-of-plane components of the nuclear cross section which have never been determined in this energy region. An essential observable is  pq, the angle between the scattering plane and the reaction plane (see Figure 3). The differential cross section is given by: (1) where h is the beam helicity (±1). To extract the different  - dependent terms in the cross section we take advantage of the orthogonality of sines and cosines. For example, to extract  LT consider the following. (2) The asymmetry A LT is proportional to  LT and less sensitive to acceptance corrections and other experimental effects because we are using a ratio. We examine this asymmetry A LT and another one A TT which is proportional to the  TT term in the cross section. Equation 3 shows the expressions we use to determine the asymmetries in a kinematic bin where N is the total number of events. (3) Track Vertex Shifts Misalignments of the components of CLAS can create false asymmetries in our data. To investigate this issue, we simulate our data without true asymmetries (A LT =A TT =0), but include small shifts in the positions of the CLAS components. The geometry of the track vertex is shown in the figure below. We measure the vertex shifts from the beam line along the z-axis from real data and obtain the results shown below. We are able to see how far from the beam axis each sector is located. We then insert these shifts into our simulation. Data Banks In the simulation and analysis process, two event banks are used: the “PART” bank contains the thrown events generated with QUEEG before they are passed through the CLAS simulation package GSIM (see above). This lets us know exactly what goes into the detector. A second “EVNT” bank contains events that were processed in the CLAS simulation and represent what actually made it through the detector and our analysis codes. Fig.4. Track vertex geometry Fig. 2. The CLAS detector at Jefferson Lab. Fig 3. Kinematic quantities. Conclusions We have developed scripts to control and execute the CLAS simulation package GSIM on the Richmond supercomputing cluster. We have found small shifts in the electron track vertex position observed in our data can create false asymmetries in the simulation. We are studying how to correct for these shifts. Figure 5. Plots of the y-component of the electron track vertex position for each CLAS sector taken from real data and fitted with a gaussian curve. The effect of the vertex shifts in the simulation is shown in Figure 6. The shifts create a significant false asymmetry that will have to be corrected in the final analysis. If the vertex shifts are removed the false asymmetries disappear. Figure 6. False A LT and A TT asymmetries created by vertex shifts in the simulation.