1. Investigating Asymmetries in the D(e,e’p)n Reaction Kuri Gill January 10, 2008

2. Goals 1.To study transition from the hadronic model to the quark-gluon model. 2.Study the Nucleon-Nucleon force using the electro-disintegration of the deuteron. 3.Look at σ TT which is one of the cross section components. 4.Simulate false asymmetries to untangle physics effects from artifacts of the apparatus.

3. Outline Introduction to Nuclear Physics The Cross Section and Asymmetries JLab and CLAS Simulations and False Asymmetries

4. Standard Model Force Carriers- Each are Bosons so they have Integer spin, do not obey Pauli Exclusion Principle. Interact with matter constituents to create matter. Matter Constituents- We know of 6 Leptons and 6 Quarks. Each are Fermions so they have spin ½ and obey Pauli Exclusion Principle. Baryons consist of 3 quarks. Mesons consist of a quark and an anti-quark. Graviton?

5. Quantum Chromodynamics (QCD) Theory of the Force that binds quarks together. Color charge has not relation to visual color, but is a good way to explain the property that there are three kinds of color charge. All known particles are color singlets (no net color force). Quarks are only found in groups of either two or three. A particle can be created with three primary “colors” or a “color” and an “anti-color”. Nobel Prize in 2004 (D. Cross, D. Politzer, F.Wilczek).

6. Quantum Chromodynamics (QCD) Two strange properties very different from the Coulomb force. As the distance increases between particles, the force pulling them together does not decrease. This is called Confinement. At very close distances, the force between quarks goes to zero. This is called Asymptotic Freedom. This graph is a calculation.

7. The purpose of my research is to measure the components of the Deuteron wave function. Why? With one proton and one neutron, the deuteron is the simplest nucleus. It is a laboratory to study the proton-neutron force, which is a residual effect of the color force between quarks. What is my motivation?

8. Cross sections Differential cross section –Connects theoretical and experimental physics. –Minimizes systematic uncertainties and differences (beam line, detector, etc.) –probability to observe a scattered particle per solid angle unit if the target is irradiated by a flux of one particle per surface unit: Scattered Particle Incident Rate

9. Cross sections The cross section for the D(e,e’p)n reaction is: Each term represents the cross sectional area in the Longitudinal (L), Transverse (T) directions or their cross terms. We are looking for σ TT, we create an Asymmetry A TT which is less vulnerable to the systematic uncertainties. We measure the out-of-plane components of the nuclear cross section which have never been determined in this energy region. Essential Angles φ pq, the angle between the scattering plane and the reaction plane θ pq, the angle between the ejected proton and the 3-momentum transfer. P m the missing momentum:

10. We know that the Cross Section for the Deuteron is: Consider: Because of the orthogonality of the functions when n≠m: and When m=2: Now we define an Asymmetry: And when m=0: We use a ratio because the acceptance and efficiencies of the detector are cancelled out.

11. Jefferson Lab Newport News, VA Where can we get particles like this?

12. CEBAF It consists of a 7/8 th of a mile racetrack shaped track 25 feet underground. It can currently produce beams with energy up to 6 GeV. An electron beam can be accelerated around up to 5 times. At the end there are 3 halls where the beam will collide with targets and scatter particles through different detectors. Continuous Electron Beam Accelerating Facility

13. CLAS 45 ton, $50 million radiation detector located in Hall B. used to detect electrons, protons, pions and other subatomic particles. Nearly a 4π detector. It can detect most particles created in a nuclear reaction. 33,000 detecting elements. Information is stored on tape. Layers provide information about charge, momentum, velocity, and energy, allowing us to identify the particles. CEBAF Large Acceptance Spectrometer

15. Drift Chambers –The innermost three regions. They help determine the trajectory particles. –Consist of 32,000 sense wires. –The scattered particles pass through a gas and leave a trail of ions. –The electrons drift to sense wires creating a burst of current. Toroidal Shaped Magnent Causes charged particles to curve as they pass through drift chambers. The magnetic field is create by six superconducting coils. Particles with higher momentums bend less.

16. Cerenkov Counters –Cerenkov light is produced when a particle moving close to the speed of light in air passes into a region where the speed of light is much slower. (The particle is moving faster than the speed of light in this medium). –Particles slow down and dump energy in the form of light. –At JLab, this distinguishes electrons from much heavier particles such as pions which are slower.

17. Time of Flight (TOF) Plastic Scintillators –Provides a very accurate time. –We can use the TOF to determine the velocity since we know the path length from the trajectory. –Using momentum and velocity, we can find the mass of the particle. –Also they help determine which beam micropulse is being viewed This gives us a start time for the TOF measurement. –Each end of the scintillators (3000 total) contains a photo- multiplier tube which is highly sensitive light detector (can detect a single photon).

18. Calorimeter –Many alternating layers of lead and scintillating plastic Used as an energy measurement Collisions in lead create a particle shower Particles from the shower produce lights in scintillators Thick enough to stop all charged particles

19. CLAS Simulations CLAS is a complex detector and we use simulations to understand it’s response We need to separate real physics effects from artifacts of the CLAS response I used a software package from CERN called GSIM to simulate events GSIM uses a Monte Carlo simulation process. The simulated events were then analyzed and compared to the actual data

20. SpiderWulf and Supercomputing What is Perl? –programming language that is useful in tying together systems, programs, and interfaces –also useful in managing large amounts of data Richmond Supercomputing Lab How do we use it? –use it to execute a sequence of commands to run a number of programs, manage files, etc. Where? –UR’s 34-node supercomputer (Spiderwulf) We need a lot of computing power because of the large data sets that JLAB produces and because we need to simulate a large number of events

21. Perl Scripts submit_sim.pl is used to initiate the job and keep track of which of the nodes on the computing cluster are working. It initiates run_queegsim_on_node.pl run_queegsim_on_node.pl runs the following programs and manages the files. QUEEG of the Quasi-Elastic Electron Generator generates electron events by creating 4-vectors. These are the events stored in the PART bank. GSIM simulates the CLAS response to the vectors created in QUEEQ, the results of which are stored in the EVNT bank. Gppjlab then removes the dead CLAS components (drift chamber wires, TOF scintillators etc.). RECSIS reconstructs the events from the event data and produces the 4-momentum and identity of each particle. This is the same program used to reconstruct tracks when analyzing the real data. eod5root is the code used to create final histograms, process the 4- momentum vectors and is where we create the graphs of the asymmetries.

22. Asymmetry found in the real data To investigate false asymmetries, data is simulated without true asymmetries. We do this by observing the vertex shifts in the real data, inserting vertex shifts into the simulations and extracting A TT from the simulations. Asymmetries seen in the real data, We are trying to figure out what part of this asymmetry is caused by the detector. Picture here

23. Simulating Vertex Shifts CLAS is a very large machine separated into six sectors. It is not perfectly aligned, and because of this we measure small vertex shifts in the y direction after reconstructing the particles trajectory. We want to mimic these shifts in our simulations. For each sector we measure the vertex shifts in the y direction in the data.

24. Vertex Shifts We insert the shifts into the simulations to mimic the data. The shifts were determined by the centroid of a Gaussian curve. The shifts were then inserted after the GSIM simulation. Notice how similar the simulated curves are to the curves from the real data. Real Data Simulated Peaks

25. False Asymmetry This simulation is then used with the vertex shifts to determine if there is a false asymmetry. When we shift the data in the simulations, we get a measurable asymmetry as shown below: Picture here

26. Sensitivity Uncertainties of this asymmetry are small, but are statistical from Monte Carlo Simulation. The next step was to account for the uncertainty in the vertex shifts. We used a shift of.01 cm which is roughly 1.5 times the accepted uncertainties for these peak. We shifted each vertex.01 cm above and below the mean vertex shift, and ran the simulation to find the asymmetry sensitivity.

27. Weighted Average The asymmetry is significant, non-zero, and does not change significantly when v y is modified. Because of this, we can determine that there is a false asymmetry. The weighted average for each bin was calculated. The formula for the weighted average and weighted uncertainty are below.

28. Final False Asymmetry The false asymmetry weighted average is shown here.

29. Data without the False Asymmetry Since the asymmetry is significant, we should subtract it from the original data which gives us the graph below

30. Limitations The vertex shifts were inserted after GSIM was run. To better improve our results the vertex shifts should be inserted before GSIM which is a much more complex programming task. We can only attest for asymmetries in the first few data points because in later points the uncertainty is too high. We should run longer simulations to reduce the uncertainties at high missing momentum. We should also run this experiment at other beam energies in this data set.

31. Conclusions GOAL: to measure and determine the asymmetries for the σ TT component of the D(e, e’p)n reaction. The cross section helps us determine this component and links experimental physics with theoretical physics. We create an Asymmetry A TT to cancel out uncertainties and to create a more precise result. We used a program called GSIM to simulated the detector CLAS. We inserted the vertex shifts in the real data to see if they caused any False Asymmetries.

32. Conclusions After concluding that they did show false asymmetries, we found the sensitivity of this measurement with regards to the vertex shifts. The results show that even with significant changes in the vertex shifts (about 1.5 times the accepted uncertainty) the asymmetry is well-behaved. This concludes that there is a false asymmetry which can be calculated and subtracted from the real data.

33. References 1 M. Barnett, A Erzberger, et al. The Particle Adventure; the fundamentals of matter and force, WWW Document, (http://paticleadventure.org) 01/09/2008. 2 Contemporary Physics Education Project, Nuclear Science Poster, WWW Document, (http://cpepweb.org/) 01/09/2008. 3 The Nobel Foundation, The Nobel Prize in Physics 2004, WWW Document (http://nobelprize.org/nobel_prizes/physics/laureates/2004/) 01/09/2008. 4 Columbia Enclyclopedia, Quantum Chromodynamics, WWW Document, (http://www.encyclopedia.com/doc/1E1-quantumch.html) 01/09/2008. 5 T.P. Smith, Hidden Worlds (Princeton University Press, 2003). 6 Opportunities in Nuclear Science, The DOE/NSF Nuclear Science Advisory Committee, April 2002. 7 Thomas Jefferson National Accelerator Facility, Jefferson Lab; Exploring the Nature of Matter, (http://www.jlab.org) 01/09/2008 8 B. Mecking, et al., The CEBAF Large Acceptance Spectrometer, Nucl, Inst. And Math. A, 524 (2004) 306. 9 V. Barger, M. Olssen, Classical Mechanics: A Modern Perspective (McGraw-Hill Inc, 1995). 10 R. Burrell, K. Gill, G.P. Gilfoyle, `CLAS Simulations for D(e,e’p)n, University of Richmond, Bull. Am. Phys. Soc., Fall DNP Meeting, BAPS 3A.00012 (2006).for D(e,e’p)n, University of Richmond, Bull. Am. Phys. Soc., Fall DNP Meeting, BAPS 3A.00012 (2006).

34. Special Thanks to: Dr. Gilfoyle Rusty Burrell Kristen Greenholt Everyone for coming!