1. Development of A Scintillation Simulation for Carleton EXO Project Rick Ueno Under supervision of Dr. Kevin Graham

2. Outline  Introduction  Theory  Detector Design  Monte Carlo Simulation  Empirical Position and Energy Reconstruction Algorithm  Results  Conclusion

3. Introduction  EXO: Enriched Xenon Observatory  Neutrinoless double beta decay (0 υββ ) Massive neutrino = Majorana particle? Neutrino hierarchy? Effective Majorana neutrino mass?  Enriched 136 Xe gas Both the source and detector Produces scintillation signals

4. Theory: Neutrino  Neutrino = neutrally charged lepton  Suggested by Pauli to explain continuous spectrum of beta decay  Neutrally charged third “ghost” particle carries some energy away

5. Theory: Neutrino Oscillation  If neutrinos have mass, then weak eigenstate can be written as a linear superposition of mass eigenstates  Where U li is a 3 x 3 neutrino mixing matrix. If tau neutrino is neglected for simplicity:  Transition Probability in the vacuum

6. Theory: 0 υββ decay  0 υββ decay occur only if massive neutrinos are Majorana particles  Effective Majorana mass  Measured quantity is half- life of 0 υββ decay

7.  SNO and Super-K measures Δm 2, but hierarchy is still unknown Theory: Neutrino Mass

8. Theory: Xenon Gas  Acts as both the source (produces electrons by the decay process) and a detector (produces scintillation light)  Scintillation process Incoming particle loses energy to form dimers The de-excitation of dimer emits photons at wavelength centred around 178nm http://hepwww.rl.ac.uk/ukdmc/iop 98njts/index.htm

9. Detector Design  A simple scintillation counter was designed to study the scintillation process alone  Motivation: Predicting total light yield of gaseous xenon Reconstruction of position and energy for a better energy resolution when coupled with the existing TPC (Time Projection Chamber) component Study of how response varies with different gas mixtures (such as addition of quenching gases)

10. Detector Design: Overall Design  Consists of a stainless steel “T”, two PMTs on either side, wavelength shifter (WLS) on the PMT window

11. Detector Design: PMT  136 Xe produces UV photon of 178nm  Possibility: Regular PMT with WLS or UV-sensitive PMT  We already have equipment to coat materials with WLS (Tetraphenyl Butadiene, TPB)

12. MC Simulation: Detector Construction  MC Simulation using Geant4 was developed  The detector design is simplified to a cylindrical geometry  PMT is represented by a cylindrical tube with a photo- cathode at the end of a glass plate y x z 12”

13. MC Simulation: Default Initial Values PropertyValues Photon energy7.07 eV ( ≈ 178nm) Scintillation yield29000 photons / MeV Absorption length100 cm Prompt scintillation timing constant 2.2 ns Late scintillation timing constant 4.5 ns Initial ParticleAlpha particle Initial MomentumRandom direction

14. MC Simulation: Event Detection and Outputs  PMT and WLS has some wavelength- dependent efficiency The simulation should be as realistic as possible The program reads an input data file containing efficiency data corresponding to a wavelength  Result is outputted into a data file to be analysed

15. Empirical Position and Energy Reconstruction Algorithm  Reconstruction of initial position and energy Input: Signal output of two PMTs Output: Reconstructed position and energy of the particle Reconstruction Program PMT1 Hits, PMT2 Hits Reconstructed Position and Energy

16. Empirical Algorithm: Position Reconstruction  Looking at the distribution of ratio between PMT1 and total signal as a function of z position  Gives a smooth curve  Can be readily used to reconstruct the initial position in z direction

17. Empirical Algorithm: Energy Reconstruction  Looking at the total signal normalized by the signal at z = 0 as a function of z position  Can approximate to a 4 th order polynomial  Used to estimate the hits if the event occurred at the centre of the detector

18. Empirical Algorithm: Energy Reconstruction  Looking at the total signal at the centre as a function of energy  Gives a linear relation  But a0=0  Rearranging the equation, initial energy is reconstructed

19. Empirical Algorithm: Radial dependency  The detected signal as a function of position across the diameter of detector shows deficiency up to ~40% near the wall of the detector

20. Empirical Algorithm: Radial dependency  Predict that the z-position reconstruction has smaller effect than energy reconstruction

21. Results of independent test simulations Three test scenarios were simulated with alpha particles with initial energy of 5.4 MeV at various positions

22. Results: Test Scenario 1  Starting position at (0,0,0) cm  Both reconstructed position and energy agrees nicely

23. Results: Test Scenario 2  Starting position at (0,0,-10) cm  Both reconstructed position and energy are fairly consistent

24. Results: Test Scenario 3  Starting position at (5,0,5) cm  Reconstructed energy is much lower than expected

25. Results: Summary Test Scenario123 Reconstructed Position (cm) -0.02354-10.354.571 Sigma0.36190.29470.3687 Reconstructed Energy (MeV) 5.415.0654.284 Sigma0.2140.28250.2134

26. Conclusion  Baseline simulation was developed using Geant4  The reconstruction algorithm was developed Works well if the event occurs at the centre Problem when the initial event is off-centre  Future plans Xenon gas and additives Implement into existing TPC system