Low Z Detector Simulations

1. Low Z Detector Simulations Off-Axis Detector Workshop Stanley Wojcicki Stanford University January 24, 2003 Stanford, Ca ( Work done in collaboration with Tingjun Yang )

2. Stan Wojcicki, Low Z Detector Simulations Outline • Introductory Comments • Parameters/Issues • Few “Typical” Events • Methodology and Initial Results • Plans for the Future

3. Stan Wojcicki, Low Z Detector Simulations Experimental Challenge (visible E) 5 times below CHOOZ limit

4. Stan Wojcicki, Low Z Detector Simulations NuMI Off-axis Detector • Different detector possibilities are currently being studied • The goal is an eventual >20 kt fiducial volume detector • The possibilities are: • Low Z target with RPC’s, drift tubes or scintillator • Liquid Argon (a large version of ICARUS) • Water Cherenkov counter • One can do relatively generic simulations for the first category of detectors

5. Stan Wojcicki, Low Z Detector Simulations Detector(s) Challenge • Surface (or light overburden) • High rate of cosmic m’s • Cosmic-induced neutrons • But: • Duty cycle 0.5x10-5 • Known direction • Observed energy > 1 GeV LoDen R&D project • Principal focus: electron neutrinos identification • Good sampling (in terms of radiation/Moliere length) • Large mass: • maximize mass/radiation length • cheap

6. Stan Wojcicki, Low Z Detector Simulations A possible low Z detector The absorber medium can be cheap recycled plastic pellets The active detector in this version are RPC chambers

7. Stan Wojcicki, Low Z Detector Simulations Relative electron/muon (pion) appearance Clean track = muon (pion) Fuzzy track = electron

8. Stan Wojcicki, Low Z Detector Simulations No of hits/plane for m and e

9. Stan Wojcicki, Low Z Detector Simulations Examples of Backgrounds NC - p0 - irreducible (PH?) NC - p0 - initial gap

10. Stan Wojcicki, Low Z Detector Simulations Backgrounds (ctd) nm CC - with p0 - muon NC - p0 - 2 tracks

11. Stan Wojcicki, Low Z Detector Simulations Aims of the studies • Understand ne detection efficiency that is possible • Understand background contributions • Devise optimum algorithms • Understand detector optimization: • Strip width • Possible gain from pulse height • Benefits of 2D readout

12. Stan Wojcicki, Low Z Detector Simulations Electron Criteria • FH = Hits in road/planes hit is high (~>1.4) • FH also high on each half (~>1.15) • No gap between vertex and 1st hit on track • No gaps early in the track • Minimum track length (~>8 planes) • Not accompanied by a muon • No converted gamma “in vicinity”

13. Stan Wojcicki, Low Z Detector Simulations Muon and gamma definitions • What is a muon? • FH is low (~<1.2) • Curvature is small • Minimum track length • What is a converted gamma “in vicinity”? • FH is high (~>1.4) • Some distance from “vertex” • Gap(s) early in the track • Makes a relatively small angle wrt “primary” track

14. Stan Wojcicki, Low Z Detector Simulations Overall Event Criteria • Total energy in the event (as measured by total number of hits) within some limits • Overall asymmetry of the event wrt beam direction is low

15. Stan Wojcicki, Low Z Detector Simulations Energy Resolution • ne CC events passing all cuts • 1 < En < 3 GeV • s = 15.1 % Oscillated ne spectrum at 715 km, 9 km for Dm2 = 3 x 10-3 s = 15.9 %

16. Stan Wojcicki, Low Z Detector Simulations Initial “practice” analysis • Toy beam - gaussian distribution, centered at 2 GeV with a width of 0.4 GeV and truncated at 1 and 3 GeV • Relatively monolithic detector, mean density somewhat smaller than what is currently proposed • Early version of the analysis algorithms based on using the longest track only • Standard NuMI neutrino interaction generator is used; is it correct for the tails?

17. Stan Wojcicki, Low Z Detector Simulations Initial Results (4 cm strips) • Assumed same number of oscillated ne’s • Assumed same ratio of beam to oscillated ne’s • Figure-of-merit (FOM) defined as signal/sqrt(backround)

18. Stan Wojcicki, Low Z Detector Simulations Issue of Rates • At 9 km and 715 km, medium energy NuMI beam, 3.7 x 1020 p/yr, produce in 5 yrs, 20 kt detector, 400 oscillated ne evts (CHOOZ limit, Posc=0.05, Ue32=0.025) • For 37.5 % detection efficiency, Ue32=.0025, we get 15 events in that time • The beam ne background should be comparable or smaller than that

19. Stan Wojcicki, Low Z Detector Simulations Relative Effectiveness of Cuts (an example) 1st cuts: gaps in front, hits/50% of planes (>1.06,1.29) 2nd cuts: hits/all planes (>1.42), no of planes(>9)

20. Stan Wojcicki, Low Z Detector Simulations Track Length Distributions

21. Stan Wojcicki, Low Z Detector Simulations Plans for the Future • Make simulation more realistic: • Use NuMI offaxis beam (9 and 11 km) • Make detector geometry more realistic • Use full fledged analysis programs • Optimize reconstruction/event selection algorithms: • Roads around the tracks • Values of cuts used • Maximum likelihood or neural network

22. Stan Wojcicki, Low Z Detector Simulations Plans for the Future (ctd) • Optimize the design of the detector: • Determinestrip width tradeoffs • Determine possible gain from pulse height information • Determine loss of sensitivity from 1D readout • Understand fiducial volume issues • Understand impact of beam parameters: • Dependence on transverse distance • Possible gain from shorter decay pipe • Dependence on target position and (?) location of 2nd horn • Understand ND -> FD extrapolation (nm CC issue)

23. Stan Wojcicki, Low Z Detector Simulations Conclusions • The initial studies show that a low Z calorimeter, with fine granularity, can accomplish desired aims • The efficiency/background rejection should be competitive or maybe better than that of JHF/SuperK • The realistic quantitative studies are just beginning