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

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

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

NuMI Off-axis Detector 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

Detector(s) Challenge 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

A possible low Z detector 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

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

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

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

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

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

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”

Muon and gamma definitions 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

Overall Event Criteria 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

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 %

Initial “practice” analysis 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?

Initial Results (4 cm strips) 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) Neutrino beam Signal ne CC Beam ne NC nm CC (ND) Effic FOM JHF OAB 20 123 11 9.3 1.8 40.7 % 26.2 2 +- 0.4 GeV 112 10 3.1 15.4 37.1 % 29.0

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

Relative Effectiveness of Cuts (an example) Stan Wojcicki, Low Z Detector Simulations Relative Effectiveness of Cuts (an example) ne CC nm CC NC All 151.5 436.8 917.5 After 1st cuts 86.6 7.2 28.3 After 2nd cuts 59.0 1.01 2.0 1st cuts: gaps in front, hits/50% of planes (>1.06,1.29) 2nd cuts: hits/all planes (>1.42), no of planes(>9)

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

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

Plans for the Future (ctd) Stan Wojcicki, Low Z Detector Simulations Plans for the Future (ctd) Optimize the design of the detector: Determine strip 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)

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