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14 July 2004University of Hawaii Physics Seminar New Nu’s from the DONUT Experiment Emily Maher University of Minnesota.

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Presentation on theme: "14 July 2004University of Hawaii Physics Seminar New Nu’s from the DONUT Experiment Emily Maher University of Minnesota."— Presentation transcript:

1 14 July 2004University of Hawaii Physics Seminar New Nu’s from the DONUT Experiment Emily Maher University of Minnesota

2 University of Hawaii Physics Seminar 14 July 2004 DONUT Collaboration Aichi Univ. of Education K. Kodama, N. Ushida Kobe University S. Aoki, T. Hara Nagoya University N. Hashizume, K. Hoshino, H. Iinuma, K. Ito, M. Kobayashi, M. Miyanishi, M. Komatsu, M. Nakamura, K. Nakajima, T. Nakano, K. Niwa, N. Nonaka, K. Okada, T. Yamamori, Takahashi Univ. of California/Davis P. Yager Fermilab B.Baller, D.Boehnlein, W.Freeman, B.Lundberg, J.Morfin, R. Rameika Kansas State Univ. P. Berghaus, M. Kubanstev, N.W. Reay, R. Sidwell, N. Stanton, S. Yoshida Univ. of Minnesota D. Ciampa, C. Erickson, K. Heller, R. Rusack, R. Schwienhorst, J. Sielaff, J. Trammell, J. Wilcox Univ. of Pittsburgh T. Akdogan, V. Paolone Univ. of South Carolina A. Kulik, C. Rosenfeld Tufts University T. Kafka, W. Oliver, J. Schneps, T. Patzak Univ. of Athens C. Andreopoulos, G. Tzanakos, N. Saoulidou Gyeongsang University J.S. Song, I.G. Park, S.H. Chung Kon-kuk University J.T. Rhee E. Maher

3 University of Hawaii Physics Seminar 14 July 2004 Outline Goals/Motivation/Status Experimental Setup Data Analysis Results (Nu Tau Events & Charm Events) Individual Event Probabilities Cross Section Measurement Conclusion

4 University of Hawaii Physics Seminar 14 July 2004 Goals/Motivation/Status Goals  Directly observe the charged-current interaction of the tau neutrino – previously attempted but never successfully  Answer the question: is the tau neutrino is a standard model particle? Motivation  Check standard model  Neutrino oscillation Status  Have observed tau neutrino interaction (Phys. Lett. B 504, 218 (2001))  Upper limit on tau neutrino magnetic moment (Phys. Lett. B 513, 23 (2001))  Paper on technical details of emulsion target (NIM A 493, 41 (2002))  Paper on technical details of spectrometer (NIM A 516, 21 (2003))  Currently working toward cross section measurement for tau neutrino – is tau neutrino is a standard model particle

5 University of Hawaii Physics Seminar 14 July 2004 directly observe cc interactions of the    + N  + X SPECTROMETER DsDs 800GeV    BEAM DUMP SHIELDING EMULSION TARGET ~ 3.5 x 10 17 protons for ~1000 interactions ~ Expected 5%  p Experimental Setup – Block Diagram

6 University of Hawaii Physics Seminar 14 July 2004 Shielding- Purify the Neutrino Beam Primary Target Emulsion Target 36m Spectrometer Shielding to protect emulsion from the high flux of muons. Sweeping Magnets Max. int. charged particle flux ~ 10 5 /cm 2 ~ 10 7 / spill @ 10 cm from emulsion edge ~ 10 12 / spill @ 2 m

7 University of Hawaii Physics Seminar 14 July 2004 Spectrometer Muon ID Calorimeter Drift Chambers Magnet ( =225MeV) 5.5m 3.25m Trigger Vertex Location Momentum Analysis Electron ID Muon ID Veto Wall Emulsion Scintillating Fiber Target

8 University of Hawaii Physics Seminar 14 July 2004 Emulsion Target Stand 500  Scintillating Fibers Image Intensifier - CCD Readout. Lead Shield 260 kg total mass

9 University of Hawaii Physics Seminar 14 July 2004 Emulsion Target Designs AgBr suspended in a gel (Fuji ET7C ) coated on plastic sheets. 29±2 grains per 100  m for minimum ionizing track 95% emulsion 5% emulsion Resolution Spatial Resolution:.3  m Emulsion modules consist stacks of sheets made of emulsion, acrylic, and steel. Three configurations were used. BULK Sampling 800 Sampling 200 0.32 mm 0.08 mm 1.0 mm 0.10 mm 0.80 mm 1.0 mm 0.10 mm 0.20 mm Stainless Steel Emulsion Acrylic

10 University of Hawaii Physics Seminar 14 July 2004 Predict interaction point in emulsion from spectrometer tracks (software + humans) Define a volume in emulsion around predicted interaction point. Digitize all track segments in emulsion volume (hardware processor at Nagoya University) Search digitized emulsion data for interaction (software pattern recognition) Use spectrometer and emulsion to characterize event (, ) Use emulsion data to locate kinks, tridents (software pattern recognition) 8 hrs/event Overview of Analysis All in mm NETSCAN

11 University of Hawaii Physics Seminar 14 July 2004 Locating Vertices in Emulsion Data Segment detection efficiency >98%

12 University of Hawaii Physics Seminar 14 July 2004 Event must have: No e,  from primary vertex Decay with one or three charged products 85% of decays are single charge  Criteria  Finding  Interactions  Tau parent must have: Short decay length length < 10 mm (mean 2.5 mm) At least one segment on parent 76% tau’s have visible track Small production angle angle < 200 mr (mean 40 mr) Single prong events must have: Minimum pt - pt > 250 MeV/c  W X N  0.8 mm acrylic 100 microns emulsion Single Prong

13 University of Hawaii Physics Seminar 14 July 2004 Components for Finding  Interactions Lepton ID  Muon ID –  must have 4 out of 6 hits in  -ID system in spectrometer  Electron ID – combination of three techniques Identify for electron pairs in emulsion Identify electromagnetic showers in scintillating fibers Identify electrons using EMCAL Momentum Measurement  Use spectrometer (analysis magnet and drift chambers)  Use multiple scattering in emulsion data to measure momentum

14 University of Hawaii Physics Seminar 14 July 2004 W X N  Spectrometer Fiber trackerEmulsion Results   Charged Current Interaction

15 University of Hawaii Physics Seminar 14 July 2004 From spectrometer From emulsion Emulsion tracks to spectrometer Results  Charged Current Interaction

16 University of Hawaii Physics Seminar 14 July 2004 Data Analysis Status 1026 predicted vertices from spectrometer 867 within fiducial volume 655 digitized emulsion data exists 433 vertex found 433 systematic decay search 6.6  10 6 triggers 655 emulsion vertex location attempted 6  candidates charm candidates 7 66 % Location efficiency 417  events

17 University of Hawaii Physics Seminar 14 July 2004 Typical Event – No Emulsion Data U View V View

18 University of Hawaii Physics Seminar 14 July 2004 Atypical Event – Emulsion Data, Not Located

19 University of Hawaii Physics Seminar 14 July 2004 Phase 1  Candidates

20 University of Hawaii Physics Seminar 14 July 2004 Phase 2  Candidates

21 University of Hawaii Physics Seminar 14 July 2004 Results Charm Candidates

22 University of Hawaii Physics Seminar 14 July 2004 How Many Events Do We Expect?  How many  events do we expect? (calculated using MC)  Expect 14.6 tau neutrino charged current interactions  85% will be single prong - expect 12.4 single prong events  15% will be tridents events – expect 2.2 trident events  Probability of passing the selection cuts is 0.52 for single prong  Expect 6.4 events  Observe 4 events  Probability of passing selection cuts is 0.90 for trident events  Expect 2 events  Observe 2 events  How many background events do we expect? (calculated using MC)  Expect 0.8 single prong events  Expect 2 trident events

23 University of Hawaii Physics Seminar 14 July 2004 What is the Probability all Events are Background? A signal of 4 single prong events with an expected background of 0.8 events A signal of 2 trident events with an expected background of 2.0 events 1. The Poisson probability of all signal events being background Single Prong EventsTrident Events 2.The above method is based on applying cuts to the data set. If we could use a different analysis which uses the events’ topologies, the analysis would contain more information, so it would be more accurate. This analysis will give a relative probability of each candidate being a tau neutrino event, which can be used to calculate a probability that all of the events are background. Since each event is independent, the probability that all events are background is calculated using the following equation: Two Methods: Individual Event Analysis and Neural Net Analysis

24 University of Hawaii Physics Seminar 14 July 2004 Parameters Track production angle  Event angular symmetry  Track decay length L Daughter momentum Daughter decay angle Sum of daughter IP = Lsin Use 4-parameter or 5-parameter analysis to assign probabilities to event interpretation. ptpt  View perpendicular to direction hadrons e   L   Vector sum of all hadrons p  e  IP 

25 University of Hawaii Physics Seminar 14 July 2004 P = The probability of a set of parameters, x, being a result of event i, where. Two inputs for each event type: 1.A i prior probability: Knowledge of the likelihood of each event i Relative Normalization (aka N signal, N charm bkg, N int. bkg ), 2.PDF i (x): probability density function Probability of finding event in (x, x+  x) where x is a 4- (for trident events) or 5- (for single prong events) tuple of parameters specific to the individual event Individual Event Analysis - Bayesian Analysis

26 University of Hawaii Physics Seminar 14 July 2004 Individual Event Probability 1-D example:  vs hadron interaction 1.Assume the only possibilities are  or hadron interaction. 2. Use only one parameter  to evaluate event. 3333_17665 has  = 2.8 rad Expect 0.22 interaction evts. A int = 0.22 Expect 6.4  events A  = 6.4 PDF(int. |  = 2.8) = 0.23 PDF(  |  = 2.8) = 0.81 0  measured   VV

27 University of Hawaii Physics Seminar 14 July 2004   Single Prong Event Parameters Track production angle Event angular symmetry Track decay length Daughter decay angle Daughter momentum Tau Candidate Individual Event Probabilities Probability all events are background = 7.6 x 10^-8 + 3333_17665 3039_01910 3263_25102 .70.98.16.99 charm.30.02.14.01 hadron scatter 00.70 0 + cc 3024_30175 Single Prong 3334_199203296_18816.99.85.01.15 00 Tridents Trident Event Parameters Track production angle Event angular symmetry Track decay length Sum of daughter IP’s

28 University of Hawaii Physics Seminar 14 July 2004 3263_25102 (Scatter) & 3333_17665 (Tau)

29 University of Hawaii Physics Seminar 14 July 2004 Single Prong Event Parameters Track production angle Event angular symmetry Track decay length Daughter decay angle Daughter momentum Charm Candidate Individual Event Prob. Trident Event Parameters Track production angle Event angular symmetry Track decay length Sum of daughter IP’s 3065_03238 3193_01361  0 0 0 charm.99.94.98  hadron scatter.01.06.02   + cc + Single Prong 3245_22786 0 1.0 0 Trident 2986_00355 7 Charm Candidates: 3 Single Prong 1 Trident 3 Neutral Vees

30 University of Hawaii Physics Seminar 14 July 2004 Cross Section Measurement  Check to see if the number of tau neutrino charged current interactions DONUT observed agrees with theory – check lepton universality  Cross section can be calculated in different ways oAbsolute cross section - first principles oRelative cross section – normalize against number of muon neutrino and electron neutrinos  For second approach, the following quantities are necessary: oMust define specific cuts to create data set (neutrino and tau neutrino data sets) oMust know efficiencies (trigger, selection, location, identification) oMust know the number of electron and muon neutrino charged current interactions Electrons – emulsion data, electron ID in spectrometer Muons – muon ID in spectrometer

31 University of Hawaii Physics Seminar 14 July 2004 Conclusion Sampling emulsion + spectrometer works even better than expected  Still learning to use all of its power Near 100% reconstruction efficiency possible (66% now)  (<50% was previously “excellent” ie CHORUS) Particle id, Momentum measurement, Single event probabilities Increasing event sample continues  From 203 to 417 Better understanding of efficiencies and more tau and charm events  Improved understanding of backgrounds and systematics  Cross section measurements Technology for future detectors to study short lived particles.  OPERA

32 University of Hawaii Physics Seminar 14 July 2004 More Charm Candidates

33 University of Hawaii Physics Seminar 14 July 2004 More Charm Candidates

34 University of Hawaii Physics Seminar 14 July 2004 Single Prong Event Parameters Track production angle Event angular symmetry Track decay length Daughter decay angle Daughter momentum Comparison of Individual Event and Neural Net Analysis 3333_17665 3039_01910 3263_25102 .70.98.16.99 cc 3024_30175 Individual Event 3333_17665 3039_01910 3263_25102.971.0.141.0 3024_30175 Neural Net Analysis

35 University of Hawaii Physics Seminar 14 July 2004 Individual Event Probabilities How Many Events Do We Expect? For the 433 neutrino interactions we calculate how many tau neutrino charged current events we expect to observe using: where Rate is the calculated rate of a type i event, and is the total efficiency of a type i event, where. Rate (per kg proton)Expected Number 0.5992 0.57104 0.34108 0.5196 0.5714.6

36 University of Hawaii Physics Seminar 14 July 2004 Individual Event Probabilities Prior Probability Calculation To calculate the prior probability, must know 1.Expected number of neutrino interactions in detector 2.Probability of the process resulting in a kinked track (trident) 3.Trigger, selection, and location efficiencies 4.Probability that the event passes the tau selection criteria Example: Calculating the prior probability of event 3333_17665 (single prong decay to electron) Num.exp. interactions: BR to single prong: Selection probability: Prior Probability: TauDDsDs Charm 14.65.21.92.16 0.850.460.370.65 0.520.130.140.09 6.40.30.1 0.54

37 University of Hawaii Physics Seminar 14 July 2004 Individual Event Probabilities Probability Density Function Calculation Calculating multi-dimensional probability density for a candidate event 1.Each event has measured values of parameters  ( ,  p,L) or ( ,  p,L,  k,P) 2.Define a (small) interval in parameter space around measured values:  v 3.Simulate hypothesis event type: count number of events which pass all tau selection cuts (N total ) count number of events which are within the interval  v (N  v ) Tridents Single Prong     p   p L   L L   Lprobability density for event   k   k  v P   P   v


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