Measurement of Muon Momentum Using Multiple Coulomb Scattering for the MicroBooNE Experiment

Transcription

1 Measurement of Muon Momentum Using Multiple Coulomb Scattering for the MicroBooNE Experiment Polina Abratenko August 5,

2 Outline What is MicroBooNE? How does the TPC work? Why liquid argon? What is the goal of MicroBooNE? What is MCS? How do we implement MCS? How does it perform on simulation? How do we quantify performance? What are the limitations of our implementation of MCS? How does MCS perform on real data? What do we compare the MCS energy to? How do we select events? What can we conclude? 2

3 What is MicroBooNE? 3

4 MicroBooNE Micro Booster Neutrino Experiment Part of the Short-Baseline Neutrino (SBN) physics program at Fermilab Liquid argon time projection chamber (LArTPC) 4

5 Located 470 m from BNB target Current largest LArTPC in the U.S. 170 tons of LAr in cryostat, 86 tons active in TPC TPC dimensions: 2.3 m 2.6 m 10.4 m 5

6 How does the TPC work? 6

7 MicroBooNE Detector - Time Projection Chamber Charged particle moves through fiducial volume, loses energy Causes ionization and excitation of argon Electrons drift to anode, Ar+ to cathode Moving electrons induce current on wires (anode wire planes) Particle tracks reconstructed from these wire signals 7

8 Why liquid argon? 8

9 Liquid Argon There are many reasons, but some are: Is a noble element (closed shell; electrons need to drift from ionization to sensor wires in detector) High number of nucleons Greater rate of interactions with particles inside the medium Ionizes easily Produces scintillation light, which is not reabsorbed High electron lifetime Inexpensive ( $2/L) 9

10 What is the goal of MicroBooNE? 10

11 MicroBooNE Goal - Observing Neutrino Oscillations MicroBooNE has a few goals: investigating the excess low energy events observed by the MiniBooNE experiment, studying neutrino-argon cross-sections, LArTPC R&D... 11

12 MicroBooNE Goal - Observing Neutrino Oscillations MicroBooNE has a few goals: investigating the excess low energy events observed by the MiniBooNE experiment, studying neutrino-argon cross-sections, LArTPC R&D... 12

13 MicroBooNE Goal - Observing Neutrino Oscillations MicroBooNE has a few goals: investigating the excess low energy events observed by the MiniBooNE experiment, studying neutrino-argon cross-sections, LArTPC R&D... 13

14 MicroBooNE Goal - Observing Neutrino Oscillations MicroBooNE has a few goals: investigating the excess low energy events observed by the MiniBooNE experiment, studying neutrino-argon cross-sections, LArTPC R&D... One aim is to explore neutrino oscillations Neutrino oscillation (two neutrino case): P α β = sin 2 (2θ)sin 2 ( m2 L 4E ) P = probability of a neutrino of flavor α later being measured to have a flavor β; θ = mixing angle; L = distance from neutrino source to detector; E = energy of neutrino; m 2 = neutrino squared mass difference 14

15 E can be computed from the energies of the neutrino s interaction products One of these products is the muon Unlike other particles, muons deposit low amounts of energy per length in the TPC 50% of the time, muon tracks are not fully contained in the fiducial volume Can t use range-based method of determining muon energy in these cases (requires full length of track) It is possible, however, to obtain the muon E for uncontained tracks through multiple coulomb scattering (MCS) 15

16 What is MCS? 16

17 What is Multiple Coulomb Scattering (MCS)? When a charged particle passes through some material, it undergoes collisions with atomic nuclei (Coulomb scattering) After experiencing each EM interaction, its trajectory is deflected from its initial direction 17

18 The collection of small deflections within the material are distributed like a Gaussian The mean is at 0 and the standard deviation is given by the Highland formula: 13.6 MeV l [ ( l )] θ 0 = z ln pβc X 0 X 0 p = particle momentum, β = ratio of particle velocity to c, l = distance travelled inside medium, X 0 = radiation length of target material Using the above formula, if we know the angular deflections, we can determine the momentum of the particle Momentum measurement through MCS is particularly useful for uncontained tracks Since we don t have the entire track length, can t use range-based calculations 18

19 How do we implement MCS? 19

20 Calculating Momentum - Maximum Likelihood Method Angular deflections are determined by splitting the particle s track into straight segments and computing the angle between adjacent segments After we have segmented the tracks, we need to find the momentum of the particle The Maximum Likelihood Method is the method we used to calculate momentum Used a minimum reconstructed track length of 100 cm Idea and implementation by Leonidas Kalousis DocDB: MicroBooNE-doc-3733-v1 (mctracks), MicroBooNE-doc-4050-v1 (reco tracks) Relativistic limit approximation is used in the MCS implementation 20

21 Maximum Likelihood Method: find the value of a parameter for a given statistic which makes the known likelihood distribution a maximum Use individual angle deflections as input to the likelihood p and standard deviation updated using energy-range relation Probability to measure a certain deflection, where f is a Gaussian function with mean 0 and standard deviation given by ( θ) std = θ0 2 + δθ2 0 (where δθ 0 is the angular resolution and is fixed to 0.5 mrad from MC): f ij = f (( θ) ij ; ( θ) std ) = 1 e 2π( θ)std ( θ) 2 ij 2( θ) 2 std With all angular deflections, we then build the likelihood product: L = (i, j) f ij 21

22 How does MCS perform on simulation? 22

23 Analysis of MC BNB Data Used Monte Carlo simulated BNB + CORSIKA cosmics files (pandoranupma) We start with 20,789 reconstructed neutrinos selected based on truth Matched 1 reco track to the outgoing muon from the neutrino interaction Plot of MC p vs. MCS p (all muons, track length > 100 cm): 4 Simulation: Muon MCS Momentum Correlation True Muon Momentum [GeV] Entries MCS Reco Momentum [GeV] 23

24 How do we quantify performance? 24

25 MC BNB Data: Quantifying Spread First we compute in bins of true muon momentum = MC p MCS p MC p The mean of shows the bias in the momentum estimation, the standard deviation shows the spread of the momentum estimation All plots are separated for muons that are fully contained in fiducial volume and exiting the fiducial volume Blue lines are contained muons, red lines are exiting 25

26 Mean vs. E: contained vs. uncontained muons 0.15 Mean vs. Energy Fractional P Mean Truth Muon Energy [GeV] For both contained and uncontained, mean bias under ± 10% For contained in particular, mean bias is under 5% 26

27 Std Dev vs. E: contained vs. uncontained muons 0.3 Std. Dev. vs. Energy Fractional P Std. Dev Truth Muon Energy [GeV] For contained muons, resolution is around 10%, no more than 20% For uncontained muons, resolution between 20-30% More limited statistics at higher energies, so more like below 24% resolution overall 27

28 What are the limitations of our implementation of MCS? There is a cut on track length at 100 cm! 28

29 Why did we choose a length of 100 cm? Leonidas initially set lower limit of recotrack length to 100 cm We set this to 20 cm and ran over the same sample The plot below is the momentum resolution as a function of track length for contained tracks only We can see that resolution worsens significantly with track lengths smaller than 100 cm, so we keep the 100 cm cut Contained Tracks: Standard Deviation vs. Reco Length Fractional Momentum Resolution Muon Reco Length (cm) 29

30 How does MCS perform on real data? 30

31 What would we compare MCS energy to? 31

32 Implementation of Range-Based E Crucial for working with real data For this plot, used MC BNB data to measure accuracy of range compared to truth for contained reco tracks Good correlation between range energy and true energy shows that we can use range-based energy for contained tracks in data Truth Momentum [GeV] Simulation: Truth vs. Range (Contained Muons) Reconstructed Range Momentum [GeV] ,257 entries 32

33 Used MC BNB data to compare MCS p with range: Range Recotrack Momentum [GeV] Simulation: Range vs. MCS Momentum (Contained Muons) Entries MCS Reco Momentum [GeV] Fairly good accuracy!

34 How do we select events? 34

35 Data and Methods Used real data files (same 5e19 POT the CCInclusive group used) Selected events with code based on CCInclusive Selection IIA Requires 2 tracks at the vertex The longest track is assumed to be the muon Additionally, we keep only events with contained muons (since range-based energy calculations don t work with uncontained muons) 35

36 Analysis of Real BNB Data 1,493 reconstructed neutrinos with contained muon Plot of Range vs. MCS p (470 entries because of minimum track length requirement): Range-Based Momentum [GeV] Real Data: Contained Tracks Momentum Correlation Entries MCS Reco Momentum [GeV] Good accuracy! Extra population is possible misid? Not yet understood 36

37 Mean vs. E: contained tracks 0.1 Mean vs. Energy 0.05 Fractional P Mean Range Based Muon Energy [GeV] Mean bias is still generally within 15% Similar to contained muons using MC BNB files 37

38 Std Dev vs. E: contained tracks 0.7 Std. Dev. vs. Energy Fractional P Std. Dev Range Based Muon Energy [GeV] Resolution goes from 60% at low energies to 10% at high energies High resolution is most likely due to the second population seen in the range vs. MCS p plot 38

39 What can we conclude? 39

40 Conclusion MCS is an important tool for anyone who wants to analyze escaping muons MCS was able to be implemented on both MC and real data Performance of MCS technique was quantified on real data for contained tracks by leveraging a range-based energy Some behavior not yet understood on data MCS can be used on real data to measure the momentum for tracks at 20% resolution 40

41 Acknowledgements Jose Crespo David Kaleko Mike Shaevitz Victor Genty Kazuhiro Terao Leslie Camilleri David Caratelli NSF MicroBooNE Nevis Laboratories and Columbia University John Parsons Amy Garwood Bill Seligman Thank you! 41

42 Backup Slides 42

43 Track Segmentation Reconstructed tracks have a very short distance between points and need to be grouped into larger segments Below is the same 1.1 GeV muon: mctrack vs. reco track z-axis 830 Single Muon: MCTrack z-axis 830 Single Muon: Track y-axis y-axis 43

44 Comparison for reconstruction error (tracks vs. mctracks) Contained Tracks: Standard Deviation vs. Reco Length Contained Mctracks: Standard Deviation vs. True Length Fractional Momentum Resolution Fractional Momentum Resolution Muon Reco Length (cm) Muon True Length (cm) Uncontained Tracks: Standard Deviation vs. Reco Length Uncontained Mctracks: Standard Deviation vs. True Length Fractional Momentum Resolution Fractional Momentum Resolution Muon Reco Length (cm) Muon True Length (cm) Similar, so reco tracks are probably well constructed 44