Progress towards the extraction of exclusive - 40 Ar CCQElike - PowerPoint PPT Presentation

Progress towards the extraction of exclusive ν µ - 40 Ar CCQE–like cross–sections using the MicroBooNE LArTPC detector A.Papadopoulou On behalf of the MicroBooNE Collaboration June 10, 2019

Motivation C harged C urrent Q uasi– E lastic ( CCQE ) Interaction Channel MicroBooNE incoming flux range • Dominant interaction at low energies • Studies of neutrino energy reconstruction • Allows high precision oscillation studies 1 / 27

Existing Data • Extracted cross–sections on 12 C, 16 O, 56 Fe, 208 Pb • None on 40 Ar (heavy asymmetric nucleus, building nucleus of LArTPC detectors) 2 / 27

Objective First extraction of exclusive ν µ - 40 Ar CCQE–like differential cross–sections using the MicroBooNE detector 3 / 27

Signal Definition Vertex of 2 tracks µ • 1 muon ( ≥ 100 MeV/c) • 1 proton ( ≥ 300 MeV/c) p • No π 0 , no π ± ( ≥ 70 MeV/c) *We allow any number of e, γ , n and charged hadrons below these thresholds, which can be further lowered 4 / 27

Cosmic Background Rejection • MicroBooNE is a surface detector dominated by cosmics ◮ 1 ν interaction in ∼ 500 events ◮ After trigger application, 1 ν interaction in ∼ 10 events � Development of cosmic rejection machinery using detector and kinematics–based cuts ◮ arXiv:1812.05679 5 / 27

Cosmic Background Rejection Detector–based cuts ◮ Energy deposition profile ◮ Track length ◮ Scintillation light ◮ Collinearity Broken Track 6 / 27

Cosmic Background Rejection Kinematics–based cuts ◮ Vertex activity ◮ Coplanarity ◮ Transverse imbalance � miss = ( � P µ + � P ⊥ P p ) ⊥ 7 / 27

Statistics � Purity: 78.7 ± 1.1 % � Efficiency: 15.5 ± 0.2 % • # events measured: 462.0 ± (stat) 21.5* • # events expected: 486.4 ± (stat) 5.0 Though low statistics, first indication of consistency between data and simulation * Using ∼ 1 / 20 of the available data–sample 8 / 27

Cross–Section Extraction • Select events in data sample • Subtract cosmic related background • Subtract MC beam related background n − N o f f N on − B n ( d σ n dp µ ) n = η µ n · Φ ν · N tar g ets · ∆ µ n *Same for the proton and other kinematic variables 9 / 27

Cross–Section Extraction n − N o f f N on − B n ( d σ n dp µ ) n = η µ n · Φ ν · N tar g ets · ∆ µ n  N on – # of events in beam-on data      DATA  N o f f – # of events in beam-off data     10 / 27

Cross–Section Extraction n − N o f f N on − B n ( d σ n dp µ ) n = η µ n · Φ ν · N tar g ets · ∆ µ n   η – effective detection efficiency        (efficiencies & bin migration)    MC    B – background processes     11 / 27

Cross–Section Extraction n − N o f f N on − B n ( d σ n dp µ ) n = η µ n · Φ ν · N tar g ets · ∆ µ n   Φ ν – neutrino integrated flux        Constants N tar g ets – number of nuclei        ∆ – bin width  12 / 27

Differential Cross–Sections Work In Progress Muons Protons 10 data 10 MC 8 38 cm 2 ] 38 cm 2 ] 8 6 6 ) [10 p ) [10 4 4 d cos( d cos( d d 2 2 0 0 0.6 0.4 0.2 0.0 0.2 0.4 0.6 0.8 1.0 0.2 0.3 0.4 0.5 0.6 0.7 0.8 0.9 cos( ) cos( p ) *Only statistical errors included Non–negligible differencies 13 / 27

Differential Cross–Sections Work In Progress Muons Protons* 10 10 data MC 8 8 GeV / c ] GeV / c ] 38 cm 2 38 cm 2 6 6 dp [ 10 dp p [ 10 4 4 d d 2 2 0 0 0.2 0.4 0.6 0.8 1.0 1.2 1.4 0.3 0.4 0.5 0.6 0.7 0.8 0.9 1.0 p [GeV/c] p p [GeV/c] Non–negligible discrepancies *First attempt to extract proton differential cross–sections at such low momenta 14 / 27

Differential Cross–Sections Work In Progress Muons Protons data 0.020 0.016 MC 0.014 deg . ] deg . ] 0.015 0.012 38 cm 2 38 cm 2 0.010 0.010 0.008 [ 10 p [ 10 0.006 d d d 0.005 d 0.004 0.002 0.000 0.000 150 100 50 0 50 100 150 150 100 50 0 50 100 150 [deg.] p [deg.] Sanity check Uniform distributions in polar angle 15 / 27

Wrap Up & Future ✓ Progress towards first extraction of � exclusive ν µ - 40 Ar CCQE–like differential cross–sections using data from the MicroBooNE LArTPC detector ✓ Finalizing systematical studies � *Paper published in the near future 16 / 27

Thank you! 17 / 27

Backup Slides 18 / 27

The MicroBooNE Experiment 19 / 27

The MicroBooNE Detector 20 / 27

Pre–Selection Hardware and Software Triggers ◮ 1 ν interaction in ∼ 1000 triggered events ◮ PMT trigger enriches this ratio to 1 ν interaction in ∼ 10 events Collection of track pairs at close proximity ◮ arXiv:1812.05679 21 / 27

Pre–Selection • Pairs of tracks at close proximity: distance < 11 cm between any two edges (start-start, start-end, end-start, end-end) E S S E 22 / 27

Statistics 23 / 27

Migration Matrices 24 / 27

Effective Efficiency 25 / 27

Background 26 / 27

Systematics ✓ Event selection cuts � ✓ Beam flux � ✓ POT � ✓ Efficiencies due to correlations � ✗ Detector modeling � ✗ Event generator � 27 / 27