Wrong Sign Contamination in NOvA Abhilash Yallappa Dombara (Syracuse University) for NOvA collaboration • NOvA is an off-axis (14.6 mrad), long baseline (810 km) neutrino oscillation experiment which uses NuMI beam at Fermilab. NOνA experiment Wrong Sign contamination Analysis procedure • The wrong sign fraction is estimated for electron neutrinos and muon neutrinos separately. • CNN (Convolutional Neural Network) was trained on simulation to identify neutrino and antineutrino events and validated with data. • A optimal cut value was chosen for Wrong Sign CNN ID based on efficiency and purity to separate the whole sample into wrong sign and right sign enhanced regions. • Compute the wrong sign fraction using matrix method 𝛼𝐵!" + 𝛽𝑆!# = 𝐷!# 𝛼𝐵$# + 𝛽𝑆$# = 𝐷$# 𝛼, 𝛽: Fit parameters D: Data S: Signal = 𝜈e , 𝜈μ CC and NC B: Background = $νe , $νμ CC and NC RS: Right sign enhanced WS: Wrong sign enhanced 𝑊𝑟𝑜𝑛𝑔𝑠𝑖𝑔𝑛𝑓𝑟𝑎𝑐𝑡𝑖𝑜𝑛= 𝛽(𝑆!" + 𝑆#") 𝛽𝑆!" + 𝑆#" + 𝛼( 𝐵!$ + 𝐵#") 𝑊𝑟𝑜𝑛𝑔𝑠𝑖𝑔𝑛𝑒𝑟𝑟𝑜𝑟= 𝐶%%(𝑆!" + 𝑆#")% (𝐷!$+𝐷#")% Matrix : 𝑀= 𝐵!" 𝑆!" 𝐵#" 𝑆#" Covariance matrix : C = 𝑀&' 𝜎(!" 0 0 𝜎(#" 𝑀) Analysis Results s Analysis Methods • Wrong sign contamination is fraction of neutrinos/antineutrinos in antineutrino/neutrino beam. • Wrong sign fraction is higher in antineutrino beam. • Wrong sign fraction affects our mass hierarchy and ẟcp. measurements because these parameters are estimated based on difference between 𝜈eand )νe appearance. • All possible wrong sign values for different universes of cross-section, beam and flux uncertainties is shown in blue histogram. Remaining systematics under investigation. • Currently used as data driven crosscheck but in future can be used for extrapolation. • Neutron capture method: Neutrinos are more likely to produce 𝜇% which gets absorbed in nucleus and produce delayed neutrons while antineutrinos don’t. • Prong CVN score: Identify neutrinos using a single particle classifier for proton identification • Wrong Sign CNN score: Dedicated CNN for classifying neutrinos and antineutrinos based on topological features • NOvA’s main goal is to use muon neutrino disappearance and electron neutrino appearance to probe neutrino mass ordering, ∆𝑚&' ' , q23 and dcp. • NOvA uses two functionally identical liquid scintillator detectors. 100 − 0 100 200 y (cm) 2200 2400 z (cm) 10 2 10 3 10 q (ADC) NOvA - FNAL E929 Run: 15330 / 4 Event: 11978 / -- UTC Fri May 23, 2014 17:30:2.632293184 Far Detector Data 5400 5600 500 600 700 y (cm) z (cm) 10 2 10 3 10 q (ADC) NOvA - FNAL E929 Run: 26110 / 49 Event: 3213 / -- UTC Sun May 7, 2017 04:41:20.910875840 Far Detector Data 0 5 10 15 Analysis bins 0 500 1000 1500 POT 20 Events / 11.09x10 NOvA Preliminary Beam n Wrong Sign enhanced Right Sign enhanced e n µ n e n µ n NC n NC n DATA High PID, 𝜈e selection 0.1 0.2 0.3 0.4 0.5 Wrong-sign fraction 0 200 400 600 Fake experiments Flux and cross- section systematic fake experiments Prong CVN Wrong Sign CNN NOvA Preliminary Beam n High PID, 𝜈e selection 0 0.05 0.1 0.15 Wrong-sign fraction 0 200 400 600 800 1000 1200 Fake experiments Flux and cross- section systematic fake experiments Wrong Sign CNN Neutron Capture Rate NOvA Preliminary Beam n 𝜈μ selection Neutrino Event Antineutrino Event 5 - 0 5 Background Uncertainty (%) Systematic Uncertainty Lepton Reconstruction Neutron Uncertainty Beam Flux Near-Far Uncor. Neutrino Cross Sections Detector Response Detector Calibration -beam n Selection e n NOvA Preliminary 0 0.2 0.4 0.6 0.8 Wrong Sign CNN 0 200 400 600 800 POT 20 Events / 11.6x10 NOvA Preliminary Beam n Data MC e n e n High PID, 𝜈e selection 2 - 0 2 Signal Uncertainty (%) Systematic Uncertainty Beam Flux Detector Calibration Lepton Reconstruction Detector Response Neutron Uncertainty Near-Far Uncor. Neutrino Cross Sections -beam n Selection e n NOvA Preliminary