Sci Bar homework M Yokoyama For Sci Bar
Sci. Bar homework M. Yokoyama For Sci. Bar group
Current status of Sci. Bar • Total # of interaction (1. 74 x 10^19 POT) • For 10 t fiducial volume • Scaled from MRD sample with MC fraction CCQE CC 1 pi(charged) CC 1 pi(neutral) CC-other NC elastic (n+p) NC 1 pi(neutral) NC-other Total 7427 ~1, 500 at En<1 Ge. V 5648 1268 What can we do with 2757 current and more data? 1374 1446 Actually, x efficiency 3569 23491
What can we do with more data? • Improvement of K 2 K analysis – Nsk (Probably we can reduce systematic to a few % level w/ more statistics. ) – Spectrum measurement especially at En<1 Ge. V – Neutrino interaction model – NC cross-section measurement • Preparation for T 2 K experiment – CC-1 pi cross-section measurement? – NC-1 pi cross-section measurement?
Improvement of K 2 K analysis
Spectrum meas. w/ exclusive reconstruction • Different (potentially small) systematics 2 track CC-QE enriched sample, ~1250 CC-QE candidates with ~70% purity *Efficiency for low-energy events will be improved
Better understanding of n int. • One example: low q 2 deficit – No coherent p? – Or, CC-1 p suppression? • Need more (>x 2) data to cleanup sample and get definite answer M. Hasegawa CC-1 pi enriched Rec. q 2 Coherent pi enriched CCQE CC 1 pi Coherent Pi Others Rec. q 2
nue flux measurement • We should have ~100 nue CCQE interactions in current sample. • If we want to measure flux as a function of Enu (e. g. 4 bins? ), we need more data.
Preparation for T 2 K experiment
T 2 K nm disappearance • Non-QE background at oscillation maximum Rec. En spectrum at SK (OA 2. 5 deg) NC w/o oscillation CC-other Non-QE (sin 2 2 q, Dm 2) =(1. 0, 0. 0027) Study by K. hiraide CC-coherent CC-1 p Dominated by CC-1 pi
CC-1 pi in Sci. Bar • Can be reconstructed as “ 2 -track µµ” events Cross-section (10 -38 cm 2) – Both tracks are “µ-like” w/ PID • With x 2 -x 3 data, we can measure crosssection (CC-1 pi/CC-QE) w/ ~<10% error. CC-1 pi CC-QE Expected number of int. w/ current data set Enu 0. 5 -0. 75 -1. 01. 25 #evt 170 540 810
So, Systematic error on Nsk is already larger than statistics. Sci. Bar might be able to improve this. • We (Sci. Bar group) need more data, at least double (hopefully triple) the current statistics. – ~2 x 1019 POT more physics data.
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