Beam n e ’s from antineutrinos using the pME and LE beams

1. Beam ne’s from antineutrinos using the pME and LE beams David Jaffe, Pedro Ochoa • Part 1: Reminder and update • Part 2: Change in technique • Part 3: Systematics December 8th 2006

2. Idea is that n spectrum is almost identical in the LE and pME configurations except for the m+ component: n from p-,K- n from p-,K- n from m+ Reminder • Goal is to measure n from m+ pME - LE LE pME diff Selected events at 1.9x1019 POT LE ME pHE

3. (n from p-,K-)ME (n from p-,K-)LE n from m+ n from m+ (pME-LE)”TRUE” at 1e18 POT • So take the pME-LE difference • And fit with two parameters: pME LE • To make feasibility study, get “true” distributions by fitting raw MC:

4. Change in technique • Now the fit is done “manually”: parLE=1 parME=1 parLE=0 parME=1 parLE=0.5 parME=2 1) Generate typically 40,000 “expected histograms” Ei for different combinations of parLE and parME parLE=2 parME=0.5 parLE=1 parME=0 … etc 2) Generate fake data by fluctuating pME “data” Di antineutrinos with a Poisson (assume ∞ MC and LE data) 3) Compare the fake data with each expected histogram by means of a chi-squared: (pME-LE)FAKE at 1e19 POT (Note: not using first bin) 4) Steps 2 and 3 are repeated 5000 times. 5) Get average c2 and subtract the minimum

5. For example, at 2.5x1019 POT of pME data: 68.27% 90 % • At each fake experiment get best fit parameters: 24% measurement !

6. n from m+, LE n from m+, pME • Statistical sensitivity of the method vs. pME-POT: preliminary Details available in backup plots • Promising. Maybe can improve considerably by relaxing cuts. • What about systematics? 2 types: 1) Not getting the right (pME-LE)p,K from MC 2) Not getting the right shape(s) from MC.

7. Small correction of differences in p-,K- contributions to n spectrum needs to be obtained from MC. (n from p-,K-)ME (n from p-,K-)LE LE pME Systematics If correction is 50% too low If correction is 50% too high • Vary contribution of difference by ±50%: 2.5x1019 POT 2.5x1019 POT • More generally: Observed no strong dependence in POT Note: true correction may be different than the one used here. Need more MC

8. n cross-section energy dependence has big uncertainty at low E • What if we don’t have the right shape? (plot by Donna Naples) • Estimating an error on the cross-section shape is hard. See talk in physics simulations parallel session.

9. disn qen resn • For now just try to be on safe side: Varied cross-section parameters ma_qe, ma_res and kno_r (all) by 50%, 50% and 20% respectively ma_res x 1.5 ratio ma_res x 0.5 ma_qe x 1.5 ratio ratio ma_qe x 0.5 ma_qe*1.5 ma_res*1.5 kno_r*1.2 effect in total cross-section(modif cs / nominal cs) ma_qe*0.5 ma_res*0.5 kno_r*0.8

10. n from p-,K- n from p-,K- n from m+ n from m+ • Effect of simultaneously increasing ma_qe, ma_res and kno_r (all) in the “true” data ( normal, with systematic): LE pME LE pME

11. #antineutrinos from m+ predicted by fit, LE sucLE = #antineutrinos from m+ in fake data, LE #antineutrinos from m+ predicted by fit, pME sucME = #antineutrinos from m+ in fake data, pME • Performed the fit and introduced “success” parameters: 2.5x1019 POT 2.5x1019 POT ma_qe*1.5 ma_res*1.5 kno_r*1.2 ma_qe*0.5 ma_res*0.5 kno_r*0.8 • With these (huge) variations in the cross-section, introduced a bias of only -2.3% and +10% (independent of POT). • With a more conservative scenario of varying ma_qe, ma_res and kno_r by 15%, 15% and 10% respectively, introduce a bias of ±2%

12. n from m+, LE n from m+, pME Summary & Ongoing work • Need to look into cross-sections a bit more to understand better and get a realistic estimate of shape uncertainty. • Being fairly conservative, and assuming we know (pME-LE)p,K to 30% and a 10% systematic (8% in pME) due to cross-section shape uncertainty we get: preliminary • Empty markers are for statistical uncertainty only • Horizontal lines are systematic limits. • Need more pHE MC statistics to see if we can do something similar with the pHE data.

13. Backup

14. 1x1019 POT, no systematics 68.27% 90 %

15. 2.5x1019 POT, no systematics 68.27% 90 %

16. 5x1019 POT, no systematics 68.27% 90 %

17. 7.5x1019 POT, no systematics 68.27% 90 %

18. 1.0x1020 POT, no systematics 68.27% 90 %

19. n from p-,K- n from p-,K- n from m+ n from m+ • Effect of simultaneously decreasing ma_qe, ma_res and kno_r (all) in the “true” data ( normal, with systematic): LE pME LE pME

20. #antineutrinos from m+ predicted by fit, LE sucLE = #antineutrinos from m+ in fake data, LE #antineutrinos from m+ predicted by fit, pME n from m+ n from m+ sucME = #antineutrinos from m+ in fake data, pME “real” data fit • When simultaneously increasing parameters: 2.5x1019 POT • Introduce the “success” parameters: 2.5x1019 POT • Found the right result to 2.3% ! Observed no dependence with POT LE pME

21. “real” data fit • Now simultaneously scale down ma_qe, ma_res and kno_r (all) by 50%, 50% and 20% respectively: effect in total cross-section • Fit gives, at 2.5x1019 POT: 2.5x1019 POT • Got it right to ~10%: Observed almost no dependence in POT (see backup)

22. CS systematics (ma_qe + ma_res down by 50%, kno_r down by 20%) 1x1019 POT 5x1019 POT 7.5x1019 POT

23. 1x1020 POT CS systematics (ma_qe + ma_res up by 50%, kno_r up by 20%) 1x1019 POT 5x1019 POT

24. 7.5x1019 POT 1x1020 POT CS systematics (ma_qe + ma_res up/down by 15%, kno_r by 10%) ma_qe*1.15 ma_res*1.15 kno_r*1.1 2.5x1019 POT ma_qe*0.85 ma_res*0.85 kno_r*0.9