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

2. 2 Reminder  Goal is to measure from  +  Idea is that spectrum is almost identical in the LE and pME configurations except for the  + component: from  -,K - LE pME Selected events at 1.9x10 19 POT from  -,K - pME - LE from  + LE ME pHE diff

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

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

5. 5  For example, at 2.5x10 19 POT of pME data: 68.27% 90 %  At each fake experiment get best fit parameters: 24% measurement !

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

7. 7 Systematics  from  -,K - ) ME ( from  -,K - ) LE  Small correction of differences in  ,K  contributions to spectrum needs to be obtained from MC.  Vary contribution of difference by ±50%:  More generally: Observed no strong dependence in POT If correction is 50% too low 2.5x10 19 POT If correction is 50% too high 2.5x10 19 POT Note: true correction may be different than the one used here. Need more MC LE pME

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

9. 9  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 qe dis ma_qe x 1.5 ma_qe x 0.5 ratio res ratio ma_res x 1.5 ma_res x 0.5 effect in total cross-section (modif cs / nominal cs) ma_qe*1.5 ma_res*1.5 kno_r*1.2 ma_qe*0.5 ma_res*0.5 kno_r*0.8

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

11. 11  Performed the fit and introduced “success” parameters: sucLE = #antineutrinos from  + predicted by fit, LE #antineutrinos from  + in fake data, LE sucME = #antineutrinos from  + predicted by fit, pME #antineutrinos from  + in fake data, pME 2.5x10 19 POT  With these (huge) variations in the cross-section, introduced a bias of only -2.3% and +10% (independent of POT). ma_qe*1.5 ma_res*1.5 kno_r*1.2 2.5x10 19 POT ma_qe*0.5 ma_res*0.5 kno_r*0.8  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. 12 Summary & Ongoing work  Being fairly conservative, and assuming we know (pME-LE) ,K to 30% and a 10% systematic (8% in pME) due to cross-section shape uncertainty we get:  Need more pHE MC statistics to see if we can do something similar with the pHE data.  Need to look into cross-sections a bit more to understand better and get a realistic estimate of shape uncertainty. oEmpty markers are for statistical uncertainty only oHorizontal lines are systematic limits. from  +, LE from  +, pME preliminary

13. 13 Backup

14. 14 1x10 19 POT, no systematics 68.27% 90 %

15. 15 2.5x10 19 POT, no systematics 68.27% 90 %

16. 16 5x10 19 POT, no systematics 68.27% 90 %

17. 17 7.5x10 19 POT, no systematics 68.27% 90 %

18. 18 1.0x10 20 POT, no systematics 68.27% 90 %

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

20. 20  When simultaneously increasing parameters:  Introduce the “success” parameters: sucLE = #antineutrinos from  + predicted by fit, LE #antineutrinos from  + in fake data, LE sucME = #antineutrinos from  + predicted by fit, pME #antineutrinos from  + in fake data, pME  Found the right result to 2.3% ! “real” data fit from  + pME LE Observed no dependence with POT 2.5x10 19 POT

21. 21  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 2.5x10 19 POT:  Got it right to ~10%: “real” data fit Observed almost no dependence in POT (see backup) 2.5x10 19 POT

22. 22 CS systematics (ma_qe + ma_res down by 50%, kno_r down by 20%) 1x10 19 POT 5x10 19 POT 7.5x10 19 POT

23. 23 1x10 20 POT CS systematics (ma_qe + ma_res up by 50%, kno_r up by 20%) 1x10 19 POT 5x10 19 POT

24. 24 7.5x10 19 POT 1x10 20 POT CS systematics (ma_qe + ma_res up/down by 15%, kno_r by 10%) 2.5x10 19 POT ma_qe*0.85 ma_res*0.85 kno_r*0.9 ma_qe*1.15 ma_res*1.15 kno_r*1.1