Download presentation
Presentation is loading. Please wait.
1
1 Using the pHE data to measure the beam e ’s from + decay David Jaffe and Pedro Ochoa March 13 th 2007 Introduction Antineutrino selection Feasibility study Systematics
2
2 Introduction David and Pedro proposed making this measurement with pME data (minos-doc-2706). Getting that data seems complicated. 2 main reasons: Fear of moving target after previous experience. Some people feel physics case not strong enough. Could we use the already existing pHE data taken after the shutdown? With pHE data expect: Improvement since antineutrinos from + decay in pHE ( ( + ) pHE ) peak at higher energies (i.e. better separation with ( + ) LE ). Degradation since less POT (~2.0x10 19 ) and higher systematics. Beginning of talk considers only statistics of available pHE data. Without sufficient statistical precision would not proceed further.
3
3 Selection Some features of PID in cedar not completely understood. For now treat as black box. Use (at least for now) nubar-PID selection (minos-doc-2377): Used daikon-cedar MC: 4.11x10 18 POT of pHE and 1.07x10 20 POT of LE. CC NC Use cut at nubar-PID > 0.9: EfficiencyPurity LE56.2%99.1% pHE51.3%97.1% LE-10pHE
4
4 Parent K + Selection in LE configuration: Background composition Background Selection vs. E reco Selection vs. E true Efficiency and Purity
5
5 Parent K + Selection in pHE configuration: Background composition Background Selection vs. E reco Selection vs. E true Efficiency and Purity
6
6 ( + ) pHE ( + ) LE ( ,K - ) pHE ( ,K - ) LE Background is problem in pHE. For now ignore. Make feasibility study with fitted spectra: Scaled to 1x10 20 POT Feasibility study very distinct
7
7 Scaled to 2e19 POT Fake experiment at 2e19 POT in MC in feasibility study one fit x parLE ( + ) pHE ( ,K) pHE - ( ,K) LE x parHE ( + ) LE Good agreement for ( ,K) pHE - ( ,K) LE in MC and in feasibility study: Note: Assume infinite MC and LE statistics Procedure: - fit pHE-LE with spectral shapes from MC. - scale ( + ) LE and ( + ) pHE by parameters parLE and parHE.
8
8 13% stat. uncertainty ! Assume we get ( ,K) pHE - ( ,K) LE exactly. Results of 5,000 fits at 2.0x10 20 POT of pHE data: 90% C.L.68.3% C.L. Less correlation between parameters than in pME case (c.f. minos-doc-2504) ( + ) pHE peaking at higher energy really helps us. However… (see next slide) Fit done manually (described in minos-doc-2504)
9
9 Systematics Systematics are the key to this measurement. Mainly: ( ,K) pHE - ( ,K) LE correction. Background in pHE. Preliminary look at C = ( ,K) pHE - ( ,K) LE : | Bias in parLE || Bias in parHE | C wrong by ± 50%~64.5%53.5% C wrong by ± 30%~38.1%~32.1% C wrong by ± 15%~19.2%~16.1% Note: As pointed out by Stan, best way to look at C is not in percentage form. This is just to get an idea. If want to know beam e ’s to ~30%, need to know C to ~20% or better if it is the dominant systematic uncertainty. From experience with pME cross-section shape uncertainties should not be big problem. Maybe can absorb some of this uncertainty by adding another parameter that scales C. Will look into it.
10
10 Summary & Ongoing work Measurement is possible to 13% from statistics point of view, using already existing pHE data. Work in progress to understand the 2 main systematics: ( ,K) pHE - ( ,K) LE correction Background in pHE selection. Goal is to incorporate this into e analysis with MCNN selection.
11
11 Backup
12
12 Smooth spectra scaled to 1e18 POT ( + ) pHE ( + ) LE ( ,K - ) pHE ( ,K - ) LE
13
13 If get wrong ( ,K) pHE – ( ,K) LE by -50%:
14
14 If get wrong ( ,K) pHE – ( ,K) LE by +50%:
15
15 If get wrong ( ,K) pHE – ( ,K) LE by -30%: If get wrong ( ,K) pHE – ( ,K) LE by +30%:
16
16 If get wrong ( ,K) pHE – ( ,K) LE by +15%: If get wrong ( ,K) pHE – ( ,K) LE by -15%:
Similar presentations
© 2025 SlidePlayer.com. Inc.
All rights reserved.