1. Analysis of  and e events from NuMI beamline at MiniBooNE
Zelimir Djurcic (a) and Zarko Pavlovic (b)
Columbia University
(b) University of Texas Austin
Outline of this Presentation
Off-axis Neutrino Beam
NuMI flux at MiniBooNE
MiniBooNE Detector and Reconstruction
CC nm Sample
NC p0 Sample
CC ne Sample

2. Analysis Motivation
Joint collaboration between MiniBooNE and NuMI. Observation and analysis of an off-axis beam. Measurement of /K components of the NuMI beam. Check of nm CCQE and ne CCQE interactions independent from Booster beam neutrinos. ne-rich sample to study MiniBooNE reconstruction and particle identification algorithms. Performing physics analysis complementary to MinibooNE analyses.

3. NuMI Beam and MiniBooNE Detector
NuMI events (for MINOS) detected in MiniBooNE detector!
MiniBooNE q
p beam
p, K
Decay Pipe
MiniBooNE detector is 745 meters downstream of NuMI target.
MiniBooNE detector is 110 mrad off-axis from the target
along NuMI decay pipe.

4. The Woes of Knowing the n flux
For wide-band(*) neutrino beams,
Use MC simulation
Particle production
Focusing
Measure in the detector
Use some process with known cross section
History has several examples of substantial corrections to these estimates
ANL 12’ B.C. in ZGS horn beam
FNAL 15’ B.C., 400GeV horn beam
BNL E734, AGS horn beam
Gargamelle, CERN PS beam
Borodovsky et al., Phys. Rev. Lett. 68, 274 (1992)
(BNL E776 ) got flux correct, right ‘out of the box’
(*) Narrow-band beams can more readily measure fluxes directly

5. Off axis beam
On-axis, neutrino energy more tightly related to hadron energy
Off-axis, neutrino spectrum is narrow-band and ‘softened’
Easier to estimate flux correctly: all mesons decay to same energy n.
n Detector
First Proposed
by BNL-E889
Decay Pipe q
Target
Horns

6. Future off axis experiments
On-axis beam
Off-axis beam
Use off-axis trick for optimized nmne search
NOvA
NuMI off-axis beam
810km baseline
14.5mrad; Enu~2GeV
T2K
J-PARC 50GeV proton beam
Use SK as Far detector 295km away
35 mrad; Enu~0.6GeV

7. NuMI Off-axis Beam at MiniBooNEK+ p+
stopped K+
stopped p+
Opportunity to demonstrate off-axis technique
Known spectral features from p, K decays
Expected energy spectra softened to within MiniBooNE acceptance

8. NuMI as a “ne Source”
NuMI off-axis beam produces strong flux in both nm and ne flavors.
The ne’s are helpful to study the MiniBooNE detector.
Hopefully one can do some physics with a ‘enhanced’ ne beam
NuMI on-axis ne ~1% NuMI off-axis ne ~6% BNB on-axis ne ~0.5%
stopped K+ m+ K+

9. NuMI Spectrum is “Calibrated”
Extensive experience with MINOS data
MINOS acquired datasets in variety of NuMI configurations
Tuned kaon and pion production (xF,pT) to MINOS data
MINOS nm
MINOS nm
Same parent hadrons produce neutrinos seen by MiniBooNE
Flux at MiniBooNE should be well-described by NuMI beam MC?
D.G. Michael et al, Phys. Rev. Lett. 97: (2006)
D.G. Michael et al, arXiv: (2007)

10. Two views of the same decays
Decays of hadrons produce neutrinos that strike both MINOS and MiniBooNE
Parent hadrons ‘sculpted’ by the two detectors’ acceptances.
Plotted are pT and p|| of hadrons which contribute neutrinos to MINOS (contours) or MiniBooNE (color scale)
MiniBooNE
MiniBooNE
MINOS
MINOS

11. Neutrino Sources along NuMI beam
Higher energy neutrinos mostly from particles created in target
Interactions in shielding and beam absorber contributes in lowest energy bins
Colors indicate the origin of  parents nm
MiniBooNE
diagram not to scale!

12. Flux Uncertainties Focusing uncertainties are negligible
Uncertainty is dominated by production of hadrons
off the target (estimated from MINOS tuning)
in the shielding (estimated in gfluka/gcalor)
in beam absorber (estimated in gfluka, 50% error assigned)
MINOS
Tuning
stopped mesons excluded in this plot

13. (Booster Neutrino Experiment) An off axis neutrino experiment
MiniBooNE
(Booster Neutrino Experiment)
becomes
An off axis neutrino experiment
using Main Injector

14. NuMI Beam and MiniBooNE Detector
NuMI events (for MINOS) detected in MiniBooNE detector!
MiniBooNE q
p beam
p, K
Decay Pipe
MiniBooNE Detector:
12m diameter sphere
liters of oil(CH2)
1280 inner PMTs
240 veto PMTs
Main trigger is an accelerator signal indicating a beam spill.
Information is read out in 19.2 s interval covering arrival of beam.

15. Detector Operation and Event reconstruction
No high level analysis needed to see neutrino events
Events in DAQ window:no cuts
Removed cosmic ray muons:
PMT veto hits < 6
Removed cosmic ray muons
and -decay electrons:
PMT veto hits < 6 and
PMT tank hits > 200
6-batch structure of MI
about 10 s duration
reproduced.
Backgrounds: cosmic muons and decay electrons
->Simple cuts reduce non-beam backgrounds to ~10-5

16. Detector Operation and Event reconstruction
The rate of neutrino candidates was constant: 0.51 x /P.O.T.
Neutrino candidates counted with:PMT veto hits < 6 and PMT tank hits > 200
The data set analyzed here: 1.42 x 1020 P.O.T.
We have a factor two more data to analyze!

17. Particle Identification
Čerenkov rings provide primary means of identifying
products of  interactions in the detector m
candidate
nm n  m- p
electron candidate
ne n  e- p p0
candidate
nm p  nm p p0
n n
p0 → gg

18. Events from NuMI detected at MiniBooNE
Flux
Event
rates
NuMI event composition at MB
-81%, e-5%,-13%,e-1%
Neutrino interactions at carbon simulated by
NUANCE event generator: neutrino flux
converted into event rates.
Event
rates
CCQE 39%
CC + 26%
NC  %

19. Analysis Algorithm

20. Event Reconstruction
The tools used in the analysis here are developed and verified
in MiniBooNE oscillation analysis of events from Booster beam.
Details:
Phys. Rev. Lett. 98, (2007),
arXiv: [hep-ex]
arXiv: [hep-ex]
Accepted for publ. by Phys.Rev.Lett.
and
Event selection very similar to what was used in MiniBooNE analyses.
To reconstruct an event:
-Separate hits in beam window by time into sub-events of related hits.
-Reconstruction package
maximizes likelihood of
observed charge and time
distribution of PMT hits to
find track position, direction
and energy (from the
charge in the cone) for
each sub-event.

21. Analysis Method log(Le/L)
Uses detailed, direct reconstruction of particle tracks, and ratio of fit likelihoods to identify particles.
Apply likelihood fits to three hypotheses:
-single electron track
-single muon track
-two electron-like rings (0 event hypothesis )
Compare observed light distribution to fit prediction:
Does the track actually look like an electron?
Form likelihood differences using minimized –logL quantities: log(Le/L) and log(Le/L)
log(Le/L)<0 -like events
log(Le/L)
log(Le/L)>0 e-like events
Example from MiniBooNE
Oscillation Analysis.  e

22.  CCQE Analysis

23. Analysis of the  CCQE events from NuMI beam
 CCQE (+n  +p) has a two “subevent” structure
(with the second subevent from stopped  e e)
Tank Hits  e
Cerenkov 1  e nm
12C
Cerenkov 2 n p
Scintillation
Event Selection:
Subevent 1:
Thits>200, Vhits<6
R<500 cm
Le/L < 0.02
Subevent 2:
Thits<200, Veto<6

24. Visible E of : final state interactions in  CCQE sample
Log(Le/L)< 0.02
Total MC
nNnXp0
Beam ne
nmp m-D
nmn m-p
nmn m-np+
Other nm Events
Events
Data
CCQE
Monte
Carlo
“other”
CC+
CCQE
CC+
PRELIMINARY
Visible energy in tank [GeV]
Data (stat errors only)
compared to MC prediction
for visible energy in the
tank.
This sample contains events
of which 70% are CCQE’s.

25. Compare  CCQE MC to Data:Parent Components
Beam MC tuned
with MINOS near
detector data.
Cross-section
Monte Carlo
tuned with MB
measurement of
CCQE pars MA
and . p K
PRELIMINARY
arXiv: [hep-ex]
Visible energy in tank [GeV]
MC is normalized to data POT number with no further corrections!

26. Compare  CCQE MC to Data:Parent ComponentsK
PRELIMINARY
Visible energy in tank [GeV]
Predicted Kaons are matching the data out of box!

27. Systematic Uncertainties in  CCQE analysis
To evaluate Monte Carlo agreement with the data need estimate
of systematics from three sources:
-Beam modeling: flux uncertainties.
-Cross-section model: neutrino cross-section uncertainties.
-Detector Model:describes how the light emits, propagates, and
absorbs in the detector (how detected particle looks like?).
Detector Model
Cross-section
Visible energy [GeV]
Visible energy [GeV]
Total
PRELIMINARY
Beam
PRELIMINARY
Visible energy [GeV]
Visible energy [GeV]

28. Add Systematic uncertainty to  CCQE Monte Carlop
Predicted Pions are
matching the data
within systematics! K
 visible energy distribution
PRELIMINARY
Visible energy in tank [GeV] K p
Outgoing angular distribution
PRELIMINARY
Information about
incoming :wrt NuMI
target direction.
cos 

29.  CCQE sample: Reconstructed energy E of incoming 
Reconstructed E QE:from Elepton
(“visible energy”) and lepton angle
wrt neutrino direction p K
PRELIMINARY
Understanding of the beam demonstrated:
MC is normalized to data POT number !

30. Conclusion from  CCQE analysis section
This is the first demonstration of the off-axis principle.
There is very good agreement between data and Monte Carlo:the MC need not be tuned.
Because of the good data/MC agreement
in  flux and because the  and e
share same parents the beam MC can
now be used to predict:
e rate, and
mis-id backgrounds for a e analysis.

31. e CCQE Analysis

32. Backgrounds to e CCQE sample
e CCQE (+n  e+p)
When we try to isolate a sample of e candidates
we find background contribution to it:
-0 (0) and radiative  (N) events, and
-”dirt” events.
Therefore, before analyzing e CCQE we constrain the
backgrounds by measurement in our own data.

33. Analysis of 0 events from NuMI beam
Among the e-like mis-ids, 0 decays which are boosted, producing 1 weak ring and 1 strong ring is largest source. g g p0  g 
Strategy:Don’t try to predict the
0 mis-id rate, measure it!
Measured rates of reconstructed 0…
tie down the rate of mis-ids g + 0 p p p + g 
 decays to a single photon:
with 0.56% probability:
What is applied to select 0s
Event pre-selection:
1 subevent
Thits>200, Vhits<600
R<500 cm
log(Le/L)>0.05 (e-like) log(Le/L)<0 (0-like)

34. Analysis of 0 events from NuMI beam: 0 mass
The peak is 135 MeV/c2
Data
Monte
Carlo 0  e
e appear to be well modelled.
This sample contains 4900 events of which 81% are 0 events: world second largest 0 sample!

35. Analysis of 0 events from NuMI beam: 0 mass
The peak is 135 MeV/c2
Data
Monte
Carlo 0  e
The 0 events are well modeled with
no corrections to the Monte Carlo!

36. Analysis of 0 events from NuMI beam: 0 momentum
Data
Monte
Carlo  0 e
PRELIMINARY
We declare good MC/Data agreement
for 0 sample going down to low mass
region where e candidates are showing up!
Further
Cross
Check!

37. Analysis of dirt events from NuMI beam
shower
dirt
- “Dirt” background is due to  interactions
outside detector. Final states
(mostly neutral current interactions)
enter the detector.
- Measured in “dirt-enhanced” samples:
- we tune MC to the data selecting a sample
dominated by these events.
-”Dirt” events coming from outside deposit only a fraction
of original energy closer to the inner tank walls.
-Shape of visible energy and event vertex distance-to-wall distributions are well-described by MC: good quantities to measure this background
component.

38. Selecting the dirt events
log(Le/L)>0.05 (e-like)
Ee <550 MeV
Distance-to-wall <250 cm
m<70 MeV/c2 (not 0-like)
Event pre-selection:
1 subevent
Thits>200, Vhits<600
R<500 cm
Fits to dirt enhanced sample:
Uncertainty in the dirt rate is less than 20%.
Dirt sample
interactions
in the tank
Events/bin
Events/bin
PRELIMINARY
We declare good MC/Data agreement for the dirt sample.
Dist-to-wall of tank along track [m]
Visible energy [GeV]

39. Analysis of the e CCQE events from NuMI beam
e CCQE (+n  e+p)
1 Subevent
Thits>200, Vhits<6
R<500 cm, Ee>200MeV
Likelihood cuts as the
as shown below +
Ee>200MeV cut is appropriate to remove e contribution from the dump
that is hard to model.
Likelihood e/ cut
Likelihood e/ cut
Mass(0) cut
Signal region
Signal region
Cut region
MC example plots here come from Booster beam MC
Cut region
Cut region
Signal region
Visible energy [MeV]
Visible energy [MeV]
Visible energy [MeV]
Analysis of e events: do we see data/MC agreement?

40. Visible energy of e CCQE events
Data
Monte Carlo e
Other  0
dirt
PRELIMINARY 
Visible energy in tank [GeV]
Data = 783 events.
Monte Carlo prediction = 662 events.
Before we further characterize data/MC agreement we have to account for the systematic uncertainties.

41. Systematic Uncertainties in e CCQE analysis
Detector Model
Cross-section
PRELIMINARY
Beam
Visible energy [GeV]
PRELIMINARY
Visible energy [GeV]
Total
Visible energy [GeV]
Visible energy [GeV]
“dirt” component of Xsec: 20% error; 0 component of Xsec: 25% error

42. e CCQE events: e visible energy and angular distributionK
e visible energy distribution KL 
PRELIMINARY p
Visible energy in tank [GeV]
All 
All 
Outgoing e angular distribution
PRELIMINARY
cos e

43. Outgoing electron angular distribution
e CCQE sample: Reconstructed energy E of incoming 
Outgoing electron angular distribution
PRELIMINARY
All e
All 

44. Summary of estimated backgrounds vs data e CCQE sample
Looking quantitative into low energy and high energy region:
E QE [MeV]
total background ± ±50
e intrinsic
 induced
NC 
NC →N
Dirt
other
Data ± ±17
Data-MC  53
Significance  
At this point systematic errors are large: we cannot say much about the difference between low and high-E regions. In the future we will reduce e CCQE sample systematics constraining it with our large statistics  CCQE sample.

45. Summary and Future Steps

46. We performed analyses of neutrinos from NuMI beam observed with MiniBooNE detector. The sample analyzed here corresponds to 1.42x 1020 protons on NuMI target.
We observed good description of the data by Monte Carlo
with both  CCQE and e CCQE sample: successful
demonstration of an off-axis beam at 110 mrad.
 CCQE sample demonstrated proper understanding of the
Pion and Kaon contribution to neutrino beam.
PRELIMINARY

47. We are currently reprocessing and collecting more data
In the future we will reduce e CCQE sample systematics constraining it with our large statistics  CCQE sample.
The e CCQE sample will be compared to what we observed with Booster beam.
We are currently reprocessing and collecting more data
(expect about 3 x 1020 P.O.T. collected by now.)
These errors
will be reduced
PRELIMINARY

48. Backups

49. Neutrino Sources along NuMI beam
Higher energy neutrinos mostly from particles created in target
Interactions in shielding and beam absorber contributes in lowest energy bins

50. NuMI Off-axis Beam at MiniBooNE
1st opportunity to demonstrate off-axis technique
Known spectral features from p, K decays
Expected energy spectra softened to within MiniBooNE acceptance
stopped p+
stopped K+
stopped K-

51. NuMI as a “ne Source”
NuMI off-axis beam produces strong flux in both nm and ne flavors.
The ne’s are helpful to study the MiniBooNE detector.
Hopefully one can do some physics with a ‘pure’ ne beam (only a few past proposals on how to build such a beam).

52. Detector Modeling
Detector (optical) model defines how light of generated event is propagated and detected in MiniBooNE detector
Sources of light: Cerenkov (prompt, directional cone),and scintillation+fluorescence of oil (delayed, isotropic)
Propagation of light: absorption, scattering (Rayleigh and Raman) and reflection at walls, PMT faces, etc.
We have developed 39-parameter “Optical Model”.
Strategy to verify model:
External Measurements: emission, absorption of oil, PMT properties.
Calibration samples: Laser flasks, Michel electrons, NC elastic events.
Validation samples: Cosmic muons (tracker and cubes).

53. Low energy  cross sections
Predictions from NUANCE
- MC which MiniBooNE uses
- open source code
- supported & maintained
by D. Casper (UC Irvine)
- standard inputs
- Smith-Moniz Fermi Gas
- Rein-Sehgal 1
- Bodek-Yang DIS
Imperative is to precisely
predict signal & bkgd rates
for future oscillation experiments
We need data on nuclear targets!
(most past data on H2, D2)
MINOS, NuMI
K2K, NOvA
MiniBooNE, T2K
Super-K atmospheric 

54. Cross-section uncertainties in the analysis
MAQE, elosf %, 2% (stat + bkg only)
QE  norm %
QE  shape function of E
e/ QE  function of E
coh/res ratio
NC 0 norm %
  Nrate 7% BF
EB, pF MeV, 30 MeV
s %
MA1 %
MAN %
DIS  %
Determined from
MiniBooNE
 QE data
MiniBooNE data
Other Experiments
Determined
from other
experiments

55. Energy Calibration Michel electrons from  decay:
We have calibration sources spanning wide range of energies and all event types !
Michel electrons from  decay:
provide E calibration at low energy (52.8 MeV),
good monitor of light transmission, electron PID
12%
E res at
52.8 MeV
0 mass peak: energy scale & resolution
at medium energy (135 MeV), reconstruction
cosmic ray  + tracker + cubes:
energy scale & resolution at high energy
( MeV), cross-checks track reconstruction  e
provides  tracks of
known length → E

56. Are the neutrinos coming from the target?
Geological Survey: Y=24.80,XZ=87.50.

57. Are the neutrinos coming from the target?

58. Are the neutrinos coming from the target?
Measurement of exiting muons from neutrino interaction: Y=24.40, XZ=

59.  CCQE events: Q2 distribution

60. PID cuts efficiency for e CCQE events
“Precuts” +
Log(Le/L)
+ Log(Le/L)
+ invariant mass
cut to rject low energy events near wall is: .not.(R>426 cm .and. Evisible<280)

61. Rejecting “-like” events
log(Le/L)>0 favors electron-like hypothesis
e CCQE
 CCQE MC
Separation is clean at
high energies where
muon-like events are long.
This does not separate e/0 as photon conversions are electron-like.

62. Rejecting “0-like” eventsMC
0 mass cut
log(Le/L) cut
 NC 0
e CCQE

63. 0 mass in 0 momentum bins
0 momentum bins are:
0<P <0.2, 0.2<P <0.3,
0.3<P <0.4, 0.4<P <0.5,
0.5<P <0.6, 0.6<P <0.8,
0.8<P <1.0, 1.0<P <1.2,
1.2<P <1.6,and P >1.6GeV/c2

64. 0 momentum In an analysis of neutral 0 sample from Booster
beam we used this
distribution to tune
MC to data: no need to do it here.

65. Selecting the dirt events
Event pre-selection:
1 subevent
Thits>200, Vhits<600
R<500 cm
log(Le/L)>0.05 (e-like)
Ee <550 MeV
Distance-to-wall <250 cm
m<70 MeV/c2 (not 0-like)
True  energy:

66. Does the dirt sample constrain events in e CCQE sample?
Lets use e CCQE cuts + “dirt” cuts: this is the overlap:
cos e

67. Visible energy of e CCQE events: systematic uncertainty
Visible energy in tank [GeV]
Visible energy in tank [GeV]

68. Visible energy of e CCQE events with dirt cuts
Visible energy in tank [GeV]
Visible energy in tank [GeV]

69. cose and Ee of e CCQE events with dirt cuts

70. We have an indication of data over MC excess below 0. 9 GeV with 1
We have an indication of data over MC excess below 0.9 GeV with 1.4 significance: could it be due to a signal?
Anomaly Mediated Neutrino-Photon Interactions at Finite Baryon Density (arXiv: : Jeffrey A. Harvey, Christopher T. Hill, Richard J. Hill)
CP-Violation 3+2 Model: Maltoni & Schwetz, arXiv:
Extra Dimensions 3+1 Model: Pas, Pakvasa, & Weiler, Phys. Rev. D72 (2005)
Lorentz Violation: Katori, Kostelecky, & Tayloe, Phys. Rev. D74 (2006)
CPT Violation 3+1 Model: Barger, Marfatia, & Whisnant, Phys. Lett. B576 (2003) 303
New Light Gauge Boson: Nelson & Walsh, arXiv: