1

Recent results from the
MINOS experimentDavid A. Petyt, University of Minnesota
for the MINOS Collaboration
RCNN-Tokyo November 2nd 2007

2

Talk structure• Outline of the talk:- The MINOS experiment- Physics goals of MINOS- The NuMI beam and the MINOS detectors- Overview of the oscillation analysis- Analysis improvements for the Summer 2007 result- Oscillation analysis of the 2.5x1020 POT dataset- Future prospects and summary

3

The MINOS experiment• MINOS (Main Injector
Neutrino Oscillation Search)- a long-baseline neutrino
oscillation experiment:- Neutrino beam provided by 120
GeV protons from the Fermilab
Main Injector- A Near detector at Fermilab tomeasure the beam compositionand energy spectrum- A Far detector deep
underground in the Soudan
Mine Minnesota, to search forevidence of oscillations

735 km735 km4

MINOS Physics Goals• Verify νµ→ντ mixing hypothesis
Neutrino mixing
and make a precision (<10%)measurement of the oscillation    νe appearance νe
Ue1Ue2Ue3
ν1
parameters Δm2 and sin22θ
νµ = Uµ1Uµ2Uµ3 ν2• Search for sub-dominant νµ→νe ντ
Uτ1Uτ2Uτ3
ν3
oscillations (not yet seen at thisνμ disappearance
mass-scale)• Search for/rule out exotic
Neutrino masses
phenomena- Sterile neutrinos- Neutrino decay• Atmospheric neutrino and cosmic ray
muon physics

ν3

Δm223

ν2
ν1

The MINOS Collaboration

27 institutions
175 scientists

Argonne • Athens • Benedictine • Brookhaven • Caltech • Cambridge • Campinas
Fermilab • College de France • Harvard • IIT • Indiana
Minnesota-Twin Cities • Minnesota-Duluth • Oxford • Pittsburgh • Rutherford
Sao Paulo • South Carolina • Stanford • Sussex • Texas A&M
Texas-Austin • Tufts • UCL • William & Mary • Wisconsin

5

6

The NuMI beam andthe MINOS detectors

The NuMI facility

7•Design parameters:•120 GeV protons from the Main Injector•Main Injector can accept up to 6 Booster
batches/cycle,•Either 5 or 6 batches for NuMI
•Single turn extraction (10µs)•Beam performance (2007)•Typical intensity: 2.4x1013ppp every
2.4 seconds (~200kW)•Peak intensity: 4.05x1013ppp every
2.2s•Currently in shutdown - goal for
2008-9 running:•Improve beam power by 30-40% by•multi-batch “slip-stacking”•2.2 second cycle time in stacking mode

8

Producing the NuMI beam

• Neutrino beam produced by 120 GeV
protons striking a graphite target:- π and K decays produce a 98.5% pure νµ beam

• Neutrino energy spectrum can be changed bymoving target position relative to first horn:- Most of our running has been in the low energy“LE-10” position, which is optimum formeasuring the oscillation parameters- Some running in higher energy positions for beamtuning and systematics studies

9

The NuMI beamline

Primary proton line
Decay pipe
Target hall

10

The NuMI target
NuMI target with water cooling lines• Target:Target/Baffle carrier
Allows for 2.5 m of target motion
to vary the beam energy• 47 segments of graphite of 20 mm
length and 6.4×15 mm2 crosssection•
0.3 mm spacing between
segments, for a total target lengthof 95.4 cm• Baffle:•protects beamline components
from beam mis-steering• 150 cm long graphite rod with
11mm diameter hole

BaffleTarget11

Focussing horns• Two parabolic focussing horns connected in series.
• Nominal horn current at 200 kA• Produces 3.0 Tesla peak fieldAccelerator performance and analysis datasets

Accelerator shutdown

Many thanks to FNAL Accelerator Division for the high-quality beam during this period!

RUN I 1.27x1020 POT(published in PRL)

Higherenergybeam
running

RUN IIa RUN IIb 1.23x1020 POT ~0.75x1020 POT(NEW DATASET)(Not yetanalysed)This analysis: Run I + Run IIa - 2.497x1020 POT

12The MINOS detectors“Two functionally identical detectors”
Far Detector at Soudan

Near Detector at Fermilab

Veto Shield

Coil

Data taking since ~ September 2001. Installation complete in July 2003.

Plane installation fully completed on Aug 11, 2004

5.4 kton mass, 8×8×30m

1 kton mass 3.8×4.8×15m

484 steel/scintillator planes

282 steel and 153 scintillator planes(x 8 multiplexing)(x 4 multiplexing after plane 120)

VA electronics

Fast QIE electronics
Magnetised steel - B ~1.2T

Multi-pixel (M16,M64) PMT readout
GPS time-stamping to synch FD data to ND/BeamContinuous untriggered readout of whole detector (only during spill for the ND)
Interspersed light injection (LI) for calibration
Software triggering in DAQ PCs (Highly flexible : plane, energy, LI triggers in use)
Spill times from FNAL to FD trigger farm

13

14

NC Eventνe CC Event

3.5m

1.8m

2.3m

•long µ track+ hadronic
activity at vertex• short event, often
diffuse• short, with typical
EM shower profileνµ CC Event
UZ

VZ

Monte Carlo

Event Reconstruction• The signature of νµ CC interactions is the presence of a penetrating muon trackin the detector• The reconstructed neutrino energy is the sum of the track momentum (estimatedfrom range if the muon stops in the detector volume, or by curvature if it exits)
and the calorimetric energy of the reconstructed hadronic showerEν = Eshower+Pµ55%/√E

6% range, 11% curvatureTypical neutrino events
Near Detector

15

Far Detector

Beam

Individual events

Time (μs)• Multiple events recorded per beam spill- separated by timing and spatial information• Much lower rate at FD (~10-5 x ND
rate)

16

Overview of theanalysis method
Brief sketch of the analysis
Analysis improvements relative to the 2006 result
Selecting CC-like events
Comparing Data and MC in the Near Detector
Selecting FD beam-related events

Brief sketch of the analysis

17• The strength of the MINOS experiment lies in the “twodetector approach”- although there are significant uncertainties in the prediction of theabsolute NuMI beam flux and cross-sections, these are common
to interactions in both Near and Far detectors.
- By comparing events in the two detectors, we can significantly
cancel these uncertainties.
- We therefore make full use of the Near detector data to predict theneutrino flux in the Far detector, using our Monte Carlo to makesmall acceptance corrections.

• Our challenge is therefore to select a set of clean andunbiased charged-current events in the two detectors in orderto perform the flux extrapolation and oscillation analysis

Improvements over 2006 analysis

18• The following improvements were made to the analysis with respect
to our 2006 result:- Improved Event reconstruction:- Re-write of track fitter results in fewer track fit failures in ND and FD- Improved event builder results in fewer “split” events in ND and FD- Event selection improvements:- New CC/NC event separation algorithm results in higher CC selection efficiency andmuch lower NC background contamination- Expanded fiducial volume in FD, retains~3% more events- Relaxed 30 GeV neutrino energy cut- Interaction model improvements:- New hadronization and intranuclear rescattering models, provide much better
agreement with worlds data. See C. Andreopoulos and T. Yang presentations at
NuInt07- results in +10% change in the overall hadronic energy scale. Comparable to ourpreviously assumed systematic error- Updated cross-section model based on comparisons with experimental data

Event selection cuts – Near and Far
νµ CC-like events are selected in the following way:

•
1.
2.

Event must contain at least one good reconstructed track
The reconstructed track vertex should be within the fiducial volume of thedetector:––

NEAR: 1m < z < 5m (z measured from the front face of the detector), R< 1m frombeam centre.
FAR: z>20cm from front face, z>1m from rear face, R< 3.7m from centre ofdetector.
–
This volume has been expanded relative to our previous analysis results in 3% more FD events
FAR DETECTOR

NEAR DETECTORνCalorimeter

Spectrometer

Fiducial Volume

3.

The fitted track should have negative charge (selects νµ)4.

Cut on likelihood-based Particle ID parameter which is used to separate CC
and NC events.

19

Selecting charged-current events

20• We separate charged-current events from neutral current background on thebasis of topological characteristics:- A likelihood-based method is used to separate the two samples using, as input
variables, quantites related to the prominence of the reconstructed (muon) track inthe event.
- This method has been improved over the previous analysis by using more
discriminating variables, and by using 2 dimensional PDFs (taking correlations
between variables into account)• Input PDFs used:

PDFs from MC– Track Topology Variables• Track Pulse Height Per Plane• Number of Track-Like Planes• Number of Planes
OUTPUT PID• Goodness of Muon Track Fit
PARAMETER• Reconstructed Track Charge– Event Variables• Reconstructed Kinematics Y distribution ( Y = Shower Energy / Neutrino Energy)• Relative CC/NC Spectrum & CC/NC Priors

21

Near detector Data/MC comparisons:
PID inputs• Good agreement between data and MC

22

Near Detector: PID distributions
0-3 GeV
ALL ENERGIES

NC-like CC-like
3-6 GeVCut at PID>0.85 to separate CClike and NC-like events• Agreement between data and MC is good for all
neutrino energies

Improvements in selection efficiency
NEAR DETECTOR

23

FAR DETECTOR

Much lower NC background
Higher CC efficiency• New PID yields ~2% higher CC selection efficiency and a factor of 2.2 lower NC
background contamination than old PID- NC background rate important as these events “obscure” the oscillation dip at low
reconstructed neutrino energies• Adoption of new PID resulted in a significant (~10%) improvement in oursensitivity to Δm2 and sin22θ
• NC background uncertainty was the leading systematic error in our previous
analysis. With the use of the new PID, this error is significantly reducedNear Detector: Data/MC comparisons
TRACK VERTICESTRACK ANGLES
Beam points
down 3degrees toreachSoudan• Low-level quantities agree well

24

25

Stability of the reconstructed spectrum• Reconstructed energy distributions agree to within statisticaluncertainties (~1-3%)• Beam is very stable and there are no significant intensity-dependent
biases in event reconstruction.
• Run I and RunIIa data were taken with slightly different target
positions (corresponding to a ~3% change in the overall event rate/
POT). They are therefore treated as independent datasets as far as
Near-Far extrapolation is concerned. We also apply a correction factor
to the MC to account for the target position change
Run I spectra by month

Run IIa spectra by month

Reconstructed events/POT

ND Energy spectra - hadron production tuning
LE-10 (z=-10cm)

pME (z=-100cm)

26

pHE (z=-250cm)• We have collected data in 7 different beam configurations:- different target positions and horn current settings• We observe a discrepancy between the ND data and our nominal (FLUKA05) MC
which changes with beam setting- this suggests that the source of this discrepancy is due to beam modelling
uncertainties, rather than cross-section uncertainties.
• We have used this data to tune our MC using a function that varies smoothly withhadronic xF and pT. The tuned MC is in substantially better agreement with data inthe various beam configurations

27

Summary of ND Data/MC agreement• Large sample (~106) of selected events in the ND allows detailed data/
MC checks to be carried out.
• Good agreement observed in low-level quantities, PID inputs and theoutput CC/NC separation parameter. In addition, the reconstructedenergy spectrum is stable over the duration of Run I and Run IIa- these indicate that our detector modelling is satisfactory and that there are no
significant intensity related biases in our reconstruction codes.

• The observed energy spectra show differences between data andMC.
- this is not surprising given the large a priori uncertainties in hadronproduction and neutrino cross-sections- however, by using an extrapolation technique that directly uses the
ND data, we can very significantly reduce the effect of these
uncertainties on our predicted FD spectrum

28

Selecting Far Detector beam events• Far detector beam events are selected on the basis of timing
and topology- The events must be in coincidence with the known times of NuMI
beam spills (within a 50µs window)- The events must point away from FNAL (track angle <50° relative
to beam direction)• In addition, the reconstructed
events must be located within
the fiducial volume of thedetector• These criteria select a very
clean sample of neutrino
events - expected backgroundfrom CR muons < 0.5 events

29

Far Detector Livetime
POT weighted inefficiency - 100-livetime(%)
Run I

Readout problems

Run IIa

Fire alarmat Soudan• FD livetime is >99% (RunI: 98.9%, RunIIa: 99.5%)- intrinsic ~0.1% inefficiency due to calibration runs

• Many thanks to everyone who helped to maintainsuch a high livetime!

30

FD events as a function of time
• Plot shows number of selected FD
events taken in the LE-10 beam
configuration as a function of time
• Good agreement between numberof selected events and protons on
target• Events/POT distributions are flatas a function of time

Run IIa
Run I

FD track vertices
Track X-Y vertex position

Track Z vertex position• Uniform distribution of track vertices- no evidence of background contamination

31

32

Near-Far extrapolationand systematic errors

33

Extrapolating the flux
• We directly use the Near detector data to perform the extrapolation between
Near and Far, using our Monte Carlo to provide necessary corrections due
to energy smearing and acceptance.
• Use our knowledge of pion decay kinematics and the geometry of ourbeamline (extended neutrino source, seen as point-like from the Far Detector)
to predict the Far detector energy distribution from the measured Near
detector distribution

To FD

stiff π+120 GeV ptargetθf

θnsoft π+Decay pipe

ND

ν
ν

• This method is known as the “Beam Matrix” method.
• By making direct use of the ND data, we significantly cancel uncertainties
due to beam modelling and cross-sections, which are common to both Nearand Far detector events

34

The Beam Matrix
Far

Near

• Beam Matrix encapsulates theknowledge of pion 2-body decay
kinematics & geometry.
• Beam Matrix provides a very
good representation of how thenear and far detector spectra
relate to each other.

Reco→True

Reconstructed Eν

Correct for efficiency

Reconstructed Eν

True CC

Selected CC

Correct for purity
Selected CC

Selected CC-like

Steps in the Beam Matrix method

35

True Eν

ND
True EνND→FD Beam Matrix↵↵

True Far Eν

True FD spectrum

True ND spectrum
True Near Eν

True Eν

Reconstructed Eν

Selected CC-like

True CC
True Eν

Apply efficiency, purity

True CC

True→RecoTrue CC

Oscillate

Reconstructed Eν

FD

Cancelling systematic errors

36

Hadron Production Modelchanged by +/- 1 sigma
Resonant Cross Sectionchanged by +/-20%• We have investigated (using MC) the effect of systematic uncertainties on thepredicted FD spectrum. The plots above illustrate uncertainties in beammodelling and neutrino cross-sections- the dashed lines show the magnitude of the systematic effect introduced toour reconstructed energy spectrum (relative to nominal MC)- the red lines show the predicted spectrum in these two cases, when the Beam
Matrix method is used to extrapolate from Near-Far- the true and predicted spectra are very close, indicating that the effect of thesesystematics largely cancel when this method is used.

List of systematic errors studied37• Beam:- Uncertainty in the predicted spectrum after beam tuning (see plot on
previous page)• CC cross-sections:- QEL and RES MA: 15% error, RES-DIS rijk scale factors: 20%• Normalisation:- 4% relative uncertainty due to fiducial mass, POT counting,reconstruction efficiency uncertainties• Energy scales:- 10% absolute shower energy scale: 6% intranuclear rescattering 6%
hadronization 6% absolute calibration- 3% relative shower energy scale- 2% uncertainty on muon range, 5% uncertainty on muon curvature• NC background- 50% uncertainty on NC background rate (from data/MC comparisonsof muon-removed CC events in the Near Detector)

22
Systematic errors on Δm and sin 2θ
• As explained above, the large a priori uncertainties due tobeam and cross-section uncertainties largely cancel in theextrapolation• The main remaining systematic errors are due to the relative
normalisation, absolute shower energy scale and NC
background contamination
Shift in Δm2(10-3 eV2)

Shift insin2(2θ)Near/Far normalization ±4%0.065<0.005Absolute hadronic energy scale ±10%0.075

<0.005

NC contamination ±50%

0.010

0.008

All other systematic uncertainties

0.007<0.005

Total systematic (summed in quadrature)

0.10

0.008

Statistical error (data)

0.17

0.080

Uncertainty

38

39

Cross-checks of the extrapolated spectrum• In addition to the Beam Matrix, we have developed threeother extrapolation methods for comparison:- Data driven methods: Far/Near ratio- Fit based methods: NDFit and 2DFit• The predicted spectra for these methods all agree to within +/- 4% much better than the statistical error on the FD spectrum

40

Oscillation analysis

Effect of selection cuts on
FD data
Cut

Number of Events

Track in fiducial volume847

Data quality cuts

830

Timing cut

828

Beam quality cuts

812

Track quality cut

811

Track charge<=0672

PID parameter>0.85564

Reco Enu<200 GeV

563 (Final analysis sample)

41

Comparison of observed/expected events
Expected
Data/Prediction(Matrix Method;(Matrix Method)
Unoscillated)

Data Sample

FD
Data

νµ CClike All Energies563

738±300.76 (4.4 σ)

νµ CClike (<10 GeV)

310

496±200.62 (6.2 σ)νµ CClike (<5 GeV)

198

350±140.57 (6.5 σ)• Strong energy-dependent deficit seen
- below 10 GeV, a deficit of 6.2σ relative to the no oscillation
prediction is observed, based purely on the total event rate
• The predicted numbers of events include the 4% normalisation
error, which is the dominant contribution to uncertainties on theoverall rate.

42

43

Oscillation fit• Fit to the visible energy spectrum of the 563
selected Far detector CC events to extract the
mixing parameters Δm2 and sin22θ:
nbins

nsyst ∆α2ji=1

j=1 σα2jχ (∆m , sin 2θ, α j , ...) = ∑ 2(ei − oi) + 2oi ln(oi/ei) + ∑
2

2

2

}

}

Statistical error

Systematic errors• Systematic uncertainties (leading systematics areincluded as nuisance parameters in the fit):- 4% overall normalisation- 10% absolute shower energy scale- 50% NC background rate}common to nearand far detectors

44Best-fit energy spectrum• Best-fit oscillation parameters:- Δm2=2.38×10-3 eV2- sin22θ=1.0- χ2/ndf=41.2/34
18 bins x 2 spectra (Run I, Run IIa) - 2• No oscillations: χ2/ndf=139.2/36

45

Allowed region2∆m+0.0020−3
2= 2.38−0.0016 × 10 eV2

sin 2θ = 1.00−0.08

46

2
Fit with unconstrained sin 2θ
• Best-fit parameters:- Δm2=2.26×10-3 eV2- sin22θ=1.07- χ2/ndf=40.9/34• Our allowed regions are drawn using the approximations:- 68% C.L - χ2=χ2min+2.3- 90% C.L - χ2=χ2min+4.61• We have evaluated the effect of the physical boundary on the allowed region
using the unified approach of Feldman and Cousins- preliminary (stat errors only) results indicate that our confidence limits areslightly conservative (the above approximations are slightly over-covering)

47

FD Data/MC comparisons• Neutrinos point 3o up at
the FD! (c.f. page 24 for
the ND)

PID input variables• Agreement between data and oscillated MC very
good

48

49

PID distributions
NEW PID

OLD PID• Agreement between data and oscillated MC verygood

FD Energy, y distributions

χ2 /n.d.f = 30.8/20 = 1.5• Good agreement
between data and bestfit MC for thesekinematic variables

y=Ehad/Eν

50

Comparison with 2006 result

51} Run I+IIa
Run I (2006)} Initial Analysis• Best-fit value changed due to:- statistics (new events due toimproved reco. efficiency
different PID, FD fid volume)- systematic shift in shower
energy (10%) due to new
intranuclear rescattering andhadronization models

52

Future prospects
νµ disappearanceνµ→νe• Significant improvements possible in the measurement of νµ disappearance
parameters with increased exposure.
• Potential to observe sub-dominant νµ→νe transitions, or improve the current
limit on the mixing angle θ13 by a factor of 2-3.

• Neutral current measurements (νµ→νs, τ appearance) will also be possible
with a larger dataset

Selecting NC events in the ND

53• Goal is a NC spectrum measurement in the FD- Sensitive to νµ→νsterile, ν decay signatures• First step of this analysis is a measurement of the NC spectrum in the ND- Use similar techniques to the CC analysis to extrapolate measured flux to FD• Use simple cuts to select NC events with high (93%) efficiency (CC contamination~50%)
NC selection variables• We have developed two methods to obtainclean samples of events for data/MC
comparisons- these are designed to reject events that overlap
in time and space and/or are not wellreconstructed- High multiplicity selection:- Uses timing & topological cuts (selects 860K
ND data events for 1.23e20 pot)
- Low multiplicity selection:- Use only spills with 1 or 2 reconstructed events(selects 10472 events for 1.23e20 pot)

ND Data/MC comparisonsHigh multiplicity

Low multiplicity• MC error band includes contributions from beam, cross-section andenergy scale uncertainties

54

Projected sensitivity to νµ→νs

55• The plot at rightshows the sensitivityof MINOS to thefraction of νµoscillating to νs at theatmospheric neutrino
scale
P(νµ → νs) = fs sin2 2θ sin2(1.27∆m2L/E)

P(νµ → ντ) = (1 − fs) sin2 2θ sin2(1.27∆m2L/E)• At the time of writing, we are in the process of
finalising the analysis, and expect to produce a
result based on the Run I + Run IIa dataset within
the next few months

Summary and conclusions

56• In this talk I have presented the updated accelerator neutrino oscillation resultsfrom a 2.5×1020 pot exposure of the MINOS far detector.
• Our result strongly disfavours no oscillations and is consistent with νµdisappearance with the following parameters (1σ errors shown):
2∆m+0.0020−3
2= 2.38−0.0016 × 10 eV2

sin 2θ = 1.00−0.08• The systematic uncertainties on this measurement are well under control• An updated analysis will be presented next Summer on the full Run I + Run II
dataset (3.25×1020 pot) and will include tests of non-standard νµ disappearance
mechanisms such as neutrino decay and decoherence• Analyses of Neutral Current and electron neutrino data are underway.
- A result on possible νµ→νs oscillations is expected in the next few months• Analysis references:- Phys. Rev. Lett. 97 (2006) 191801 (Run I) (long paper shortly to besubmitted to PRD)
- arXiv:0708.1495: (preliminary Run I + Run IIa result)

57

Back-up slides

58

Neutrino Time of Flight• GPS synchronises two detectors• Know distance
precisely:

betweendetectors- 734,298.6 +/- 0.7 m (~2.5 ms at c)• Measure distribution of event times in two
detectors• Log likelihood fit to time distribution
allowing δt to vary

• MINOS Time of Flight:- 2449223 +/- 84 (stat.) +/- 164 (syst.) ns(99% C.L.)• Nominal Time of Flight:- 2449356 ns (for neutrinos travelling at c)

Far detector events - points
Near detector prediction - solid line

• In terms of velocity:- (v-c)/c = 5.4 +/- 7.5 x 10-5(99% C.L.)- Previous experiment had baselineof ~500 m with timing precisionof ~ns, gave result of:- |v-c|/c < 4 x 10-5 (95% C.L.)

Prospects for higher beam intensity

59• R e c e n t p r o g r e s s o n NuMI beam monitoring display - Feb 22nd 2007
increasing beam intensity
for NuMI from “slip13 ppp
4x10
stacking” studies- slip stacking allows us toinject up to 11 booster
batches in Main Injector

protons/pulse (x1012)

Slip-stacking schematic

Boosterbatches- On Feb 22nd delivered 4.05x1013 protons to
the NuMI target in a single pulse- Regular running in this mode will require more study (+hardware upgrades) but current study is very promisingfor increasing beam intensity

Beam pointing with µ monitors

ME
ME

HE

170/200 kA
Muon
Alcove 1

170/200 kA

HE
Muon
Alcove 2• To keep distortions in the FD spectrum <1%, we require <100µrad missteering of the ν beam from FNAL
• At the muon monitors, a 10 cm shift in the muon beam centroid
corresponds to a 130µrad angular deviation.

60

Cancellation of beam uncertainties
Beam Matrices that correspond toquite different near detector spectra arevery similar (spread in each column
determined primarily by the geometryof the beamline)
NOTE :Red dotted bands are ± 5%.

Method: Use instead of LE010 185 kA Beamtransfer Matrix the LE010 200kA Beamtransfer Matrix
These different matrices correspond to quite
different “beams” as evident from the Near
Detector Spectra.
However, Far Detector Prediction is quite
accurate to within < 5%61

Cancellation of cross-section uncertainties
ND Spectrum

Beam Matrix

ND Flux

FD Spectrum

FD Flux

Cross Section matrices & Beam Matrix almost diagonal=>They Commute!

Their Product is I regardless of their values! (In the limit where theBeam Matrix is diagonal)

62

Effect of MC tuning on the FD prediction
Far Predicted Spectra using the Beam Matrix
and with/without hadron production tuning
Using tuned MC forenergy smearing andacceptancecorrections

Ratio of Far Prediction using the Beam Matrix
and with/without hadron production tuning

Ratio of predicted spectra
with/without tuning

Using nominal MC forenergy smearing andacceptancecorrections• Using the Beam Matrix Method, hadron production tuning does not affect the
Unoscillated prediction (obtained from the ND data) by more than 1-2%.

• However, its use improves the MC (make it more similar to the data) andtherefore uncertainties due to energy smearing-unsmearing and acceptancebecome smaller.

63

Run I/Run IIa spectrum differences

64

65

Contour evolution

MINOS Detector technology• MINOS Near and Far detectors are functionally identical: sharesame detector technology and granularity:
2.54 cm thick magnetised steel plates
4.1x1cm co-extruded scintillator strips (MINOS-developed technology)
orthogonal orientation on alternate planes – U,Voptical fibre readout to multi-anode PMTs
Scintillator strip

Scintillator module

M64 PMT

M16 PMT66

MINOS calibration••

Calibration of ND and FD :– Calibration detector (overall energy scale)– Light Injection system (PMT gain+Linearity)(strip to strip and detector to detector)– Cosmic ray muons
Energy scale calibration:– 3.1 % absolute error in ND– 2.3 % absolute error in FD– 3.8 % relative

67

68

MINOS Calibration Detector• Help understand energy response to reconstruct Eν
Eν = pµ + Ehad
• Measured in a CERN test beam with a “mini-Minos”• operated in both Near and Far configurations• Study e/µ/hadron response of detectorbeam• Test MC simulation of low energy interactions• Provides absolute energy scale for calibration

Single particle energy resolution

Event catching - timing and triggering•

The elements of the timing system are as
follows:– $74 signal from Main Injector – tells kicker
magnet (which extracts protons to NuMI)
that it is in the queue to fire (which itdoes ~220 us later).
– $74 signal sent to clock controller at ND& a spill gate (SGATE) window is opened(in hardware) for 13us around the timeneutrinos hit the ND (with an offset of –1.5us)– SpillServer process at FD informed whenmost recent spill occurred.
– FD trigger farm queries SpillServer
process every second. If a spill signal has
been received and the Spill Trigger isenabled, the DAQ reads out 100us ofpreviously buffered data around thepredicted time that the neutrinos shouldhave hit the FD

69

70

NEUGEN cross-section model
Neutrino-nucleus interactions were generated using the
NEUGEN3 neutrino event generator(H. Gallagher, Nucl.Phys.Proc.Suppl. 112: 188-194, 2002)
Quasi-Elastic: dipole parametrizationof form factors with ma=0.99 GeV/c2(BBBA05 Bradford et al. Nucl.Phys.Proc.Suppl.
159:127-132,2006)
Resonance Production:
Rein-Seghal model for W<1.7 GeV/c2.
(Annals Phys. 133: 79, 1981)
DIS: Bodek-Yang modified LO model.
For W<1.7 GeV tuned to electron and neutrino data in
the resonance / DIS overlap region.
(Bodek-Yang, Nucl. Phys. Proc. Suppl. 139: 113-118, 2005
and H. Gallagher, NuINT05 Proceedings)
Coherent Production:
Rein-Seghal (Nucl. Phys. B 223: 29, 1983)

71

Cross-section changes

model (MODBYRS-4).
OLD

NEW

Daikon: model + parameter• Corresponds
to
~3%
drop
changes.

H. Gallagher
May 4, 2007
Phys. Sim Meeting

OLD

σCC(νμ+N→μ+X)E (10-38 cm2/GeV)

CarrotDaikonCarrotandand
Daikon• Change in cross-section
parameters and total CC
We are now discussing
We are nowondiscussing
cross-section
betweenuncertainties
theuncertainties
on theCarloold(2006)
daikoncross Montesectiondaikoncross section
model
and
the(MODBYRS-4).
current
analysis

H. Gallagher
May 4, 2007
Phys. Sim Meetinginrate modelof CC
events,Daikon:+ parameter
integratedchanges. over LE-10
energy spectrum

NEWblack=daikon
red=carrot

black=daikonEν (GeV)
red=carrot

72

Exotic models - decay/decoherence

Neutrino Decoherence• Decay/Decoherence Disappearance!
"
2
probabilities
are exponentialµ2L
sin 2θ− 2E
1−eP(νµ → νµ) = 1 −functions of energy

2- no “dips” in spectrum ratio• They can mimic oscillation signals,
but there are discrepancies at highenergy (+low E for decoherence)Monte Carlo simulation

Neutrino Decay

2

2

− αL
2E 2

P(νµ → νµ) = (sin θ + cos θeMonte Carlo simulation)

73

PID correlations• DP PID: Old CC/
NC separation
method using 1D
PDFs• AB PID: New CC/
NC separation
method using 2D
PDFs• Overlap between
selected samples ishigh, however new
PID has much
lower rate of misidentified NC
events at low
energies