nova first results

NOvA First Results

JeffHartnellUniversityofSussex

Rencontres de Moriond EW 14thMarch2016

Introduc?on•  Long-baselineappearancemeasurement

•  NuMIbeam•  NOvAdetectors

•  Muonneutrinodisappearance

•  Electronneutrinoappearance

JeffHartnell,MoriondEW2016 2


Long-baseline 𝜈𝜇→𝜈e For fixed L/E = 0.4 km/MeV A more quantitative sketch…

At right: P(𝜈⎺𝜇→ 𝜈⎺e) vs. P(𝜈𝜇→𝜈e) plotted for a single neutrino energy and baseline

Ryan Patterson, Caltech Fermilab JETP, August 6, 2015 4


Long-baseline 𝜈𝜇→𝜈e For fixed L/E = 0.4 km/MeV A more quantitative sketch…

At right: P(𝜈⎺𝜇→ 𝜈⎺e) vs. P(𝜈𝜇→𝜈e) plotted for a single neutrino energy and baseline Measure these probabilities (an example measurement of each shown) Also: Both probabilities ∝ sin2𝜃23



NOvAOverview•  “Conven?onal”beam•  Two-detectorexperiment:

•  Neardetector–  measurebeamcomposi?on

–  energyspectrum

•  Fardetector–  measureoscilla?onsandsearchfornewphysics

Ash River

Ash River

810 km

KeyFeaturesof2ndGenera?onExpt•  Narrowband(off-axis)beam

•  Detectorsop?misedfor– νeflavouriden?fica?on– νeappearancemaximum(L/E)

•  Higherpowerbeam

•  NOvAhasabouttriplethema\ereffectofT2Kandhigherrela?vean?neutrinoxsec



Off-axis

On-axis

NuMI Beam

NOvADetectors



To APD

4 cm ⨯ 6 cm

1560 cm

A NO𝜈A cell NO𝜈A detectors

Fiber pairs from 32 cells

32-pixel APD

Far detector: 14-kton, fine-grained, low-Z, highly-active tracking calorimeter → 344,000 channels

Near detector: 0.3-kton version of the same → 20,000 channels

Extruded PVC cells filled with 11M liters of scintillator

instrumented with 𝜆-shifting fiber and APDs


JeffHartnell,MoriondEW2016 10Ryan Patterson, Caltech Fermilab JETP, August 6, 2015 11


𝜈𝜇 disappearance

(simulated 𝜈𝜇 CC event)

• Identify contained 𝜈𝜇 CC events in each detector • Measure their energies • Extract oscillation information from differences between

the Far and Near energy spectra

NearDetectorNuMuCCSpectrum


5

Length of Primary Muon Track (m)0 5 10 15

)3Ev

ents

(x10

0

5

10

15

20

25

30

Simulated Selected EventsSimulated BackgroundData

POT20 10×ND, 1.66

)ZθPrimary Muon Track cos(0 0.2 0.4 0.6 0.8 1

Even

ts

1

10

210

310

410

510

610


POT20 10×ND, 1.66

FIG. 2. Reconstructed track length (left) and track angle ✓Z relative to the detector longitudinal axis, along the beam direction(right) for the primary muons in selected ⌫µ CC interactions in the ND. The simulated distributions follow the conventions ofFig. 1.

Hadronic Energy (GeV)0 0.5 1 1.5 2 2.5 3

)3Ev

ents

(x10

0

20

40

60

80

100DataData (w/o 14% offset)Simulated Selected EventsSimulated Background

POT20 10×ND, 1.66

FIG. 3. Reconstructed hadronic energy Ehad for selected⌫µ CC interactions in the ND, both with (black circles) andwithout (gray squares) the 14% o↵set described in the text.The simulated distributions follow the conventions of Fig. 1.

Figure 2 shows the reconstructed muon track param-eters for ⌫µ CC events in the ND. Figure 3 shows theEhad distribution both with and without the 14% dif-ference in Ehad calibration scale between data and sim-ulation. A corresponding ±14% uncertainty is assessedon the hadronic energy scale, and is included in all ofthe uncertainty bands shown. Figure 4 shows the finalE⌫ distribution. The energy resolution for reconstructed⌫µ CC events is estimated from simulation to be 7%.

The prediction for the FD neutrino energy spectrumis based on the observed ND neutrino energy spectrum,with corrections for acceptance and flux di↵erences de-rived from simulation. First, the small NC background,estimated from simulation, is subtracted from the NDdata spectrum. The resulting background-subtractedspectrum is then converted into a true neutrino energy

Reconstructed Neutrino Energy (GeV)0 1 2 3 4 5

)3Ev

ents

(x10

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100


POT20 10×ND, 1.66

FIG. 4. Reconstructed neutrino energy E⌫ for selected ⌫µ CCinteractions in the ND. The simulated distributions follow theconventions of Fig. 1.

spectrum via a mapping derived from simulation. Thistrue neutrino energy spectrum is then used to constructa spectrum in the FD by multiplying it by the energy-dependent ratio of FD-to-ND selected events from sim-ulation. Oscillation probabilities for a given set of os-cillation parameters are then applied, by energy bin, tothe predicted true FD energy spectrum, which is thenmapped to a reconstructed neutrino energy spectrum us-ing FD simulation. The extrapolated ⌫µ CC energy spec-trum is then combined with beam-induced backgrounds(NC, ⌫e CC, and ⌫⌧ CC) predicted from simulation, andthe background spectrum measured using events selectedfrom outside of the beam spill window.

Systematic uncertainties in the calibration, flux esti-mate, cross sections, hadronization modeling, particle-transport modeling and exposure di↵erences between thetwo detectors are assessed by varying these aspects of the

MC scaled up by 7.2% Shape only systematics

JeffHartnell,MoriondEW2016 16Evan Niner I Results from NOvA 02/11/16

νμ Spectrum

• 211.8 ± 12.5 (syst.) events predicted in the absence of oscillations.

• 33 candidate events between 0 and 5 GeV observed.

12

Reconstructed Neutrino Energy (GeV)0 1 2 3 4 5

Even

ts /

0.25

GeV

0

10

20

30

40

50 DataUnoscillated predictionBest fit prediction (no systs)

syst. rangeσExpected 1-Best fit prediction (systs)Backgrounds

Normal Hierarchy POT-equiv.2010×2.74

=19.0/16dof/N2χBest fit

FarDetector

νμDisappearanceResults


Best Fit Oscillation Parameters

13

23θ2sin0.3 0.4 0.5 0.6 0.7

)2 e

V-3

(10

322m

∆

2.0

2.5

3.0

3.5 Normal Hierarchy, 90% CLAνNO

T2K 2014MINOS 2014

arXiv:1601.05037

�m232 =

�2.52+0.20

�0.18

�⇥ 10�3eV2 �m2

32 = (�2.52± 0.19)⇥ 10�3eV2

sin2 (✓23) = [0.38, 0.65] sin2 (✓23) = [0.37, 0.64]

Normal Hierarchy Inverted Hierarchy

(68% CL) (68% CL)Degenerate best fit points at 0.43 and 0.60 Degenerate best fit points at 0.44 and 0.59Evan Niner I Results from NOvA 02/11/16

Best Fit Oscillation Parameters

13

23θ2sin0.3 0.4 0.5 0.6 0.7

)2 e

V-3

(10

322m

∆

2.0

2.5

3.0

3.5 Normal Hierarchy, 90% CLAνNO

T2K 2014MINOS 2014

arXiv:1601.05037

�m232 =

�2.52+0.20

�0.18

�⇥ 10�3eV2 �m2

32 = (�2.52± 0.19)⇥ 10�3eV2

sin2 (✓23) = [0.38, 0.65] sin2 (✓23) = [0.37, 0.64]

Normal Hierarchy Inverted Hierarchy

(68% CL) (68% CL)Degenerate best fit points at 0.43 and 0.60 Degenerate best fit points at 0.44 and 0.59


𝜈e appearance

(simulated 𝜈e CC event)

• Identify contained 𝜈e CC candidates in each detector • Use Near Det. candidates to predict beam backgrounds

in the Far Detector • Interpret any Far Det. excess over predicted backgrounds

as 𝜈e appearance

νeSelec?on


νe Identification• Likelihood Identifier (LID)

- Compare longitudinal and transverse dE/dx in leading shower to template histograms for e/p/n/μ/π±/π0/γ.

- Build neural net from these inputs and reconstructed quantities.

• Library Event Matching (LEM)- Compares input event to simulated

event library.- Properties from most similar events

fed into decision tree.

• 62% event overlap between selectors. • LID chosen before unblinding as

primary selector.

15

νeAppearance


νe Appearance Analysis Results• LID observed 6 events on

a background prediction of 0.99±0.11(syst), 3.3σ excess.

• LEM observed 11 events on a background of 1.07±0.14(syst), 5.3σ excess.

• All LID events in LEM set.

• 7.8% probability of this overlap configuration or one less likely.

17


Evan Niner I Results from NOvA 02/11/16

νe Appearance Analysis Results

19

0 0.1 0.2 0.3 0.4 0.5

CPδCPδ

13θ22sin

0

2π

π

2π3

π2

2π

π

2π3

π2 POT equiv.2010× 2.74LID = 0.5023θ2sin

A Preliminary

νNO

Best fit68% C.L.90% C.L.Reactor 68% C.L.

Normal hierarchy

Inverted hierarchy

Normal

2mΔ

221mΔ

Inverted

eν µν τν

Global bestfit from reactor experiments

LIDSelector


νe Appearance Analysis Results

20

0 0.1 0.2 0.3 0.4 0.5

CPδCPδ

13θ22sin

0

2π

π

2π3

π2

2π

π

2π3

π2 POT equiv.2010× 2.74LID = 0.5023θ2sin

A Preliminary

νNO

Best fit68% C.L.90% C.L.Reactor 68% C.L.

Normal hierarchy

Inverted hierarchy

Normal

2mΔ

221mΔ

Inverted

eν µν τν

Global bestfit from reactor experiments

0 0.1 0.2 0.3 0.4 0.5

CPδCPδ

13θ22sin

0

2π

π

2π3

π2

2π

π

2π3

π2 POT equiv.2010× 2.74LEM = 0.5023θ2sin

A Preliminary

νNONormal hierarchy

Inverted hierarchy

LEMSelector

ResultswithReactorConstraint



Significance with Reactor Constraint

• Apply global reactor constraint- sin2θ13=0.086±0.05

• Marginalize over θ23.• Both selectors weakly

prefer normal mass hierarchy and π<δcp<2π.

• This preference is consistent with T2K (arXiv:1502.01550)

21

CPδ

Sign

ifican

ce

0 /2π π /2π3 π20

σ1

σ2

σ3

σ4

σ5

90%

POT equiv.2010×2.74

NH LID NH LEMIH LID IH LEM

arXiv:1601.05022


Significance with Reactor Constraint

• Apply global reactor constraint- sin2θ13=0.086±0.05

• Marginalize over θ23.• Both selectors weakly

prefer normal mass hierarchy and π<δcp<2π.

• This preference is consistent with T2K (arXiv:1502.01550)

21

CPδ

Sign

ifican

ce

0 /2π π /2π3 π20

σ1

σ2

σ3

σ4

σ5

90%

POT equiv.2010×2.74

NH LID NH LEMIH LID IH LEM

arXiv:1601.05022

Conclusions•  FirstNOvAoscilla?onresultswith7.6%ofplannedexposure

•  νμdisappearanceconsistentw/MINOS&T2K•  νeappearanceresulthintsatnormalhierarchyandπ<δCP<2π,consistentwithT2K

•  Cross-sec?onstudiesinprogress,νeCCandcoherentπ0resultsshownatNuINT

•  Planning2ndresultwithdoublethesta?s?csforthesummer

•  Staytuned!JeffHartnell,MoriondEW2016 27

Backupslides



Relation of Oscillation Parameters in NOvA

25

inverted%hierarchy

normal%hierarchy

Θ23%<%45 o

Θ23%>%45 o

%

Normal Inverted

eν µν τν

2mΔ

221mΔ


νe Appearance Analysis Strategy

• FD background prediction extrapolated from ND - ND selects ~7% more background

in data relative to simulation. • Combination of containment,

topology and event classifier achieve cosmic rejection factor >108. Effective FD fidicual volume of 10 kT.

• “Cut and count” analysis between 1.5 and 2.7 GeV in FD for the primary selector.

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Calorimetric Energy (GeV)0 1 2 3 4 5

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500A PreliminaryνNOLID

ND Data

(Flux + stat. uncert.)Total MC

eνMC Beam

MC NC

CCµνMC

LID0.0 0.5 1.0 1.5

PO

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A PreliminaryνNOND Data eνMC Beam

(Flux + stat. uncert.)Total MC MC NC

CCµνMC

ND energy spectrum with LID>0.95


(1) Estimate the underlying true energy distribution of selected ND events(2) Multiply by expected Far/Near event ratio and !"→!" oscillation probability

as a function of true energy(3) Convert FD true energy distribution into predicted FD reco energy distributionSystematic uncertainties assessed by varying all MC-based steps



Hadronic Energy (GeV)0 0.5 1 1.5 2 2.5 3

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ents

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100DataData (w/o 14% offset)Simulated Selected EventsSimulated Background

POT20 10×ND, 1.66

Length of Primary Muon Track (m)0 5 10 15

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POT20 10×ND, 1.66

E⌫ = Eµ + Ehadrons

• Muon variables in agreement• Best fit to hadronic energy prefers 14% increase in data


• Correct%for%attenuation%in%each%cell%using%throughGgoing%cosmic%muons%(right)%

• Set%absolute%energy%scale%using%stopping%muons%in%data%and%tuned%Monte%Carlo%(below)

calib

ratio

n w

indo

w

Far Detector Data

calib

ratio

n w

indo

w

JeffHartnell,MoriondEW2016 34[G. Feldman]

NOvAFarDetector

Total mass of 14 ktons

An admirer

TASD: Totally Active Scintillator Design Longitudinal sampling is ~0.15 X0, which gives: -- excellent µ-e separation -- π0 rejection capability

Full-size Modules

JeffHartnell,MoriondEW2016 35[L. Corwin]


Very cool time lapse video: http://www.youtube.com/watch?v=gFpK00WJl90&sns=tw

nova first results

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