Daya Bay 原子炉ニュートリノ実験における反電子ニュートリノ消失の精密測定中島康博

ローレンス・バークレー国立研究所
2013年10月8日
京都大学

1Outline• Introduction• Daya Bay experiment• Current data sets
• Spectrum analysis• Challenges andimprovements• Oscillation parameter

extraction• Summary2

Neutrino Mixing• Neutrino flavor (weak) eigenstates and mass eigenstates are mixed
Weak eigenstate(α = e, μ, τ)|⌫↵ i =

Xi

U↵i |⌫i i

Mass eigenstate(i = 1, 2, 3)

MNS mixing matrix• Neutrinos change their flavor as they travel (neutrino oscillation)• Natural interferometer to explore fundamental nature of neutrinos
✓
◆
2
2
2
2 L
m
Two neutrino case: P(⌫↵ ! ⌫ ) = | h⌫ |⌫(t)i | = sin 2✓ sin
4E

KamLAND

Amplitude

Frequencyθ: mixing angle
2
Δm : mass squared diﬀerenceL: the distance traveledE: the energy of neutrino3

Neutrino Mixing
All the three angles are finally observed! c ⌘ cos ✓ and s ⌘ sin ✓
ij
ij
ij
ij
1
0
1
0
1 0
c12 s12 0100c13
0 s13 e iA ⇥ @ s12 c12 0 A
010
U = @ 0 c23 s23 A ⇥ @00 1
0s23 c23s13 e i
0
c13
≈ 45o

θ23
Atmospheric ν
Accelerator ν

θ13

~ 9o

First >5σ observation
at Daya Bay (2012)θ12 ≈ 35o
Solar νLong-Baseline
Reactor ν• Open questions:• Is there CP-violation in neutrino sector?
• What is mass hierarchy?
• Are there any other type of neutrinos?

Precise measurement of mixing angle
is a key to answer those questions.
4Reactor Antineutrinos• Most powerful man-made sourceof antineutrinos, and it’s free
• Nuclear fission release:• 6 antineutrinos/fission• Typically ~1020 fissions/second• Detected through inverse beta

decay
• Broad spectrum with meanenergy of ~4 MeV

5Reactor Neutrino Oscillation
2P(⌫ e ! ⌫ e ) =1

sin 2✓13 sin

2

2
mee
'

✓

2
mee

L
4E

2
m32
'

◆

2

4

cos ✓13 sin 2✓12 sin

2

2
m31

✓

2
m21

L
4E

◆

Short Baseline Reactor Neutrino Oscillation

KamLAND

Daya BayFar SiteP⌫¯e !⌫¯e

0.8

θ13

0.2

2

| mee |

sin22θ13

1

θ12

0.6
0.4

1

Survival probability

KamLAND

1

Survival probability at 1.6 km

0.95
2

sin 2✓13

0.95
Assuming cont.
⌫¯e energy with.
peak at 4 MeV

θ12+θ13
10

Δm2ee

0.9

L [km]
1

0.9

0

100

0.5

0.85

1

1.5

2

2

2.5

3

4
6
Neutrino energy (MeV)

8✓13 revealed by deficit of reactor antineutrinos at ⇠ 2 km

2Characteristic
deficit
at
~2
km
due
to
θ
and
Δm
13
ee
Mixing angle ✓ governs overall size of ⌫¯ deficit
E↵ective mass squared di↵erence | m | determines deficit dependence on L/EFirst establishedby Daya Bay (2012)
Long Baseline
Short Baseline
✓
◆
✓
◆
L
L
P
=1
sin 2✓ sinmsin 2✓ cos 2✓ sinm
Now moving
4E towards precision measurement!
4E

1

13

2
ee

2

⌫¯e !⌫¯e

2

13

2

2
ee

e

2

2

12

2

4

L
sin ( mee 4E
)⌘

13

2

2

2
21

2

2

L
cos ✓12 sin ( m31 4E)

6Complementarity
ncertainty

ure improved measurements ofwill be important to extract
rmation about other oscillation
T2K
Preliminary
ameters (including δCP) inlongline experiments

T2K Preliminary

A T2K combined νe+νμ analysiss underway

these are 1D contours for various
values of δCP, not 2D contours

sin22θ13 results from reactor experiments(Dominated by Daya Bay)

M. Wilking @EPS-HEP2013

2

Precise measurement of sin22θ13 is an essential ingredient
for resolving CP violation and mass hierarchy7

Daya Bay Experiment8

Daya Bay Nuclear
Power Station~55 kmHong Kong
International Airport

9Daya Bay:A Powerful Neutrino Source at an Ideal Location
Mountains shield detectors
from cosmic ray backgrounds

Entrance to Daya Bay
experiment tunnels
10Daya Bay Collaboration

Asia&(21)&Beijing*Normal*Univ.,*CGNPG,*CIAE,*Dongguan*Polytechnic,*ECUST,*IHEP,*
Nanjing*Univ.,*Nankai*Univ.,*NCEPU,*Shandong*Univ.,*Shanghai*Jiao*Tong*
North&America&(17)&Univ.,*Shenzhen*Univ.,*Tsinghua*Univ.,*USTC,*Xian*Jiaotong*Univ.,*
Brookhaven*Natl*Lab,*CalTech,*Illinois*Ins7tute*of*Technology,*Iowa*
Zhongshan*Univ.,*
State,*Lawrence*Berkeley*Natl*Lab,*Princeton,*Rensselaer*Polytechnic,*
Chinese*Univ.*of*Hong*Kong,*Univ.*of*Hong*Kong,*
Siena*College,*UC*Berkeley,*UCLA,*Univ.*of*Cincinna7,*Univ.*of*Houston,*
Na7onal*Chiao*Tung*Univ.,*Na7onal*Taiwan*Univ.,*Na7onal*United*Univ.*
UIUC,*Univ.*of*Wisconsin,*Virginia*Tech,*William*&*Mary,*Yale*

Europe&(2)&Charles*University,*JINR*Dubna*~230 collaborators from 40 institutions
11

Strategy for Precise Measurement
Relative measurementwith functionallyidentical detectors
Most of uncertainty
from detector response
and absolute flux cancel
Far/Near νe Ratio

Detector Target Mass

Near detector(s)constrain flux

Distances fromreactorFar detector(s)measure oscillation

Oscillation deficit

Detector efficiency
12

Experiment Layout
Far(hall(measures(
oscilla=on(
Far Hall (EH3)
Ling Ao nearHall (EH2)

TunnelWater
Hall

Two(near(halls(
constrain(reactor(ﬂux(

Construction
tunnelLS
Hall

Ling Ao IIreactors

Ling Aoreactors

Entrance

Daya Bay Near
Hall (EH1)m!
8/23/13&

Daya Bay
reactors

Spectral&Measurement&of&An7neutrino&Oscilla7on&at&Daya&Bay&

Reactor(power(
6(×(2.9(GWth(10

13

Daya Bay Advantages
Ideal baseline• Detector locations optimized to known parameter space of Δm2ee• Better sensitivity to both θ13 and Δm2ee
Daya$Bay
RENO
Double$Chooz

Stronger, bigger, and deeper
!

!

!

!

Double!Chooz!
RENO !
!
Daya!Bay!
!

!Reactor![GWth]!!!8.6!
!16.5!
!17.4!

!Target![tons] !

!
!
!!!16!(2!×!8)!
!
!
!!!32!(2!×!16) !
!
!
!160!(8!×!20) !
Large!Signal!

!Depth![m.w.e]!
!300,!120!(far,!near)!
!450,!120!
!860,!250!!
Low!Background!
14

Daya Bay Detector

15

Detection Method
Antineutrinos are detected via
inverse beta decay reaction~ 30 µsec
w/ 0.1% Gd

Edelayed ~ 8 MeV
Ee+ ~ Eν - 0.8 MeV

Prompt + Delayed coincidence• Prompt positron: carries antineutrino energy• Delayed neutron capture: efficiently tag
antineutrino signal
16

Antineutrino Detector• 8 functionally identical detectors

Calibration
system• Three-zone cylindrical modules:
Zone

Mass

LiquidPurpose20 t

Gd-dopedliquidscintillator

Antineutrino
targetOuter
acrylic
vessel22 t

Liquidscintillator

Gamma
catcher (fromtarget zone)

Liquid Scint.

Stainlesssteel vessel

40 t

Mineral Oil

Radiation
shieldingMineral oil

Inner
acrylic
vesselStainless
Steel
Vessel (SSV)

192 8-inch
PMTs
20-t Gd-LS

5m• Reflectors at top/bottom of cylinder

are used to increase light yield.

5m
17

Calibration System• Three Automated Calibration Units(ACUs) per detector.

• Deploy sources along the z-axis• Three sources + LED in each ACU,

on a turn table.

R=1.7725 m R=0

R=1.35m• 68Ge (γ, 2 x 0.511 MeV)
• 60Co (γ, 2.506 MeV)
• 241Am-13C (n, 8MeV)• LED for timing and gain calibration• Temporary special calibration sources:• γ: 137Cs(0.622 MeV), 54Mn(0.835 MeV),
40K (1.461 MeV)

• n: 241Am-9Be, 239Pu-13C
18

Muon Tagging System• 2.5 meter thick two-

section water shield• Cherenkov detector
to tag cosmic raymuons.
• Shield for neutrons
and gammas fromsurrounding materials.
• RPC• Covers water pool toprovide further muon
tagging.
19

Data Set

20

Data sets

1.0

Installation of AD 7+8,
Special Calibration Runs

Daya Bay Near Hall

0.8

Two detector comparison

0.6[1202.6181]

0.4• 90 days of data, Daya Bay near only
• NIM A 685 (2012), 78-970[1203:1669]• 55 days of data, 6 ADs near+far• PRL 108 (2012), 171803

Improved oscillation analysis [1210.6327]• 139 days of data, 6 ADs near+far• CP C 37 (2013), 011001

Data Taking Fraction

First oscillation analysis

0.2

1.0

Ling Ao Near Hall

0.8
0.6
0.4
0.2
0
1.0

Far Hall

0.8
0.6

Spectral Analysis• 217 days, complete 6 AD period• 55% more statistics than CPC result

0.4
0.2
0

0

200
DAQ

400
600
Days since August 11 2011
Physics

This Analysis

4/2

21

Antineutrino Selection① Reject'spontaneous'PMT'light'emission'(“ﬂashers")'② Prompt'positron:''
0.7'MeV'<'Ep'<'12'MeV'③ Delayed'neutron:'
6.0'MeV'<'Ed'<'12'MeV'④ Neutron'capture'Mme:'
1'μs'<'t'<'200'μs'⑤ Muon'veto:'• Water'pool'muon'(>12'hit'PMTs):'
Reject'[T2μs;'600μs]'• AD'muon'(>3000'photoelectrons):'
Reject'[T2'μs;'1400μs]'• AD'shower'muon'(>3×105'p.e.):'Reject'[T2'μs;'0.4s]'⑥ MulMplicity:'• No'addiMonal'promptTlike'signal'
400μs'before'delayed'neutron'• No'addiMonal'delayedTlike'signal'
200μs'aaer'delayed'neutron

22

Antineutrino Rate vs. Time
Detected rate strongly correlated with reactor flux expectations
900
800

Daya Bay Near Hall

700
600

IBD Rate (/day/AD)

500
400
800

Data
No Oscillation
Best Fit• Absolute normalization

Ling Ao Near Hall

determined by fit to data

700
600
500

• Normalization within a

400
110
100
90
80
70
60
50
40

Dec
2011

few percent of
expectations

Far Hall

Jan
2012

Feb
2012

Mar
2012

Apr
2012

Run Time

May
2012

Jun
2012

Jul
2012

23

Signal and Background Summary
IBD candidates
DAQ live time (day)Efficiency
Accidentals (/day/AD)*

AD1

Near Halls
AD2

AD3

10129010251992912

191.001

AD4

Far Hall
AD5

AD6

13964

13894

13731

189.645189.779

0.79570.79270.82820.95770.95680.95669.54±0.03

9.36±0.03

7.44±0.02

2.96±0.01

2.92±0.01

2.87±0.01

Fast neutron (/day/AD)*0.92±0.46

0.62±0.31

0.04±0.02

8He/9Li (/day/AD)*2.40±0.86

1.20±0.63

0.22±0.06

0.26±0.12

Am-C corr. (/day/AD)*13C(α, n)16O (/day/AD)*0.08±0.04

0.07±0.04

0.05±0.03

0.04±0.02

0.04±0.02

0.04±0.02

IBD rate (/day/AD)*653.30± 2.31

664.15± 2.33581.97± 2.0773.31± 0.6673.03± 0.6672.20± 0.66* Corrected for the efficiency of the muon veto and multiplicity cutsCollected more than 300k antineutrino interactions• Consistent rates for side-by-side detectors• Uncertainties still dominated by statistics
24

Oscillation Analysis

25

Initial results

Ndetected/Nexpected)

Based)on)55)days)of)data)with)6)ADs,)discovered)disappearance)of)reactor)νe)at)
short)baseline)in)March)2012.!!!![PRL)108,)171803])!

sin22θ13)>)0)

Obtained)the)most)precise)value)of)θ13)in)Jun.)2012:!
)))))))))))))))))))))))))))))))))sin22θ13)=)0.089)±)0.010)±)0.005)))[CPC)37,)011001])!
26

Rate Only Analysis
Far$Site$with$oscilla/on$

Near$Sites$
give$normaliza/on$

Previously+reported+
Integrate$
all$energies$

R Emax2
Nfar
Nprotons,far 1/L2far ✏far Emin Pee (E , Lfar ; ✓13 , mee ) (E ) (E )dE=
R2 ) (E ) (E )dE
Nnear
Nprotons,near 1/L2near ✏near Emax Pee (E , Lnear ; ✓13 , mee
Emin

Advantage: Fewer systematic uncertainties
Disadvantages: Less sensitive. Unable to constrain Δm2ee

27

Rate + Shape Analysis
Far Sitewith oscillation

Near Sites
give normalization

dNfar
dE
dNneardE

Latest method
Compareeach energy

θ13

2
Nprotons,far 1/L2far ✏far Pee (E , Lfar ; ✓13 , mee) (E ) (E )=2 ) (E ) (E )Nprotons,near 1/L2near ✏near Pee (E , Lnear ; ✓13 , mee

Advantages: Gain sensitivity from energy dependence. Constrain Δm2ee.
Disadvantages: Require detailed understanding of detector response28Challenges for the spectrum
shape analysis• Understanding of background rate and shape• Understanding of the detector response• Energy resolution• Energy scale• Effect of inactive volume (acrylic vessel)

29

Challenges for the spectrum
shape analysis• Understanding Background rate and shape• Understanding of the detector response• Energy resolution• Energy scale• Effect of inactive volume (acrylic vessel)

30

Understanding Background
Rate and ShapeIBD candidates
DAQ live time (day)Efficiency
Accidentals (/day/AD)*

AD1

Near Halls
AD2

AD3

10129010251992912

191.001

AD4

Far Hall
AD5

AD6

13964

13894

13731

189.645189.779

0.79570.79270.82820.95770.95680.95669.54±0.03

9.36±0.03

7.44±0.02

2.96±0.01

2.92±0.01

2.87±0.01

Fast neutron (/day/AD)*0.92±0.46

0.62±0.31

0.04±0.02

8He/9Li (/day/AD)*2.40±0.86

1.20±0.63

0.22±0.06

0.26±0.12

Am-C corr. (/day/AD)*13C(α, n)16O (/day/AD)*0.08±0.04

0.07±0.04

0.05±0.03

0.04±0.02

0.04±0.02

0.04±0.02

IBD rate (/day/AD)*653.30± 2.31

664.15± 2.33581.97± 2.0773.31± 0.6673.03± 0.6672.20± 0.66

Two worst contributors tobackground uncertainty at the far hall
31

8He/9Li Backgrounds

Directory measured by fitting
the distribution of IBD
candidates vs. time since muon

9Li/8He(= 178 ms, Q = 13. 6 MeV= 119 ms, Q = 10.6 MeV

9Li: τ
½
8He: τ
½

uncorrelated(• Generated by cosmic rays
• Long-lived• Mimic antineutrino signal

Analysis muon veto cuts
control B/S to ~0.3±0.1%
328He/9Li Backgrounds• Simulated 8He/9Li spectra including

neutron and alpha contributions

Neutrons)from)9Li)decay)(simula5on)))• Benchmarked with external data
• Uncertainty in shape is conservatively

estimated by varying 9Li/(9Li+8He)
ratio and detector response model

Neutrons)from)9Li)decay))(data))(from)Nucl.)Phys.)A510,)2)1990:189A208)))33

241Am-13C Background

Subtle background fromour calibration source• 241Am-13C source produces ~0.75 Hz

Single n-like z distribution in physics run
241Am-13C n-Fe captures(230±40/day/AD)

neutron via 13C(α,n)16O• Neutron interact with steel toproduce fake prompt-delayed pairbottomReconstructed z (m) top• Background rate expected to besmall: 0.2-0.3/day/module (MC)• Yet, one of the largest source ofsystematic uncertainty frombackgrounds

34241Am-13C BackgroundA special x80 stronger 241Am-13C
source placed on the AD

Single n-like

Correlated prompt spectrum

Zoom In

Used special strong source data tobenchmark and correct MC simulation

Estimation for physics data:

Rate: 0.26/day/module (45% uncertainty)
Spectrum: exponential (15% uncertainty)
Factor 2 reduced from the previous analysis

Removed 2 of 3 sources in far detectors
to reduce future backgrounds.
35

Challenges for the spectrum
shape analysis• Understanding Background rate and shape• Understanding of the detector response• Energy resolution• Energy scale• Effect of inactive volume (acrylic vessel)

36Understanding of Detector Response
Energy Losses in Acrylic
Acrylic vessels non-scintillating
Induce shape distortion
Correction from MC

Particle
Energy Etrue

Two major sourcesof non-linearity.
Difficult to decouple !

Energy Depositedin Scintillator Edep

1: Scintillator Response
Energy Converted
to Visible Light Evis

Energy Resolution
Light production
Light collection
PMT/electronics response

Quenching effects
Cherenkov radiation

2: Readout Electronics
Reconstructed
Energy Erec

Charge collection efficiency
decreases with visible light37

Acrylic Vessel / Energy Resolution
Energy loss in the acrylic
vessel distorts spectrum

Energy resolution

Simula'on*
IBD$in$target$

IBD$in$acrylic$$$$(~1.3%)$

Modeled using
MC simulation

Contribu)ons+from:+• a+:+Spacial/temp.+resolu)on+(E)+• b+:+Photon+sta)s)cs+(E)+• c+:+Dark+noise+(const:)+

Calibrated primarily using monoenergetic gamma sources38

Constraining Non-Linearity Parameters
Boron Beta-Decay Spectrum

Special Calibration Source
Regular Calibration Source
Singles Spectrum

1.04
1.02
1

Events / 0.25 MeV

Reconstructed / Predicted Energy

Gamma Sources

54

Mn 40
n-H 208
137
K
Tl
Cs

0.98

12

n- C

16

O*

60

n-Gd

n-56Fe2

Co

68

Ge

Data
Prediction
12
B component
12
N component

1000

500

n-56Fe1

0.96
0

1

2

3

4

5

6

7

8

9

10

Reconstructed Energy [MeV]

0
0

2

4

6

8

10

12

14

16

Reconstructed Energy [MeV]

Full$detector$calibra.on$data$

1. Monoenerge)c+gamma+lines+from+various+sources+• Radioac)ve+calibra)on+sources,+employed+regularly:+68Ge,+60Co,+241AmC13C++++++and+during+special+calibra)on+periods:+137Cs,+54Mn,+40K,+241AmC9Be,+PuC13C+• Singles+and+correlated+spectra+in+regular+physics+runs+(40K,+208Tl,+n+capture+on+H)+

2. Con)nuous+spectrum+from+12B+produced+by+muon+spalla)on+inside+the+scin)llator+$

Standalone$measurements$• Scin)llator+quenching+measurements+using+neutron+beams+and+Compton+eC+• +Calibra)on+of+readout+electronics+with+ﬂash+ADC+
39

Final Positron Energy NonLinearity response
Positron Energy Response Model

Reconstructed / True Energy

Final1.05Positron Energy Non-Linearity Response
1

0.95

0.9

Nominal Model + 68% CL

0

1

2

3

4

5

6

7

8

9

10

True Positron Energy [MeV]Several validated models⌅

Constructed based on di↵erent parameterizations/weighting of data constraints⌅ All models in good agreement with detector calibration data
⌅ Resulting positron non-linearity curves consistent within ⇠ 1.5% uncertainty

Used combination
modelsto conservatively
estimate
uncertainty
Combination ofof5 5models
to conservatively
estimate
uncertainty⌅

Models selected so that1

Correlations are minimized

40

Relative Energy Scale

Crucial ingredient: Consistent energy response for all ADs
Careful calibration with in-situ data and calibration sources:
A"er%calibra+on,%achieve%energy%response%that%is%stable'to'~0.1%'in%all%detectors,%%with%• Energy response stable to 0.1% in all detectors
a%total'rela/ve'uncertainty'of'0.35%'between%detectors.%%%A"er%calibra+on,%achieve%energy%response%that%is%stable'to'~0.1%'in%all%detectors,%%with%
Spalla+on%nGd%capture%peak%vs.%•a%total'rela/ve'uncertainty'of'0.35%'between%detectors.%%%Total+me%(a"er%all%calibra+on)%
relative uncertainty of 0.35% between detectors
Spalla+on%nGd%capture%peak%vs.%+me%(a"er%all%calibra+on)%

Rela+ve%energy%peaks%in%all%
detectors%(a"er%calibra+on)%
EH1 AD1

0.6
0.4

Erec Asymmetry w.r.t. Mean Peak Energy (%)

Erec Asymmetry w.r.t. Mean Peak Energy (%)

Rela+ve%energy%peaks%in%all%
detectors%(a"er%calibra+on)%

EH1 AD2
0.6

EH2 AD1

0.4

EH3 AD1
EH1 AD1
EH3 AD2
EH1 AD2
EH3 AD3
EH2 AD1

0.2

GdLS
Spallation
EH3 AD1

0.2

0

-0.2

GdLS
Alphas
EH3
AD2
0

GdLS
Singles
EH3
AD3

-0.4

ACUA
Center
GdLS
Spallation-0.2

GdLS Alphas

-0.6

0-0.4

1

2

3

4

5

GdLS Singles
6

7

8
9
Erec (MeV)ACUA Center
-0.6
0

1

2

3

4

5

6

7

8
9
Erec (MeV)

Yet, the largest source of systematic uncertainty for Δm2ee
41

Results

42

⇤ ⇥2

Detected / Expected Events

Rate only analysis
1.04
1.02

120
100

1

Ling Ao

0.98

80

Daya Bay60

0.96

Far Hall*

0.94

40

0.92

0.88

20

*AD 4+6 data points are displacedby -50m and 50m for visual clarity

0.90
0

0.2

0.4

0.6

0.8

1.0

1.2

1.4

1.6

1.8

2.0

Effective Baseline [km]2

0 0 0.02 0.04 0.06 0.08 0.1 0.12 0.14 0.16 0.18 0.2
sin22 13sin 2✓13 = 0.089 ± 0.009

2/NDOF = 0.48/4• Uncertainty reduced by statistics of complete 6 AD data period• |Δm2ee| constrained by MINOS result: | m2µµ | = 2.41+0.09
0.10 ⇥ 103

eV2

PRL. 110, 251801 (2013)• Far vs. near relative measurement: absolute rate not constrained• Consistent results from independent analysis, different reactor models
43

IBD Prompt Energy Spectra

Spectral distortion
consistent with oscillation• Both background and predicted no oscillation

spectra determined by the best fit• Errors are statistical only
44

⇥⇤2

Rate and Shape Analysis Results
15
10
5

Rate+Spectra
Rate-Only
0.1

0.15

Best Fit
Rate+Spectra
Rate-Only

3

99.7% C.L.
95.5% C.L.
68.3% C.L.

-3|⇥m2ee| [10 eV2]

0.05

2.5

MINOS |⇥ m2µµ|
2

1.5

0.05

0.1

2

sin (2 13)

0.15

5

10 15

⇥⇤2

2

+0.0082/NDOF = 162.7/153
sin 2✓13 = 0.090 0.009
2
+0.19
2
3
| mee | = 2.59 0.20 ⇥ 10 eV

45

2
2
Δm ee and Δm μμ?
P(⌫ e ! ⌫ e ) =1

sin

2

✓

sin2 2✓13 sin2
2
mee

L
4E

◆

✓

2 L
mee
4E

2

◆

⌘ cos ✓12 sin

2✓cos4 ✓13 sin2 2✓12 sin2

✓

2
m31

L
4E

◆

2

2 L
m21
4E

+ sin ✓12 sin

2

✓

◆
2
m32

L
4E

◆

• Oscillation at ~2 km governed by two mass splittings: Δm231 and Δm232• Insensitive to distinguish the two. →Effective mass splitting: Δm2ee

Can relate to actual splittings:|

m2ee | ' |m232 | ± 5 ⇥ 10

5

eV

2

+:"Normal"Hierarchy"-:"Inverted"Hierarchy"Δm2ee should be within 2-3% from the effective mass splitting
for muon (anti-)neutrino disappearance Δm2μμ
P(⌫µ ! ⌫µ ) ' 1

2

sin 2✓23 sin

2

✓

2
mµµ

L
4E

◆

Important test of three-flavor oscillation model
46

⇥⇤2

Rate and Shape Analysis Results
15
10
5

Rate+Spectra
Rate-Only
0.1

2

sin

0.15

Best Fit
Rate+Spectra
Rate-Only

3

99.7% C.L.
95.5% C.L.
68.3% C.L.

-3|⇥m2ee| [10 eV2]

0.05

2.5

|

MINOS |⇥ m2µµ|+0.0082✓13 = 0.090 0.009+0.19
2
mee | = 2.59 0.20 ⇥ 10

2

1.5

2
0.05

0.1

sin2(2 13)

0.15

5

3

eV

2

/NDOF = 162.7/153

10 15

⇥⇤2

Strong confirmation of the oscillation model
Normal MH[10 3 eV2 ]From Daya Bay
From MINOS[João, NuFact2013]2
m32

Inverted MH[10 3 eV2 ]2mee

2.54+0.19
0.20

2.64+0.19
0.20

2
mµµ

2.37+0.09
0.09

2.41+0.12
0.09

2
m32

47

Near vs. Far Spectrum study

Far / Near(weighted)

Predict(far(spectra(directly(from(measured(near(site(spectra((

Use$covariance$matrices$to$
account$for$systema1c$errors$! Minimizes(impact(of(absolute(ﬂux(and(spectra(predic6on.(!!Alternate!method!ﬁnds!consistent!
uncertain2es!for!neutrino!parameters.!

14

Far site data

12

Weighted near site data (best fit)

Relative uncertainty for each bin
Fractional uncertainty

Events/day (bkg. subtracted)

Independent crosscheck with minimal reactor assumption

Weighted near site data (no oscillation)

10
8

Total prediction error

Far site statistics

0.12

Near site statistics
0.1

Reactor flux error
Detector response error

0.08

Background error

6
0.06

4

0.04

2

0.02

1.15
1.1

0

1.05
1
0.95
0.9
0.85
1

2

3

4
5
Prompt energy (MeV)

6

7

8

1

2

3

4

5

6

7
8
Prompt energy (MeV)

Systematic uncertainties controlled
to well below statistical error
48

14

Far site data

12

Weighted near site data (best fit)

0.0035Weighted near site data (no oscillation)

1σ (68.3% C.L.)10

2σ (95.5% C.L.)8

3σ (99.7% C.L.)

0.003

6

Default Method|Δm2ee| [eV2]

Far / Near(weighted)

Events/day (bkg. subtracted)

Near vs. Far Spectrum Study
Fit Result

4
2
1.15

Relative Shape Method
Default Best Fit
Relative Shape Best Fit

0.0025

1.1
1.05
1
0.95

0.002

0.9
0.85
1

2

3

4
5
Prompt energy (MeV)

6

7

8

0.06

0.08

0.1

0.12 0.14

0.16

0.18

2

sin (2θ13)

Consistent results with the default method49

Neutrino Oscillates
1

EH1

P(νe→νe)

EH2
EH3
Best fit

0.95

0.9
0

0.2

0.4
0.6
Leff / Eν [km/MeV]

0.8

50

Global Comparisonofof ✓θ13
Measurements
Global Comparison
Measurements
13

reevaluated flux

Solar+KamLand[1106.6028]

MINOS[1108.0015]

T2K 6 Events[1106.2822]

NormalHierarchy

DC 101 Days

[1112.6353]

Inverted
Hierarchy

Daya Bay 55 Days

[1203.1669]

RENO 229 Days

[1204.0626]

T2K 11 Events[ICHEP2012]

DC 228 Days

[1207.6632]

Rate only
Rate+Spectral

Daya Bay 139 Days

[1210.6327]

n-Gd
n-H

DC n-H Analysis[1301.2948]

RENO 416 Days

[NuTel2013]

T2K 11 Events[1304.0841]

DC RRM Analysis[1305.2734]

T2K 28 Events[EPS2013]

Daya Bay 217 Days

[NuFact2013]

Best Fit +68% C.L.

2011

original flux

Accelerator
Experiments**All results assuming:2012

CP = 0,
23 = 45°

2013

ReactorExperiments

reactor on data only
reactor on+off datasin2 2 13
0

-0.05

0.05

0.1

0.15

0.2

0.25

0.3
21 /5122

Daya Bay Onsite Progress
Final&two&detectors&installed,&
opera1ng&since&Oct.&2012.&

Full&4π&detector&
calibra1on&
in&Sep.&2012.&

EH2&

EH3&
52

0.02
0.018

Error of ⇥ m2ee [10-3eV2]

Error of sin 22 13

Future Sensitivity
Rate Only
Rate+Spectra

0.016
0.014

PRL 108 171803

Installationof AD 7+8

0.012

CPC 37 011001
This Analysis

0.01
0.008

0.25

Rate+Spectra
This Analysis

0.2

0.15

0.1

MINOS 1- on

2
m µµ

0.006
0.004

0.05

Now

0.002
0

0

200

400

600

800

Now
1000

1200

1400

1600

0
0

200

400

600

800

Time [days]

1000

1200

1400

1600

Time [days]

Sensi$vity's$ll'dominated'by'sta$s$cs!
• Sta$s$cs'contribute'73%'(65%)'to'total'uncertainty'in'sin2'2θ13'(|Δm2ee|')'• Major'systema$cs:'• θ13:'Reactor'model,'rela$ve'+'absolute'energy,'and'rela$ve'eﬃciencies'• |Δm2ee|:'Rela$ve'energy'model,'rela$ve'eﬃciencies,'and'backgrounds'• Precision'of'mass'spliLng'measurement'closing'in'on'results'from'μ'ﬂavor'sector''

53

How the data will look like in 2015
1

EH1

P(νe→νe)

EH2
EH3
Best fit

0.95

0.9
0

0.2

0.4
0.6
Leff / Eν [km/MeV]

0.8

54

Summary• The Daya Bay Experiment has made the first direct measurementof the short-distance electron antineutrino oscillation frequency:

|

+0.19
2
mee | = 2.59 0.20 ⇥ 10

3

eV

2

• We also produced the most precise estimate of the mixing angle:2

sin+0.0082✓13 = 0.090 0.009• Still, a lot of results coming in the near future:• Measurement of absolute reactor flux
• Testing non-standard neutrino models• Significantly increased precision with much more statistics

55

Backup slides

56

Scintillator Response Model
Electron%response%
2%parameteriza9ons%to%model%quenching%eﬀects%and%Cherenkov%radia9on:
1)%3Aparameter%purely%empirical%model:
2)%SemiAemp.%model%based%on%Birks'%law:

Gammas%+%positrons%• Positrons%connected%to%electron%model%through%MC:%

N/ E [MeV-1]• Gammas%connected%to%electron%model%through%MC:%

Simula9on%of%individual%eA,%e+%energies%
due%to%gamma%interac9on%in%scin9llator.%
teringCompton scat ct
effe
icPhotoelectr
Pair production

10-3

e–

e+

10 -4

60Co

n captureon H

n capture
on C

10-5

0

1

2

3

4

5

Energy of primary e+/e– [MeV]57

Electronics Non-Linearity Model
Overview of the Energy Response Model

Electronics+does+not+fully+capture+late+secondary+hits+• Slow+scin5lla5on+component+
missed+at+high+energies+• Charge+collec5on+eﬃciency+
decreases+with+visible+light

Secondary Hit
Charge Collection Eff.

PMT$readout$electronics$introduces$addi1onal$biases$
1

Single Channel
MC Simulation

0.8
0.6
0.4
0.2
0

0

50

100

150
200
250
Time Since First Hit [ns]Observed non-linearity is a productscintillator
and electronics
non-linearity
Total ofe↵ective
non-linearity
f
f =

Erec
Evis Erec=⇥= fscint (Etrue ) ⇥ felec (Evis )Etrue
Etrue Evis

1

Scintillator non-linearity

2

Electronics non-linearity

Constrained the model with full use of current existing data...

9 / 2258

Trigger Performance
Trigger&Thresholds:&!!"!AD:!>45!PMTs!(digital!trigger)!
!!!!!!!!!!!!>0.4!MeV!(analog!trigger)!
!!"!Inner!Water!Veto:!>!6!PMTs!
!!"!Outer!Water!Veto:!>7!PMTs!
!!"!RPC:!¾!layers!in!module!
&

Digital!Trigger!(Nhit)!

EH1!

Trigger&Eﬃciency:&!!"!No!measureable!ineﬃciency!>0.7!MeV!
!!"!Minimum!energy!expected!for!prompt!!
!!!!anRneutrino!signal!is!~0.9!MeV.!

Analog!Trigger!(Esum)!

EH1!

59

Calibration: PMT+Electronics Gain
Measure'charge'from'single'photons'in3situ'with'data'
Use%out=of=(me%PMT%signals%hits%to%calibrate%the%PMT%+%electronics%response%to%single%photons.%%

Gain%varia(on%with%(me%Cross=check%with%weekly%LED%deployments.%%%

ADC%charge%from%(mostly)%single%
photons%in%one%
channel%%Calibra8on'driven'by'uncertainty'in''rela8ve'detector'eﬃciency'

60

Calibration: Energy Scale
Measure'energy'scale'in.situ'with'data'
Calibrate)charge)(photoelectrons))collected)per)MeV)in6situ)using)spalla8on)nGd)
capture)events.)Also)use)weekly)deployments)of)60Co)source.))
Spalla8on)nGd)capture))(uniform)throughout)detector))~1.5%/year'
degrada9on'of'
the'energy'scale'Test)periods)

Energy)Scale)=)Q)/)E)
Measured)charge)of)nGd)peak)

Average)energy)
released)in)nGd))

Small)degrada8on)of)energy)scale)is)seen)with)nGd,)60Co,)and)other)event)types.)Its)origin)is)s8ll)unknown,)but)do)not)an8cipate)any)problems)in)experiment’s)life8me.))61

Calibration: Detector Uniformity

Measure'uniformity'with'sources'placed'along'three'axes'and'spalla7on'nGd'events'

Energy"response"varies"
across"detector…""…but"s4ll"consistent"
between"detectors""

Example:'60Co'

3"sources"along"3"axes"

A/er"ﬁrst2order"
correc4on,"energy""
is"more"uniform.""~%"level"residual"non2uniformi4es"

62

Largest(uncertainty(between(detectors(*Some*nGd*gammas*escape*scin2llator*region,**visible*as*tail*of*nGd*energy*peak.***
0.01

Use*varia2ons*in*energy*peaks*to**constrain*rela2ve*eﬃciency.*
Po215 alphaAsymmtry w.r.t. AD1

0.008

Entries/30keV

Delayed Energy Cut
EH1 AD1
EH1 AD2104

EH2 AD1
EH3 AD1
EH3 AD2103

EH3 AD3

102

IBD n-Gd1

Spa n-Gd

0

Po212 alpha

0.006

Po214 alpha

0.004

nGd*

10

0.002

Spall<n*capture**
2

4

6

8

10
12
Energy (MeV)Eﬃciency(varia5ons(
es5mated(at(0.12%(

0-0.002Asym = (EAD1 – EADn)/<E>-0.004-0.006-0.008-0.01‘Intrinsic’*energy*peak*varia2on:*~0.3%*
1

2

3
4
AD number

5

Mo2va2on*for*
3<zone*design*

663Capture Time
EventsConsistent(IBD(neutron(capture(1me(measured(in(all(detectors(
EH1-AD1103

EH1-AD2

Capture(1me(cut:(!!1μs!to!200μs!
!
Eﬃciency!uncertainty!
within!0.01%!!
between!detectors.!!

EH2-AD1
EH3-AD1
EH3-AD2102

EH3-AD3

10

1

10-1
0

20

40

60

80

100

120

Simula'on*contains*no*background*(deviates*from*data*at*>150*μs)*

140

160

180 200Δt [µs]64

Accidental backgrounds
Two$uncorrelated$signals$can$accidentally$mimic$an$an3neutrino$signal.$

Signals(>6(MeV:($$12B$from$cosmic$spalla3on$$$241Am<13C$calib.$source$
Accidental(B/S(is(4%((1.5%)(of(far((near)(signal.($
Accidental$background$be$accurately$modeled$using$uncorrelated$signals$in$data.$$!$Negligible$uncertainty$in$background$rate$or$spectra.$65

Fast-neutron backgrounds
Constrain)fast+n)rate)using)
IBD+like)signals)in)10+50)MeV)

Fast%Neutrons:%))EnergeJc)neutrons)produced)by)cosmic)rays)))(inside)and)outside)of)muon)veto)system)))

Mimics%an1neutrino%(IBD)%signal:%)+)Prompt:)Neutron)collides/stops)in)target))+)Delayed:)Neutron)captures)on)Gd)))

Analysis)muon)veto)cuts)control)B/S)
to)0.06%)(0.1%))of)far)(near))signal.)

Validate)with)fast+n)events)
tagged)by)muon)veto.)

66

Reactor Flux Models
Antineutrino flux S(E) from each reactor used to predict IBDs at each detector
New/Old flux model difference inunoscillated IBD prediction by hall

Approximate percentage of IBDs fromeach fission isotope at each detector
New model:
P. Huber, Phys. Rev. C84, 024617 (2011),
T. Mueller et al., Phys. Rev. C83, 054615 (2011)

S(E) uncertainties, new model

Flux model has negligible impact on
far vs. near oscillation measurement

Old model:
K. Schreckenbach et al., Phys. Lett. B160, 325 (1985)
A. A. Hahn et al., Phys. Lett. B218, 365 (1989)
P. Vogel et al. Phys. Rev. C24, 1543 (1981)67

Rate Uncertainty Summary
With near/far
measurement, correlated
uncertainties cancel.
Only uncorrelated
uncertainties are used.

• Rate Uncertainty Summary

Largest systematics
are smaller than far
site statistics (~1%)

Uncorrelated reactor
systematics reduced by
far vs. near measurement.
68Daya Bay Future
Improved)precision)on)oscilla0on)parameters)!"!Constrains!non"standard!oscilla.on!models!
!"!Improves!reach!of!future!neutrino!experiments!
!

Measure)absolute)reactor)neutrino)ﬂux)!"!Explore!the!‘reactor!an.neutrino!anomaly’!
!"!Precise!spectrum!probes!reactor!models!
!

Cosmogenic)Backgrounds)!"!Measurement!of!cosmogenic!produc.on!vs.!depth!
!

Supernova)Neutrinos)
Approximate!Daya!Bay!
near"site!precision!

PRD$83,$073006$$
arXiv:1303.0900$
69

2

χ Definition
det ×E pχ = ∑ [ Ni
2

pred

i

2
χ definition

2⃗ ,−N data + N data log(θ13 , Δ mee , ⃗f , ⃗η , ⃗ϵ , b)ii

N idata
N

pred
i

⃗
(θ13 , Δ m , ⃗f , ⃗η ,⃗ϵ , b)2ee]

site× E p site× E p+ ∑jabs. E+ ∑l∑ f j V −1jk f k
k

η2l

+

Energy Model Constraint

σ2l

det ×eff

∑

2

ϵm

m

σ 2m

det ×bg

b2n

n

2
n

+ ∑

Reactor Flux Model Constraintσ

Detector Efficiency Constraint
Background Constraint

Binned maximum likelihood method● Constrain with the uncertainty from reactor flux
model, background and relative detection
efficiency.

Far vs. near relative measurement [Noconstraint on the absolute rate]

2 HE

Using covariance matrix to reduce number of thenuisance parameters for the reactor flux model.

1 HE

●

3 HE

●

EH1

EH2

EH3

35
70

|⇥m2ee| (10-3 eV2)

Pure Spectral Analysis
3.6
3.4

99.7% C.L.
95.5% C.L.
68.3% C.L.

3.2

Shape-Only Best Fit

3
2.8
2.6
2.4
2.2
2
1.8

0

0.05

0.1

0.15

0.2

2

0.25

sin 2 13

θ13$=$0$can$be$excluded$at$>$3σ$from$spectral$informa:on$alone!

71

sin 2θ sensitivity projection

2 Sensitivity Projection
sin22θ13
13
80%

this analysis

Data collected up to now

Error Percentage

70%

73%

sin22θ13

65%

60%

Δm2ee

50%
40%
30%

21%

18%

20%

13%

10%

2%

0%
Statistic

11%
1%

4% 6%

ReactorAbs. Energy
Rel. Energy and Eff.
Background

Current errors are dominated by the statistical uncertainties (73%)● Major systematics:● Reactor Model, relative+absolute energy and detector efficiency
2● Daya Bay sin 2θ
final precision ~4%, it can be further improved by
13
adding nH capture analysis
●

41

72

Δm sensitivity projection2Δm2ee Sensitivity
Projection
this analysis
80%

MINOS 1σ error
2
+0.09
−3
2
∣Δ mμ μ∣=2.41−0.10×10 (eV )PRL. 110, 251801 (2013)

Data collected up to now

Error Percentage

70%

73%

sin22θ13

65%

Δm2ee

60%
50%
40%
30%

21%

18%

20%

13%

10%

11%

2%

0%
Statistic

1%

4% 6%

ReactorAbs. Energy
Rel. Energy and Eff.
Background

Current errors are dominated by the statistical uncertainties (73%)● Major systematics:● Relative energy and background2-3
2● Daya Bay |Δm|
final
precision~0.1x10eV, comparable to theeeresults from μ flavor sector
●

42
73

Making a Far Site prediction fromthe Near Site data
From%the%%% •%rela4ve%reactor%core%power%info%% •%experimental%layout%geometry%%
it%is%possible%to%determine%what%
frac4on%of%events%in%each%near%detector%at%each%true%energy%bin%
originate%from%each%core.%%Each%of%these%components%is%then%individually%extrapolated%to%the%far%site%%
All%reactor%and%detector%correlated%systema4cs,%including%the%absolute%
ﬂux%and%shape%uncertain4es,%cancel&
to&ﬁrst&order.%%
76%

74

2
2
Δm
,
Δm
μμ and MHee2• Value of Δm ee constrained by the effective mass splitting measured
2 .
by muon (anti-)neutrino disappearance,
Δm
μμ
✓
◆

P(⌫µ ! ⌫µ ) ' 1

2

sin 2✓23 sin

2

2
mµµ

L
4E

• Reactor neutrinos can make independent measurement of Δm2ee

ANOTHER POSSIBLE WAY TO DETERMINE THE . . .

• Need <1% precision for both

Δm2

ee

and Δm2

μμ to resolve

mass hierarchy.
• Extensively discussed in• PRD 72, 013009(2005) and• PRD 74, 053008 (2006)

PRD 72, 013009 (2005)
2cosδ = -1

1.5

NORMAL1cosδ =

1

0.5

Daya Bay0-0.5cosδ = 1-1

INVERTED-1.5

cosδ =

-2

-2.5

0

0.005

0.01

0.015

0.02

0.025

Excluded by CHOOZ

oscillation model

2.5∆eµ% (Δm2ee - Δm2μμ)• Important test of the three-flavorcosδ = 0cosδ = 0

-1

0.03

0.035

0.04

0.045

0.05

2

sin θ1375