Download Sean Grullon

Searching for High Energy Diffuse
Astrophysical Neutrinos with
IceCube
Sean Grullon
For the IceCube Collaboration
TeV Particle Astrophysics 2009
Stanford Linear Accelerator Laboratory
Overview
• Astrophysical Neutrinos & Searching for a
Diffuse Flux of Muon Neutrinos
• Muon Energy Estimation
• 22 String Diffuse Analysis Results
• Outlook for 40 Strings
• Questions & Discussion
Sean Grullon – TeVPA 2009
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Neutrinos as Cosmic Messengers
Neutrinos help answer many questions in
astrophysics:
•What are the sources of
highest energy cosmic
rays? Are there pp and p
interactions at the source?
•Can neutrino production
be linked to TeV  sources,
GRBs, AGN?
• Can a superposition of
faint neutrino sources
cause a detectable
signal?
Sean Grullon – TeVPA 2009
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2007-2008:
18 Strings
2006-2007:
13 Strings
IceTop
2005-2006: 8 Strings
Air shower detector
threshold ~ 300 TeV
2004-2005 : 1 String
InIce
first data 2005
upgoing muon 18.
July 2005
80-86 Strings,
60 Optical Modules per
AMANDA
String
19 Strings
677 Modules
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Cosmic ray
Atmospheric m
n
m
Astrophysical
(signal) n
Atmospheric n
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Downgoing Muon Rejection
• Apply quality cuts on Data, Corsika MC, and
Atmospheric Neutrino MC
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Diffuse Analysis Strategy
• Find an excess of astrophysical neutrinos
(E-2) over atmospheric neutrinos (E-3.7) at the
high-energy tail of an energy distribution
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Energy Estimation
•Convert what is measured, Cherenkov light, to an estimate of the Muon
energy.
•Simplest estimation: Number of Triggered Optical Modules (NCh)
•More Sophisticated: Muon Energy Loss (dE/dX)
m
p

e+e-
photo-nuclear
pair-creation
bremsstrahlung
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Reconstructing The Muon energy
loss
Formulate LLH:
k
 log P({ni } | {mi })   ni log mi m   N log m  m
Approximate as:
dusty
i 1
clean
Incorporate Ice Properties:
Sean Grullon – TeVPA 2009
shallow
10
deep
Muon Energy Correlation – 40 Strings
dE/dX Reco
NChannel
•dE/dX reco more linearly correlated with Muon energy
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Energy Resolution – 40 Strings
Width
0.27
Width
0.43
•dE/dX reco has narrower energy resolution
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Energy Resolution as a Function
of Muon Energy – 40 Strings
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The dE/dX distribution of IC22
275.7 days LiveTime
•Find cut that minimizes
average upper limit
•Energy Cut > 1.4
Keep
•Background above cut
= 4.1 Events
•Observed Data above cut
= 4.0 Events
• Sensitivity:
2.5 x10-7
GeV cm-2 s-1 sr-1
Sean Grullon – TeVPA 2009
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The dE/dX distribution of IC40
300 days LiveTime - MC Only
Sean Grullon – TeVPA 2009
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Likelihood Analysis Method
• Likelihood - product over bin-by-bin Poisson probabilities:
k
L  P({ni } | {mi })  
i 1
Events observed in bin i
mi n
i
ni !
e  mi
Events expected in bin i
mi  N c ci   N p pi  N e ei
Conventional Atmospheric ν
Prompt ν
Sean Grullon – TeVPA 2009
Astrophysical ν
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Fitting Example: 1 Year IC40 - No
Astrophysical or Prompt ν
•“Data” Poisson sampled
from 1 year of Atm. ν MC
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Allowed Regions, No Astrophysical or
Prompt ν : 1 Year of IC40
Preliminary IC40 Diffuse Sensitivity:
E2 < 1.1 x 10-8 GeV cm-2 s-1 sr-1
No Systematics included
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Models & Limits
IC22
WB
IC40
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Summary
• A reliable log-likelihood reconstruction of the muon
energy loss is now available for IceCube analyses.
• The IC22 sensitivity is E2 < 2.5 x 10-8 GeV cm-2 s-1 sr-1
above a dE/dX cut of log10(dE/dX) >= 1.4
• 275.7 days of IC22 data were analyzed and compared
with the Bartol + naumov RQPM atmospheric neutrino
simulation.
No data excess over the atmospheric neutrino prediction
observed above the dE/dX cut.
• The IC40 analysis uses a likelihood method giving a
preliminary sensitivity of E2 < 1.1 x 10-8 GeV cm-2 s-1 sr-1
and the incorporation of systematic errors is currently
underway.
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Backup slides
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Systematics – IC22
New from
IceCube
Data
AMANDA
depth
Atms. Nu MC
Coinc. Mu
• Observed data
exceeds MC by a
factor of 2 in deep
ice
• Deep Ice 40%
clearer.
Single
Mu
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COGZ
COGZ
Systematic Test (low energy, NCh<50)
Data
COGZ
upgoing cos(zenith) horizon
Data - MC
Atms. Nu MC
upgoing cos(zenith) horizon
• Data excess is observed even
with the low energy events
(conventional atmospheric
neutrinos)
• Divide the detector in 2 depths
: upper half and lower half
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Systematic Test
Upper Half
Estimator
Energy Sensitivity Bartol+Naumov 1e-7 E-2
data
-7
cut
x 10
RQPM
MC
log10(dEdX) >=0.97
NCh
>=68
0.50
0.41
7.9
7.9
12.2
15.0
5
3
log10(NPe) >=2.85
0.54
8.0
11.3
5
Lower Half
Estimator
Energy Sensitivity Bartol+Naumov 1e-7 E-2
data
-7
cut
x 10
RQPM
MC
log10(dEdX) >=0.91
NCh
>=80
log10(NPe) >=3.15
0.58
0.47
15.5
12.8
14.0
15.7
0.64
2.4
6.4
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25
4
26
Sensitivities: Likelihood Method
Extraterrestrial Only
Energy Estimator
MRF
Limit
MCν
0.04
4* 10-9
MCμ
0.066
6.6* 10-9
Photorec
0.101
1.01* 10-8
MuE
0.122
1.22* 10-8
NChan
0.125
1.25* 10-8
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Fitting Example: No Signal
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Fitting Example: No Signal
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Allowed Signal and Prompt
Regions
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Fitting Example: Signal + Prompt +
Conventional Atmospheric Neutrinos
“Data”
sampled
from
Atm Nu
backgro
und
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Allowed Extraterrestrial and
Prompt Regions
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