Transcript The Search for Neutrinos from Gamma Ray Bursts with the Antarctic Muon and Neutrino Detector Array Kyler Kuehn, UC-Irvine Presented at OSU-CCAPP September 7, 2007

The Search for Neutrinos from
Gamma Ray Bursts
with the Antarctic Muon and
Neutrino Detector Array
Kyler Kuehn, UC-Irvine
Presented at OSU-CCAPP
September 7, 2007
Outline
• Introduction
• Results
- The Punch Line
- Gamma-Ray Bursts
- Models of  Emission
- AMANDA
- Principles of  Detection •
• Analysis Procedure
- Correlated Observations
- Burst Types
•
- Detector Stability
- Data Selection Criteria
- Systematic Uncertainties
- Effective Collection Area: Aeff
- Combined Observations:
1997-2003
- Flux and Fluence Limits
- Model Rejection Factors
Future of Transient Point
Source Searches
- Failed GRBs
- Jet-Driven SNe
Conclusions
• Alabama University, USA
• Bartol Research Institute, Delaware, USA
• Pennsylvania State University, USA
• UC Berkeley, USA
• UC Irvine, USA
• Clark-Atlanta University, USA
• University of Alaska, Anchorage, USA
• Univ. of Maryland, USA
• IAS, Princeton, USA
• University of Wisconsin-Madison, USA
• University of Wisconsin-River Falls, USA
• LBNL, Berkeley, USA
• University of Kansas, USA
• Southern University and A&M College, Baton Rouge, USA
The IceCube Collaboration
USA (14)
Japan
Europe (15)
• Chiba University, Japan
• University of Canterbury, Christchurch, NZ
New Zealand
• Universite Libre de Bruxelles, Belgium
• Vrije Universiteit Brussel, Belgium
• Université de Mons-Hainaut, Belgium
• Universiteit Gent, Belgium
• Humboldt Universität, Germany
• Universität Mainz, Germany
• DESY Zeuthen, Germany
• Universität Dortmund, Germany
• Universität Wuppertal, Germany
• MPI Heidelberg, Germany
• Uppsala University, Sweden
• Stockholm University, Sweden
• Imperial College, London, UK
• Oxford University, UK
• Utrecht University, Netherlands
ANTARCTICA
A New Astronomical Messenger
Cutoff determined by e+e- threshold for stellar IR photons
diffuse, GRB
Cutoff determined by μG galactic B field
AGN, TD
Neutrinos open a new window onto astrophysical
processes in ways which no other particle can
The First GRB
• Observed by Vela
(test-ban monitor)
• Intense burst of
high-energy (>keV)
photons over short
time period (<10 s.)
• Cause unexplained
for decades...
The BATSE Revolution (1991-2000)
A total of 8 detectors, one on each corner of CGRO
• Located on the
Compton Gamma-ray
Observatory (CGRO)
• Detected ~1 GRB/day
with 1/3 sky coverage
• Led to many of the
breakthroughs in our
understanding of GRBs
Burst and Transient Source Experiment
What Did BATSE Observe?
Galactic
coordinates
Isotropy is an indicator of the cosmological origin of GRBs
(also determined from redshift measurement of BeppoSAX)
What Did BATSE Observe?
Bimodal Distribution: Two Classes of Bursts
Gamma-Ray Burst Lightcurves
Widely varying
characteristics
between, and
even within,
GRB classes:
duration,
peak flux,
time profile,
etc.
Long GRBs
Short GRBs
Canonical Progenitor Theories
• Collapsars widely accepted
to be associated with longduration bursts (t90 > 2 s.)
• NS-NS mergers associated
with short-duration bursts
(SGR giant flares also
sGRBs?)
•GRB Phenomenology and
(usually) emission mechanism
are independent of nature of
progenitor: Fireball
•Other progenitor models:
Cannonball mechanism?
Image courtesy of David Darling
Fireball Model of GRB Emission
Jet break seen when opening angle equals observer viewing angle
Image courtesy of T. Piran (Science 295, 986)
Characteristics of the Fireball
according to Waxman, astro-ph/0303517
• relativistically expanding jet, accelerated by
(magneto-)hydrodynamic mechanisms
• 102  Γ  103 from constraints of non-thermal
spectrum
• Internal collisions within fireball lead to γ-ray
emission (synchrotron, inverse Compton)
• Ejecta eventually expand into ISM (reverse
shock, afterglow, jet opening angle θ >> 1/Γ0)
GRB Search: Science Motivation
• Cannot directly observe the inner engine of GRBs
(stellar progenitor environment optically thick)
• If protons are accelerated in the GRB environment*,
neutrinos will be produced:
p +   ±  m± + m  e ± + e + m + m
(this could also explain the origin of UHECRs)
• Probe inner engine and physics of the explosion,
eventually test neutrino properties
• Predicted neutrino flux varies depending upon
specific model parameters (GRB emission
mechanism, neutrino spectrum, ν/γ ratio, etc.)
* But see also Lyutikov & Blandford, astro-ph/0312347: the “Poynting-flux dominated”
model of GRB emission predicts negligible baryon loading and ~0 neutrinos.
GRB Muon Neutrino Spectra
Waxman, E.,
Nuc. Phys. B 118 (2003)
Razzaque et al.,
PRD 68 083001 (2003)
“Precursor”
Razzaque et al.,
PRL 90 241103 (2003)
“Supranova”
Max SN/GRB efficiency
Murase & Nagataki (Set A)
PRD 73 063002 (2006)
See also Dar & DeRújula (astro-ph/0105094): “CannonBall” Model predicts that
bursts with F > 10-5 erg cm-2 (~10%) emit »1  in narrow beam, (Θ/Θγ)2 ~ 1/100
AMANDA
ν
IceCube
CGRO
γ, ν
A Distant GRB
IPN Satellites
(HETE, Swift, etc.)
GRB timing/localization information
from correlations among satellites
South Pole
South
Pole
• AMANDA-II:
19 Strings,
677 Optical Modules
• AMANDA B-10: 10
strings,
302
Optical Modules
• Trigger rate: ~70 Hz
(mostly downgoing muons)
• Angular resolution:
δθ ~ 3°
(likelihood reconstruction)
Digital Optical Module (DOM)
8’’ Hamamatsu PMT with twisted pair (electrical) or optical fiber transmission cable
with in situ calibration source (LED + diffuser or laser)
Few percent failure rate—primarily cable penetrator disconnection on refreezing)
AMANDA: Principles of Detection
• νμ + N  μ + X
• μ emits Cherenkov
radiation within ~1°
of  direction
• Particle direction
reconstructed from
timing correlations
between OMs:
Look for sources...
AMANDA: Principles of Detection
• Observations over entire sky
• If an upgoing particle is
observed, it must be a
neutrino—nothing else can
travel through the entire earth
•Downgoing/horizontal events
used in UHE, cascade analysis
(minimal background above
107 GeV)
Data Acquisition & Processing
Offline Analysis
Level Zero
• Hit Cleaning
• Flare Checking
Level One
• FG Reconstruction
• Angular Selection (70º)
Level Two
• Advanced Reconstruction
• Angular Selection (80º)
Level 3+
• Analysis-Specific
Selection Criteria
AMANDA’s Objectives
• Transient Point Sources: GRBs
• Continuous Point Sources:
AGNs, SNRs
• Diffuse Sources: “low” energy
(<105 GeV) and ultra-high
energy (e.g. GZK )
• Atmospheric 
• Dark Matter: indirect detection via
WIMP annihilation in Earth/Sun
• Cosmic Rays: Energy Spectrum
and Composition
• Glaciology/Paleoclimatology
Analysis Goals
Previous work with GRBs (1997-2000) by AMANDA collaboration
This work describes an independent analysis with refined search
algorithm applied to extended dataset
•Based on methods of prior analyses, but derived independently
•Improve cut selection, reconstruction
•Apply search algorithm to new burst types:
Used Third InterPlanetary Network of satellites (IPN) exclusively
after BATSE ceased data-taking on May 26, 2000
Analysis designed to increase probability of GRB neutrino detection
or in the absence of a detection, to improve the flux upper limit on
various predicted neutrino spectra.
Observation Procedure
Burst location and timing
determined by:
BATSE
•Burst Catalogs
•Stern, Kommers
•
•
•
•
•
•GUSBAD
IPN3
•IPN Circulars
•Archival search
(K. Hurley et al.)
•
•
•
•
Instrument
BATSE LAD:
Ulysses:
Konus:
BeppoSAX:
– GRBM:
– WFC:
HETE-II:
– FREGATE:
– WFXM:
– SXC:
Mars Odyssey:
INTEGRAL:
NEAR
RHESSI
Energy (keV)
50-300
25-150
12-10000
40-700
2-26
6-400
2-25
1-14
100?-8000
15-10000
100-10000
300-25000
Categories of Observed Bursts
• BATSE Triggered
– Theoretical models based on “standard” GRBs*
– Localized to <1/2 searchbin size (usu. arcmin.)
• BATSE Non-Triggered
– Significantly lower peak flux
– Not incorporated into theoretical models
• IPN Well-Localized Bursts (BATSE trig?)
• IPN Annular-Localized (“Banana”) bursts
*some models further restricted to only long GRBs (t 90 >2 s)
IPN as Triggered Bursts
• ~10% of IPN do not trigger BATSE
(135 BATSE non-trig, 1088 BATSE triggered)
• Why non-triggered?
– Earth occultation, SAA, other downtime
– Energy Range, Collecting Area, Efficiency: BATSE>Ulysses
Not Due to Sensitivity!
 Include All IPN as Triggered-Equivalent
Adds <10% uncertainty for all IPN bursts
Annular-Localized (“Banana”) Bursts
Annulus segment length = 20°
from KONUS ecliptic latitude
determination
~3x standard searchbin size
Requires more restrictive selection
criteria to remove 3x more BG
See also forthcoming results of
Anna Franckowiak, who performed
an analysis on 64 AnnularLocalized bursts from 2000-2004.
Observation Procedure
Blinded
10 minute
window
-5
minutes
+5
minutes
- 60
minutes
+ 60
minutes
~110 (120-10) minute background used to set cuts and check for data quality & stability
•Background region is approximately ±60 minutes surrounding each GRB
•Omit ±5 minutes surrounding GRB trigger time
•Expected NBG/burst = Off-Time Rate x Burst Duration/110 minutes
Detector Stability
Stability Criteria:
• Number of functional OMs
• Not missing important segments of data
• Time between events (t)
• Nevents/10 s. well modeled by Gaussian fit:
(P=[RMS(data) – Sigma(fit)]/RMS)
• P<6% OR 6%<P<12% and
no on-time/off-source fluctuations > 3σ
Detector Stability (Continued)
Occurrences in 2 hr. window
Representative sample of
background (2 hour) time
period with uncorrelated
events: e-αx with α = 1.8
t = 1/rate  0.56 Hz, as
expected after application of
initial data “cleaning” and
angular restrictions
time difference (t)
Avoid “false negatives”:
anomalously large time
differences between
subsequent events signify
missing data where no signal
would be detected
Detector Stability (continued)
Occurrences in 2 hr. window
Representative sample of
background (2 hour) time window
with uncorrelated events
Mean event rate ~7 Hz, as
expected after application of initial
data “cleaning” and loose angular
restrictions
(BATSE#6610)
30
40
50
60
70
80
90
Nevents/10 s.
Avoid “false positives”:
anomalously large numbers of
high Nevents/10 s. signify excess
events which could mimic signal
events
Simulated and Observed Data
• Simulated Signal
– Nusim (or muo0)  Muon Monte Carlo (MMC)  AMASim
– 10k generated events/file * ~100 files/year  <1% statistical
uncertainty in any energy bin
– Optimized for W-B spectrum, reweighted to other spectra
• Simulated Background
– CORSIKA (w/QGSJet)  MMC  AMASim
– Used primarily as a “sanity check” for GRB analysis
• Observed Data
– approximately February 15 - December 10 each year
– ~10 TB raw data/year (muon DAQ + TWR DAQ)
– Transmitted to White Sands via satellite link + stored on magnetic tape
• Simulated and Observed data processed identically
• Data Reduction includes “Hit Cleaning”, Initial track/cascade
econstruction, zenith angle selection
• Individual analyses implement higher level selection criteria
Simulation Characteristics
DATA agree with
BG SIMULATION
but are distinct from
simulated signal events
based on W-B model
•Observed BG modeled
well by simulated events
•Provides additional
measure of confidence for
signal simulations (see
also Ph.D. Dissertation of
J. Hodges from UW)
Optimization of Selection Criteria
Minimize Model Rejection Factor*, based on sensitivity for
Waxman-Bahcall and Precursor neutrino spectra:
MRF = Event Upper Limit, FC†[90%] (μ90)
.
Expected Signal from simulations (Nsig)
Nsig = ∫Aeff,(E) (E) dE dt dΩ
Iterative Minimization of MRF with N-1 cuts applied
* Hill, G., and K. Rawlins, Astropart. Phys. 19 (2003) 393-402
† Feldman, G., and R. Cousins, PRD 57 (7) 3873
(this formalism is particularly useful for small number statistics)
Data Selection Criteria (“Cuts”)
Selection criteria to separate signal from background:
•Event Time: (t0 - 110 s) to (t0 – 10 s) for precursor search
(t0 - 10 s) to (t0 + duration + 1 s) for coincident search
where duration = t90 for BATSE bursts, t3σ for IPN bursts
•Angular Mismatch of Reconstructed Track Direction (i) relative
to burst position; several different reconstructions applicable (i=1-4)
•Uniformity (S) of hits along reconstructed track
•Number of Hit Channels (NCH)
•Number of Direct Hits (NDir) with small time delay from scattering
•Angular Resolution (σ) of alternate track reconstruction
•Zenith-weighted log(Likelihood) of Reconstructed Track log(£reco)
Representative Selection Criteria
Simulated Signal
Simulated Signal
Observed BG
Observed BG
Angular Mismatch (2)
Track Uniformity (S)
Relative MRF
Selection Criteria Optimization
Reasonable ranges are tested
for each criterion individually,
then in conjuction with all
other criteria (“iterative N-1
optimization”)
Angular Mismatch 1
In this example, a slightly
larger mismatch angle is
chosen to provide higher
signal retention, given the
burst position uncertainty.
Final Selection Criteria
Effective Neutrino Collecting Area
Collecting Area Aeff, (cm2)
Nsig = f * ∫Aeff,(E) (E) dE dt dΩ
calculated for A-II, B-10 bursts
Aeff, includes: σcc, rμ, selection
critiera, earth attenuation effects
dt  livetime = NBursts/700
dΩ  searchbin size
log10(Neutrino Energy/GeV)
= No Attenuation
= B-10 GRB
= A-II Point Source (50o)
= A-II Diffuse
f = statistical correction for burst
subtypes selected (long, short,
triggered, etc.)
00-03 = 151 GRBs
Observations 1997-2003
Year
1997
NBursts
78
NBG
0.06
NObs
0
1998
94
0.20
0
1999
2000
2001
2002
2003
Total
96
87
16
22
26
419
0.20
1.02
0.07
0.08
0.13
1.74
0
0
0
0
0
0
Also Observed 0 Events in
coincidence with 153 Non-Triggered
BATSE Bursts from 1997-2000
Feldman-Cousins
90% Confidence Level
Event Upper Limit for
0 observed/1.74 expected:
μ90 = 1.30
(~1/3 Expected Sensitivity)
μ*90 = μ90(POLE) = 1.1
Recall
Model Rejection Factor:
MRF(*) = μ(*)90 / Nsig
MRFs and Flux Upper Limits
MRF*(Waxman & Bahcall) = 1.3
This benchmark flux prediction will
be reached within a few years.
MRF*(Murase & Nagataki) = 0.82
Observations eliminate predictions
of Parameter Set A at 90% CL.
MRF*(Supranova) = 0.40
Observations eliminate most
optimistic assumptions, in agreement
with  observations.
CannonBall: 0 events, 419 bursts
 (Θ/Θγ)2 ≤ 1/40
Testing Other Models: MRF*(DePaolis) = 0.71
MRF*(Precursor) = 14.
Comparative Flux Upper Limits
UHE
diffuse
this work
This GRB analysis has the most sensitive
limit to date–more than a factor of 10 better
than other AMANDA analyses!
Spectrum-Independent Limits
Green’s Function Fluence Limit
from Super-Kamiokande: Fukuda et al., ApJ 578 (2002) 317
Φ(Eν) = N(90)
Aeff(Eν)
.
where
N(90) = FC90(Nobs, NBG)/Nbursts and Nbursts = Ntrig + NIPN
Limit is independent of assumed ν spectrum!
Differential Fluence Limit at each energy can be integrated and
converted into flux limit over all energies
Green’s Function Fluence Limit
Integrating the Green’s
function fluence limit over
250 GeV to 107 GeV
provides results consistent
with the flux upper limit
for the Waxman-Bahcall
model described earlier:
E2 < 1.3 GeV cm-2 s-1 sr-1
(MRF ~2.5 for 151 bursts)
Extending the Transient PointSource Search: “Failed” GRBs
• GRB/SN: 980425/1998bw, 030329/2003dh
(also,
XRF020903—see astro-ph/0502553)
• “Failed” GRB: no γ signal (perhaps afterglow)
• Up to 100x observed GRB rate
• Uncorrelated searches: rolling time-window, diffuse
• Correlated search: Some fraction of SNe Ib/c are
correlated with GRBs, so use SNe spatial/temporal
information to isolate potential GRB ν signals
Extending the Transient PointSource Search: Supernova Jets
• Mildly relativistic jet (Γ~2-6) can produce TeV ν’s:
• SN at 3 Mpc (0.1/yr) may produce ~300 events in IceCube
• SN at 20 Mpc (several/yr) may produce “several” ν
• 3%-25% of SNe may be jet-driven
• astro-ph/0502521, 0407064, 0403421, 0402163, 0307228, 0303621
•CBAT catalogue (1997-2004): ~1400 SN, 119 SNIb/c
•GRB-like supernovae are promising candidates!
Conclusions and Outlook
• AMANDA has been searching for high-energy ν’s in
spatial and temporal correlation with GRBs since 1997
• Null result from 7 years of observations places stringent
limits on coincident & precursor ν emission from GRBs
• We are beginning to constrain the parameter space for
several theoretical models (esp. MN06, R03)
• Green’s Function fluence limit allows test of any
theoretical ν spectrum based on AMANDA observations
• Ongoing observations: IPN/Swift/GLAST and IceCube