Neutrino Astrophysics with IceCube

U N I V E R S I T É L I B R E D E B R U X E L L E S , U N I V E R S I T É D ’ E U R O P E

Neutrino Astrophysics with IceCube

KAEL HANSON UNIVERSITÉ LIBRE DE BRUXELLES

12T H MARCEL GROSSMANN MEETING13 – 18 JULY 2009 PARIS


Two-minute IceCube quiz

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Easy Question: Is IceCube a TeV-scale neutrino observatory?Answer: Yes, of course. IceCube was designed to optimize the response to ν-induced µ in energy range between 1-100 TeV (Aeff,ν ≈ 10 m2 at 10 TeV). Muon energy loss related to Eµ above 1 TeV. Angular resolution of 1°.

Harder Question: Is IceCube a GeV-scale neutrino observatory?Answer: Also yes. With the addition of the DeepCore detector, the threshold energy is lowered from 100 GeV to 10 GeV. In addition, 4π solid angle acceptance possible due to shielding power of surrounding detector.

Trick Question: Is IceCube an MeV-scale neutrino observatory?Answer: Yes and no. By turning the array into a simple photon counting system, it is possible to detect bursts of low-energy neutrinos emitted by supernova explosions. Discrete events are lost – you are left with a rate-vs-time. However, the effective volume is extremely large and with the resulting high statistics quite a bit of information can be extracted.


Motiva t ion: why the supernova connec t ion?

Only a handful of confirmed astrophysical sources of neutrinos– Neutrinos from the Sun– Atmospheric neutrinos– Neutrinos from 1987A supernova explosion

Measurement of temporal profile of neutrino burst from SNe in our galaxy would be invaluable data for explosion models.

Realtime monitoring into worldwide burst alert network can give hours of advance warning to optical observers.

Finally, de gustibus non est disputandum

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The IceCube Collaboration

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R. Abbasi24, Y. Abdou18, T. Abu-Zayyad29, J. Adams13, J. A. Aguilar24, M. Ahlers28, K. Andeen24, J. Auffenberg35, X. Bai27, M. Baker24, S. W. Barwick20, R. Bay7, J. L. Bazo Alba36, K. Beattie8, J. J. Beatty15,16, S. Bechet10, J. K. Becker17, K.-H. Becker35, M. L. Benabderrahmane36, J. Berdermann36, P. Berghaus24, D. Berley14,

E. Bernardini36, D. Bertrand10, D. Z. Besson22, M. Bissok1, E. Blaufuss14, D. J. Boersma24, C. Bohm30, J. Bolmont36, O. Botner33, L. Bradley32, J. Braun24, D. Breder35, T. Castermans26, D. Chirkin24, B. Christy14, J. Clem27, S. Cohen21, D. F. Cowen32,31, M. V. D'Agostino7, M. Danninger30, C. T. Day8, C. De Clercq11,

L. Demirörs21, O. Depaepe11, F. Descamps18, P. Desiati24, G. de Vries-Uiterweerd18, T. DeYoung32, J. C. Diaz-Velez24, J. Dreyer17, J. P. Dumm24, M. R. Duvoort34, W. R. Edwards8, R. Ehrlich14, J. Eisch24, R. W. Ellsworth14, O. Engdegård33, S. Euler1, P. A. Evenson27, O. Fadiran4, A. R. Fazely6, T. Feusels18, K. Filimonov7,

C. Finley24, M. M. Foerster32, B. D. Fox32, A. Franckowiak9, R. Franke36, T. K. Gaisser27, J. Gallagher23, R. Ganugapati24, L. Gerhardt8,7, L. Gladstone24, A. Goldschmidt8, J. A. Goodman14, R. Gozzini25, D. Grant32, T. Griesel25, A. Groß13,19, S. Grullon24, R. M. Gunasingha6, M. Gurtner35, C. Ha32, A. Hallgren33,

F. Halzen24, K. Han13, K. Hanson24, Y. Hasegawa12, J. Heise34, K. Helbing35, P. Herquet26, S. Hickford13, G. C. Hill24, K. D. Hoffman14, K. Hoshina24, D. Hubert11, W. Huelsnitz14, J.-P. Hülß1, P. O. Hulth30, K. Hultqvist30, S. Hussain27, R. L. Imlay6, M. Inaba12, A. Ishihara12, J. Jacobsen24, G. S. Japaridze4, H. Johansson30, J. M. Joseph8, K.-H. Kampert35, A. Kappes24,a, T. Karg35, A. Karle24, J. L. Kelley24, P. Kenny22, J. Kiryluk8,7, F. Kislat36, S. R. Klein8,7, S. Knops1, G. Kohnen26, H. Kolanoski9, L. Köpke25, M. Kowalski9, T. Kowarik25, M. Krasberg24, K. Kuehn15, T. Kuwabara27, M. Labare10, S. Lafebre32, K. Laihem1, H. Landsman24, R. Lauer36, D. Lennarz1, A. Lucke9, J. Lundberg33, J. Lünemann25, J. Madsen29, P. Majumdar36, R. Maruyama24, K. Mase12, H. S. Matis8, C. P. McParland8,

K. Meagher14, M. Merck24, P. Mészáros31,32, E. Middell36, N. Milke17, H. Miyamoto12, A. Mohr9, T. Montaruli24,b, R. Morse24, S. M. Movit31, R. Nahnhauer36, J. W. Nam20, P. Nießen27, D. R. Nygren8,30, S. Odrowski19, A. Olivas14, M. Olivo33, M. Ono12, S. Panknin9, S. Patton8, C. Pérez de los Heros33, J. Petrovic10,

A. Piegsa25, D. Pieloth17, A. C. Pohl33,c, R. Porrata7, N. Potthoff35, P. B. Price7, M. Prikockis32, G. T. Przybylski8, K. Rawlins3, P. Redl14, E. Resconi19, W. Rhode17, M. Ribordy21, A. Rizzo11, J. P. Rodrigues24, P. Roth14, F. Rothmaier25, C. Rott15, C. Roucelle19, D. Rutledge32, D. Ryckbosch18, H.-G. Sander25, S. Sarkar28,

S. Schlenstedt36, T. Schmidt14, D. Schneider24, A. Schukraft1, O. Schulz19, M. Schunck1, D. Seckel27, B. Semburg35, S. H. Seo30, Y. Sestayo19, S. Seunarine13, A. Silvestri20, A. Slipak32, G. M. Spiczak29, C. Spiering36, M. Stamatikos15, T. Stanev27, G. Stephens32, T. Stezelberger8, R. G. Stokstad8, M. C. Stoufer8,

S. Stoyanov27, E. A. Strahler24, T. Straszheim14, K.-H. Sulanke36, G. W. Sullivan14, Q. Swillens10, I. Taboada5, A. Tamburro29, O. Tarasova36, A. Tepe35, S. Ter-Antonyan6, C. Terranova21, S. Tilav27, P. A. Toale32, J. Tooker5, D. Tosi36, D. Turčan14, N. van Eijndhoven34, J. Vandenbroucke7, A. Van Overloop18, B. Voigt36, C. Walck30, T. Waldenmaier9, M. Walter36, C. Wendt24, S. Westerhoff24, N. Whitehorn24, C. H. Wiebusch1, A. Wiedemann17, G. Wikström30, D. R. Williams2,

R. Wischnewski36, H. Wissing1,14, K. Woschnagg7, X. W. Xu6, G. Yodh20, S. Yoshida12

1. RW T H A ach e n U n i v e r s i t y2. U n i v e r s i t y o f A l a b a ma3. U n i v e r s i t y o f A l a s k a

A n c h o r ag e4. C l a r k - At l an t a U n i v e r s i t y5. G eo rg i a I n s t i t u t e o f

Tec h n o lo g y6. S o u t h e r n U n i v e r s i t y7. U n i v e r s i t y o f C a l i f o r n i a ,

B e r k e l e y8. L aw r e n c e B e r k e l e y N a t i o n a l

L ab

9. H u m b o l d t - U n i v e r s i t ä t zu B e r l i n

10. U n i v e r s i t é L i b r e d e B ru x e l l e s11. Vr i j e U n i v e r s i t e i t B ru s s e l12. C h i b a U n i v e r s i t y13. U n i v e r s i t y o f C a n t e r b u r y14. U n i v e r s i t y o f M ar y l an d15. O h i o S t a t e Un i v e r s i t y16. O h i o S t a t e Un i v e r s i t y17. T U D o r t mu n d U n i v e r s i t y18. U n i v e r s i t y o f G h en t19. M a x - P l an c k - In s t i t u t f ü r

K e r n p h y s i k20. U n i v e r s i t y o f Ca l i f o rn i a ,

I r v i n e21. É co l e P o l y t ec h n i q u e F é d é r a l e22. U n i v e r s i t y o f Ka n s as23. U n i v e r s i t y o f Wi sc o n s i n ,

M a d i s o n24. U n i v e r s i t y o f Wi sc o n s i n ,

M a d i s o n25. U n i v e r s i t y o f M a i n z26. U n i v e r s i t y o f M o n s - H a i n a u t27. B a r t o l R es ea r ch I n s t i t u t e

28. Un i v e r s i t y o f O x f o r d29. Un i v e r s i t y o f Wi s c o n s i n ,

R i v e r F a l l s30. S t o ck h o l m Un i v e r s i t y31. P en n S t a t e U n iv e r s i t y32. P en n S t a t e U n iv e r s i t y33. Up p s a l a Un i v e r s i t y34. Ut r e ch t Un i v e r s i t y35. Un i v e r s i t y o f Wu p p e r t a l36. DE S Y Z eu t h e n


The IceCube Detector

When complete 2012– 80 in-ice strings– 6 deep core strings– 160 surface airshower tanks

2009 “IC59” status– 58 normal in-ice strings– 1 DeepCore string– 118 surface tanks– 3730 channels in the DAQ– 1.8 kHz trigger rate (CR µ)– 15 MB/sec raw data to tape– 50 GB per day filtered data over

satellite link from Pole– 300 atmospheric neutrinos per day

at trigger level 2008 IC40 run complete now

analyzing data from this period (5/08 – 5/09)

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IceCube DeepCore

Increase in detector eff. at 10 – 100 GeV IceCube str ings form veto shield around

core for 4π acceptance Ice extremely c lear at depth (λ a t t > 150

m) Low-energy topics

– Atmospher ic neutr inos– Neutr ino mass h ierarchy– Dark matter– Low energy ast rophys ica l fluxes

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Dril l ing and deployment

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Digital Optical Module technology

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DOM OpticalLarge Area Photocathode10” (500 cm2) Hamamatsu R7081-02 bialkali PMT (peak QE 24% @ 420 nm); High QE variant (peak QE 35% @ 420 nm) used in DeepCore DOMsLow noise< 300 Hz background counting rate in-ice (with artificial deadtime - see later)Glass / Gel ImprovementsBetter transmission in 330 - 400 nm relative to AMANDA OMOptical calibrationEach DOM is calibrated ε(λ) in the lab to about 7%; in-situ flasher board additionally permits in-ice measurements

DOM Electronics“Smart” sensor digital technologyVersatile FPGA design with option to expand / change programming at any point in lifecycle. Core of supernova DAQ resides inside DOM itself.Array TimingHandled in DOM logic - DOM-to-DOM timing good to 2-3 ns using RAPCal method.Low power - 3.75 W / DOM

15 of 3776 DOMs are useless, 35 more have serious problems. As of June 2009 all DOMs have been produced.


TEV NEUTRI NO ASTRO -PARTICLE PH YS ICS WITH I CECUBE

Part I I

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Cosmic ray accelerat ion

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Model of CR acceleration in shocks of SN remnants fits observation but not confirmed. TeV γ emission now established for many sources but could be from EM processes. Neutrino emission would be “smoking gun” for hadronic acceleration in these sources.


The neutrino sky

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LINEAR TRACKSCASCADES“DOUBLE-BANG”

Detecting TeV ν in IceCube

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Neutrino undergoes CC or NC interaction with nuclear material, produces charged particles which emit Cherenkov radiation

CC

NC

νμ (or UHE ντ) produces μ or τ via CC scatter. which can travel for many kilometers along linear track radiating Cherenkov photons in conical wavefront about track. The extended range of taus and muons means vertex can lie far outside detector volume – detector effective area is key performance parameter. Angular resolution of 1° is achievable with sophisticated maximum likelihood track reconstruction.

νe CC or νX NC nuclear interactions produce either EM or hadronic cascades. These produce enormous amounts of Cherenkov photons (108 photons per TeV) radiated over 4π. The extent of the cascade is ~10 m longer at UHE due to LPM. Detector effective volume is operational parameter for cascades. Good energy resolution – ice is caloric medium. Poor angular resolution

VHE ντ interacting inside the detector produces the primary recoil cascade and a τ which can propagate many 100’s of m at HE. τ decay produces a secondary cascade – leaving a very distinct event. Other topologies as well: “lollipop” and “sugar daddy.”

τ channel has no ATM background. UHE ντ fluxes can regenerate and are not absorbed by passage through Earth.


900 PeV cosmic ray event

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Atmospheric Neutrinos

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Energy and baseline of atmospheric neutrinos: able to probe regions of parameter space for Lorentz violation and quantum decoherence completely inaccessible

New techniques developed for unfolding the energy spectrum of atmospheric neutrinos – here from IC22 data.

D. CHIRKIN ICRC 2009

HEULSNITZ & KELLEY ICRC 2009


Point Sources

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Dumm ICRC 2009

½ year of IC40 data – 175.5 d live time17777 evts – 6796 up, 10981 down

I C E C U B E P R E L I M I N A R Y


Diffuse Neutrinos (IC22) Extraterrestrial neutrino flux harder than atmospheric

neutrinos – look for HE excess of events Tricky analysis – very sensitive to systematics in Monte

Carlo simulation IC22 diffuse results are just now being released (Hoshina

2009 ICRC) Use 3 ‘simple’ energy estimators– N c h : # of hit channels– Np e : integral of reconstructed Q from DOM waveforms– µ dE/dX : muon energy loss from photon tables

Nch and Npe showing significant excess at high multiplicity while µ dE/dX is consistent with atmopheric neutrino background

(Continuing) investigation of systematics associated with very primitive channel, charge counting

Limit from dE/dX analysis:

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Neutrinos from Gamma-Ray Bursts

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Search for high-energy muon neutrinos from the “naked-eye” GRB080319B with theIceCube neutrino telescope arXiV:0902.0131 accepted by ApJ

Right after deployment of the 40 strings last year the theoretically-visible-to-the-naked-eye GRB 080319B went off. Unfortunately IceCube was in maintenance mode at the time and only 9 strings were active.

• GRB fireball model predicts HE neutrinos from pγ interactions in GRB jet.

• Satellite-triggers (Fermi/SWIFT) used to pinpoint the burst search windows and reduce background (looser cuts possible)

http://arxiv.org/abs/0902.0131


Neutrino-tr iggered optical fol low-up

IceCube ‘trigger’ to optical network (ROTSE) on neutrino multiplet: 2 or more neutrino events inside 100 s and 4° space angle (25 accidentals / year for M=2)

Motivation: GRBs, gamma-poor bursts, SNe with jets and TeV neutrino emission

Program initiated end of 2008

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Dark Matter

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M EV NEUTRINO ASTRO -PARTICLE PH YS ICS WITH I CECUBE

Part I I I

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Supernovae

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• For star of mass > 8 M☉ it is possible to develop Fe core ~ 1.4 M☉.

• Burning of Fe not exothermic – core collapses under it’s own gravity.

• Almost all (99%) of gravitational energy of collapsing core is radiated away as neutrinos – approx 1053 erg.

• Not all supernovae are core collapse supernovae. Also Type Ia (used as standard candles in redshift measurements) which do not produce strong neutrino emission.

• Core collapse are Type Ib/c and Type II


Observation of neutrinos from SN1987A

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Detection of MeV ν’s from SNe

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Primary detection channel is inverse βdecay

Note this is only sensitive to the electron anti-neutrinos. Electron neutrinos (in particular those from the de-leptonization burst) detected primarily from o

rThe weak Cherenkov signal from any particular neutrino-nucleus interaction for IceCube-scale detector seen by at most one PMT. However, for sufficiently intense burst of finite duration, the counting rates of many such interactions recorded in many PMTs may be combined in manner to discriminate from background count rate.


IceCube DOM Effec t ive Volume (MeV neut r inos)

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Effective volume scales as photocathode area, attenuation length, and E3, thus dependent on temperature of SNe. We compute in E-independent manner the single photon eff volume, Veff,γ (note PMT response already folded into this expression): <Veff,γ> = 0.185 m3

• SNe models give <E3> ~ 15 MeV• One may easily derive approx

photon yield from positrons: 2500

• This gives per PMT, effective volume of 450 m3

• 2 Mton target mass for IC86

• 500,000 counts above background expected for SN1987A at galactic center

• cf. rms noise fluctuation of 3700

S/N = 130 : 1


Photon counting in IceCube

PMT counts pulse crossing discriminator threshold of 0.25 pe

DOM logic maintains virtual scalers: 4-bit counters with integration t ime 1.64 ms.

Edges of bins defined in DOM clock frame – translation to global t ime via RAPCal method

Introduction of artificial deadtime important to opt imize S/N in presence of optical art i facts: PMT after-pulsing and other late l ight effects.

The scalers from each channel col lected and sent to assembly phase where they are chronological ly sorted and then written to disk file (3 MB/sec) for– handoff to rea l t ime supernova a le r t

sys tem– permanent s to rage

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Supernova detect ion in real t ime

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Internally we generate multiple triggers per day for monitoring purposes. Of these, high significance triggers sent to SNEWS via 24/7 Iridium satellite messaging system.

SNEWS alert rate < 2 / week – average latency is approx. 10 min.

• Realtime supernova alert system at pole consumes data files emitted by DAQ system• Merge and globally align scaler bins coming from DOMs• Compute the following statistics to search for excess counts

SIGNAL + ERROR

BACKGROUND ELIMINATION


SNe ν’s as probes of the supernova explos ion mechanism

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• Various phases of evolution signaled by change in neutrino flux• infall• neutronization burst• accretion• cooling

• Theoretical models still have trouble producing explosion – neutrinos may be critical ingredient restarting the stalled shockwave

• For very massive stars > 25 M☉ supernova explosion may be interrupted by formation of a black hole: optical burst not present – neutrino fluxes characterized by increase in temperature and eventual truncation.


Part icle physics with SN ν

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Conclusions

Add these

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SUPPLEMENTARY MATERIAL

Backup please!

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RAPCal

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RAPCal Analog Waveform

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Neutrino Effective Area

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UHE Neutrino Cross Sections

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Tau neutrino events

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Neutrino Astrophysics with IceCube