High Energy Neutrino telescopes

Water Cherenkov detector: ANTARES, NESTOR, BAIKAL, KM3Net project, located in the Mediteranean and Baikal lake (Northern hemisphere) Ice Cherenkov detector: AMANDA, IceCube located at the South Pole (Southern hemisphere)

→ different FoV (uniform coverage of the northern sky at the South Pole and non uniform exposure but larger FoV in the Mediterranean) Northern hemisphere detectors have a direct view of the galactic center

Sky coverage in Galactc coordinates for a detector located in the Mediterranean Sea and at the South Pole. The shading indicates the visibility for a detector in the Mediterranean with 2π downward coverage; dark (light) areas are visible at least 75% Also systematics, mainly: (25%) of the tme. The locatons of recently observed sources of high energy γ‐rays are also indicated. - Light scattering properties of the medium: - Better pointing resolution in water (0.3o instead of 1o) (useful above TeV) - Better energy resolution is in ice (better calorimeter)

- Moving detector in large and uncontrolled background in the Mediterranean VS frozen detector in a medium with uneven properties at the South Pole 43 NT200+ Antares

NEMO Nestor

IceCube

44 λ λ detector depth abs scatt PMT Volume Energy range #OM [km] [m] [m] noise [km3] [GeV] rate [kHz] AMANDA 1.5 150 30 1 0.03 102-107 600 2002 ICECUBE 2 150 30 1 1 101.5-109 5000 2011 BAIKAL 1 25 50 1 0.01 103-107 228 (NT-200+) 1998 (2005) ANTARES 2.5 40 110 30 0.03 101.5-107 900 2008 NESTOR 4 40 110 30 15 (1 floor) NEMO 2 16 (4 floors) KM3NET ? 40 110 30 6 ? 101.5-109 ?

45 2004-05 1 1 IceTop array 2005-06 8 9 - 81 stations 2006-07 13 22 - 324 optical modules 2007-08 18 40 - Threshold: 300 TeV 2008-09 19 59 2009-10 20 79 2010 11 7 86

IceCube in-ice array - 86 strings - 5160 DOMS 1450 m - 60 / 125 m string spacing - 60 modules / string - 7 / 17 m between OM - 10 GeV < E < 10 EeV

2450 m

46 The IceCube digital optical module a complete data acquisition system

● signal digitization ● PMT gain and time calibration ● transmitting digital data to the surface ● power consumption: 3W ● deadtime < 1% ● dark noise rate < 400 Hz ● local Coincidence rate ~ 15 Hz Hamamatsu 10” (muons)

Waveform digitizers: ATWD: 3 channels, sampling rate 300 MSPS, capture 400 ns, nominal gain ratios 0.25:2:16 FADC: sampling rate 40 MSPS, capture 6.4 s Wide dynamic range: from single p.e. to 1000's p.e.

47 IceCube construction ended December 18, 2010

- 86 strings (inc. 8 Deep Core) + 81 IceTop stations - operating in its final configuration since May 2011

48 Cosmic ray events in the limited acceptance system IceTop – In-Ice array (0.3π km2 sr )

49 ~100 PeV primary cosmic ~100 TeV ν μ ray, ~ 300 muons in deep induced muon IceCube

50 Çoincident muons A difficult background, important in a large size detector

51 Moon shadow absolute pointing & resolution angular calibration

Expected event defcit from the directon of the moon seen with > 10σ

Systematc error on the pointng resoluton < 0.1 degree

G.W. Clark 1957 IC-59

52 Transparent detector medium South Pole ice characteristics

Essential to precisely characterize the ice characteristics ● MC description of exp. data ● Event reconstruction in IceCube sensitively depend on the optical properties of the ice!

A major and longstanding effort in IceCube

53 Transparent detector medium South Pole ice characteristics

Mie scattering on grains (lognormal distributed sizes): - Typical size r ~ μm > λ → scattering with weak dependence on λ - Typical distance between scattering O(m) >> λ → no interference - Scattering is strongly forward, characterized by

No known solution to the photon propagation from first principles in the regime considered → large statistics of photons are generated and propagated

→ light absorption (λabs) & scattering parameters (λscatt , ) as a function of depth (dust concentration) and wavelength λ are adjusted using:

● LED, laser light sources ● muons ● ‘Dust logger’

54 Transparent detector medium South Pole ice characteristics

The effective scattering length is the distance after which the photon direction is randomized (vanishing projected speed along the initial direction):

λeff = λscatt / (1 - )

→ reduction of the number of parameters

~100 m

~30 m

The IceCube MC relies on simulated “photon tables” built by propagating large numbers of photons for various event hypotheses (tracks and cascade parameters --> composite) 55 The Dust Logger

56 Are the dust layers horizontal?

57 Event reconstruction

Log likelihood minimization proceeds via the measurements of Cherenkov photon density and arrival time for a given event hypothesis

Following a hypothesis for the event topology (track, shower, composite), the photon time residuals (to which correspond a PDF) are calculated:

t = t - t ij ij, hit j,geo

th for the i photon number at sensor j (for a given hypothesis, tgeo is the time of arrival of an unscattered photon)

This PDF will in general depend on the sensor location & properties (quantum efficiency, angular sensitivity), emission point of the photon and surrounding ice (photon paths in a medium of variable scattering and absorption properties). 58 Event reconstruction: main difficulties

Limited information, inherent fluctuations and intrinsic noise Reconstruction hypothesis not matching the event - muon bundles with outliers, - bright stochastic cascades along a track - starting / stopping tracks - uncorrelated particle signatures (muons from independent air showers) Corner clipper events - muons traveling along a corner appearing as an up-going track Variability of - the ice characteristics in the fiducial volume, - the detector geometry (in water), Environmental noise - Bio-luminescence (in water), - radioactive decay (e.g. 40K)

59 Event reconstruction First guess

Analytical minimization LineFit: hit i recorded at time ti at location ri 2 r r v t 2  =∑i  − i i

The parameters are expressed:

〈r i ti 〉−〈r i 〉〈ti 〉 v= 2 2 〈ti 〉−〈ti 〉

{ ri , ti } r=〈ri 〉−v 〈ti 〉

Results are loose, often ambiguous. v It efficiently serves as a first guess reconstruction r “It ignores the geometry of the Cherenkov cone and the optical properties of the medium and assumes light traveling with a velocity v along a 1-dimensional path through the detector" 60 Event reconstruction geometric ambiguity

- Recorded amplitudes (p.e. multiplicity (geom/abs.)) { ri, ti } - 3D multiplicity (hits in more than a single string) - Scattering (introducing a delay ~ distance) helps remove the geometric ambiguity

This is the pathology affecting the misrecontructed corner-clipper events

2θC

61 Event reconstruction

Chisquare minimization: hit i recorded at time ti and expected at time ti

2 2 ti−ti  Aggouras et al., ApP 23 (2005) 377  =∑i 2 i

d d Ld tg   where t= m   = C c c/n c

Used in Mediterranean telescopes, where  scat ≫  abs i.e. Cherenkov light is direct (travel about unscattered).

In ice medium, the ice properties force to use more sophisticated likelihood minimization with an appropriate PDF for good results

62 Event reconstruction

The time residual PDF simplifies greatly assuming specific topologies (cascades, tracks) and takes the effective form:

p(d, t, θ) = ρξ tξ-1 e-ρt / Γ(ξ) f(θ) with parameters ξ = d/λ, ρ = c/λ + 1/τ tuned on the data / MC and θ the a relative angle between the cascade/track and the sensor axis.

p is the normalized solution of

once multiplied with an exponential damping factor, accounting for absorption and depending on the time delay.

To take into account for time resolution of the sensors, it is convoluted with a gaussian (the analytical solution exists, see astro-ph/0506136).

63 Event reconstruction In AMANDA / IceCube, the PDF are generalized for multi-photon recorded at sensor j (NIM A 524 (2004) 169):

p(d, {t} , θ) j i i=1..n

Good results are obtained by considering the simplified time residual PDF of the first out of n photons reaching sensor j: ∞ n−1 p d ,t , , n n p d , t , d t p d , t , j  1  = j  1  t j   ∫ 1 

Given a track/cascade hypothesis { t 0, r0, p} → set of {d}, {t}, {θ}.

The loglikelihood reads

ln = ln p(d, t , θ, n) L Σj j 1

for the incidence direction reconstruction.

This is approximate and this can be generalized to account for the energy reconstruction as well and to include the possibility of handling a PDF describing the coherent response from multiple sources (NIM A 574 (2007) 137). 64 Event energy reconstruction qualitative treatment

Energy reconstruction of contained tracks / cascades especially interesting: the neutrino energy can be assessed more precisely. For uncontained events, the energy reconstruction is a measure of the energy loss in the detector.

The prob. of recording n photons for a given energy E is f(d, θ, n, E), which can j be obtained by integrating p(d, t, θ) exp(-d/λ ) over t , a i ∞ p d ,t , exp d d t w−d ∫0   − /a  = The average number of photons at a sensor is proportional to w-d (q.e., etc.)

−d d , , E=a  , E w bnoise where b the detector / environment noise noise contribution. f(d, θ, n, E) is a Poisson distribution with number j of photon expectation μ(d,θ,E).

65 Event energy reconstruction qualitative treatment

Given a f (e.g from previous example or photon tables):

The loglikelihood reads

ln = ln f(d, θ, n) + ln f(d, θ, 0) L Σj, n>0 j Σj, n=0 j

for the energy reconstruction.

- ΔlogEμ=0.3 is reached with this simple algorithm.

- Better method, accounting for energy losses in Account for cascade events along cascades along the high energy muon tracks and the muon track (D. Chirkin) with an effective implemention of the ice depth-dep. min. ionizing characteristics, reach a resolution of nearly ΔlogEμ~0.1

66 Event observables

High level observables: essentially

- ln(Lcascade / Ltrack)

- ln(Levent) - resolution of the reconstructed parameters (from the analysis of the likelihood landscape in the neighborhood of the minimum), in particular the error on the directionality σ - partial / full LLH, with various set of sensors, of hits, of initial conditions (and consistency between reconstructed parameters)

Low level, filtering, hit cleaning:

Nhit, Nhit sensor Event sphericity / directionality Smooth light emission along a track Track length for various time residual windows Afterpulse and noise rejection: hits isolated in space and time ...

Analyses, sequential cuts or more sophisticated (combining observables in various multi-variate analysis schemes), either at high level to extract physics or at low level (filtering, to efficiently reduce the highly contaminated neutrino sample) 67 Steady point source Basic methodology: binned search at the South Pole

- At the very specific SP location: background is a function of declination δ only (θ ≡ δ and detector symmetry in R.A. α) - A source at a given location (δ,α), circular or square bin around the source of area a, defined by the the neutrino sample PSF at this declination - N events (neutrino candidates) in the declination band δ of area A → defines the bin background expectation

μbg = N p = N (a/A) bin → significance of an observation: from δ

the CDF �B of the binomial probability

PB(nobs; N, μbg) of observing nobs events in the search bin (in the absence of signal)

The significance can be set without relying on Monte Carlo (contrary to setting flux, where it is necessary to know the detector response in all detail)

Blindness during analysis (looking at a specific source): avoid any bias in the selection of the neutrino candidates → event selection optimization done off-source, using randomized α (equivalent to scrambling time) 68 Steady point source Basic methodology: binned search

Perform an actual measurement (below discovery threshold): 90% UPPER LIMIT

- For a given experimental outcome nobs, the true unknown signal flux lie below the 90% flux upper limit Φ (or μ in terms of number of events) in 90% of the 90 90 experiments (Neyman or Feldman-Cousin construction).

- Converting μ to Φ necessitates the Monte Carlo and assumes a spectrum 90 90

Tune or compare concurrent analyses, assess the detector potential before the actual measurement of nobs takes place): 90% average upper limit or SENSITIVITY

- Upper limits averaged for all possible outcomes nobs of an ensemble of experiments in the absence of true signal n ∞  obs   =  n ,  bg e−bg  90 bg ∑n =0 90 obs bg obs nobs !

69 Steady point source Basic methodology: binned search

5σ DISCOVERY FLUX in 50% of the experiments:

The binomial PDF defines the min. nobs for a detection at the 5σ C.L. given μbg : nobs,5σ.

The discovery flux is set by adding the right amount of signal μs to the binomial PDF

PB(μbg → μbg + μs), so that in 50% of the experiments, the outcome is nobs ≥ nobs,5σ

Building the Test Statistics distribution: �B(>nobs; N, μbg) Generate scrambled sky maps, with variable too weak signal: 5σ discovery flux in less than 50% experiments amount of signal (incl. none) nobs,5σ → fill the distribution for each map at

(δ,α) with nobs in the search bin 1 �B(

This is only illustrative: in this simple case, μs (sometimes referred to as μlds) defined such that:

nobs,5σ = nobs | �B (μbg, nobs) = ½ erfc(5/√2) (@ 5σ C.L) → μs | �B(μbg+μs, nobs,5σ) = ½ 70 Steady point source Unbinned search methodology a) Data modeled as a two component mixture of signal and background. b) Max. likelihood fit to the data used to determine the rel. signal contribution

a) Given N events (neutrino candidates) in the data set (see Braun et al., ApP. 29 (2008) 299), considering a source located at (α, δ) with spectral index γ, assumed to th contribute with ns events, the probability density of the i event n n s S 1− s B N i N i measured at location ( i , i ) with energy Ei and where Si and Bi are the signal and background PDF's:

S i=N s {i ,i } ∣ { , } ,i E E i ∣  ,i

B i=N atm i E Ei ∣ Atm ,i

- N S , prob. that the event originates from the source modeled as a 2D gaussian of width σi;

- N atm , angular PDF for atmospheric background (flat w.r.t. α);

- E describes the prob. of reconstructed energy Ei . 71 Prob. densities of the muon energy estimator for various simulated signal power laws and for data

Correlation between σi and the actual track reconstruction error ψi (simulated data)

N S : 2D gaussian angular PDF for

signal event i of width σi Space angle corresp. (σ from the paraboloid fit of the to the 2D gaussian i likelihood landscape in (θ,φ) space of the reconstructed event) is an estimator of the angular uncertainty

72 Steady point source Unbinned search methodology

b) Maximum likelihood on all events i ∈ {1, N }: N n n n , s 1 s n , L  s  = ∏i 1 S i   − B i   s  = [ N N ]

The test statistics (TS) distribution, commonly defined against the null hypohesis ns=0, L n =0  = −2 ln s n , [ L   s   ] is built over millions of randomized skies (in time).

Significance of an observation: IC-40: Abbasi et al., ApJ 732 (2011) 18. 1) Build the TS distribution: E-2 source compared to the binned search, = 45

substitute: nobs → {maximization, λ(n,�)} 2) The p-value associated to λ is the fraction of scrambled (time≡R.A.) data sets leading to 5σ higher TS values than λ λ defines the discovery flux; used in FC construct, the sensitivity and upper limit 73 λ Steady point source Unbinned search methodology

This formalism enables to study the resolution on � and the number of events required for discovery for various spectra

for 5σ C.L. discovery

error on �rec

74 Steady point source Unbinned search methodology

Complication: the trial factor. The analysis is repeated but on the global sky (sky location with best p-value IC-40 upper limit sky map contributes to the test statistics distribution) → post-trial p-value. The trial factor can be reduced by considering a catalogue with a restricted number of sources. p-values / 90% C.L. upper limits with IceCube: - Best for positive declination (northern sky) IC-40 p-value sky map - Degraded by 10-100 for sources located in the southern sky

75 Point source searches IceCube 40-string configuration

Angular resolution

Effective area for muon neutrinos

76 Point source searches methodology

Extending the methodology: - For GRB and/or periodic sources: same principle, but a new time-dep. factor term in the signal PDF is added, translating the transient nature of the emission (see e.g. Abbasi et al., PRL 106 (2011) 141101).

- Stacking source search to cumulate the signal from similar sources: signal weighted sum of signal, weights depending on e.g. on the source distances, on the different source acceptance)

- Extended source search: PSF PSF source distribution

77 Mediterranean sites

78 Attenuation length is strongly determined by the absorption length in sea water.

Scattering lengths are much longer than in the ice, between 100 and 300m → mainly direct photons are detected, providing therefore an excellent angular resolution in the Mediterranean, ~0.1o for high energy neutrinos

79 - The NESTOR project in the ionian sea. Currently a floor is operating (since 2003) at a depth of 3800m.

- At larger depth, exponential suppression of G. Aggouras et al., the atmospheric muon background, ApP 23 (2005) 377. largely enhancing the sensitivity

- Next step: deploy some additional floors + surrounding strings

Chisquare reconstruction based on geometric time 80 Mediterranean neutrino telescope ANTARES A 0.1 km2 neutrino telescope composed of - 12 lines consisting of 25 storeys deployed at depths between 2000 – 2400 m - anchored on the sea floor - subject to movement from deep sea currents - Each storeys equipped with a triplet of optical modules (OM) - OM equipped with 10'' PMTs - OM looking downward at 45o away from the axis - Signal digitization and pulse extraction at the storey - Optical fibers for group of 5 storeys to the seabed junction box, sent multiplexed in a single optical fiber to the shore via the 40 km cable (O(0.75 Gb/s) per TX line for a max. 350 kHz rate per OM) - String spacing of 60 m - Demultiplexing / event building / filtering in the counting house at the shore

81 82 Mediterranean neutrino telescope ANTARES Specific technical difficulties

Deployment / recovery

Sea currents → acoustic positioning system ● Emitter/receiver devices anchored on the sea floor and along the lines ● Conversion of acoustic transit time into distances from sound speed to measure storey location - accurate knowledge of the temperature, salinity and pressure required ● Combined with compass and tiltmeters on each storey for twist measurement

→ 10 cm precision achieved on the OM location and degree orientation

Bio-deposition and sedimentation have not been reported to be problematic

83 Mediterranean neutrino telescope ANTARES Specific technical difficulties

Backgrounds

● 40K β-decay:

40K 89% → 40Ca + e- (1.3 MeV) 40K 11% → 40Ar + e+ (0.5 MeV) ~30 kHz

● Bacterial bioluminescence ~30 kHz (rarely up to 70 kHz)

● Bioluminescence from bigger animals occasionally (seasonally) blinding the detector for long periods, in correlation with deep see currents - can be efficiently rejected but reduce lifetime

84 Antarès VS IceCube 40-strings: Competing for pure E-2 power law, no cutoff, for declination < –30o

δ=-30o

85 Mediterranean neutrino telescope KM3NET Project (TDR available on km3net.org)

- ~5-6 km3 instrumented volume, view on the galactic center (complementary to IceCube) - Three different string designs - Three possible sites

86 Design options for the detection unit mechanical s tructures :

horizontal extension of 6 m incorporates 6 optical modules storey comprised of a single multi‐PMT optical module

6 optical modules arranged in pairs, placed at a distance of 1.1 m from the centre

87 KM3NET performance, sensitivity & discovery potential

discovery Point source search selection sensitivity

×10-9

θkin

88 Dark matter

To explain galactic rotation curves, we introduce a local halo WIMP density: −2 −3  = 0.4 GeV c cm in corotation with the galaxy with a velocity dispersion

v = 300 km/s

→ number density

2 2 −4 500GeV /c −3 4 500 GeV/c −2 −1 n = 8⋅10 cm   = n v = 2⋅10 cm s  m    m      

89 Dark matter Neutralino number density & neutrino flux (Gaisser et al., Phys. Rept 258 (1995) 173)

Solar WIMP capture cross section (WIMP are gravitationally trapped by successive scatterings), under the assumption of a weak interaction exchange of a neutral weak boson 2 2 2 between the WIMP and a quark in the nucleon N = GF mN  /mZ msun 57 −41 2 sun = N = 1.2⋅10 × 0.5⋅10 cm mN 20 −1 2 → capture rate is cap =  sun = 1.2⋅10 s for m = 500 GeV/c

Neutrino production rate from dark matter origin annihilating in the center of the Sun (assuming equilibrium between WIMP capture and annihilation rates). Dominant annihilation channel into weak bosons,   WW   each producing muon neutrinos with a branching ratio around

10%, Eν = ½ Eχ → neutrino generation rate related to the capture 19 −1 rate:  = cap /10 = 1.2⋅10 s and the flux at earth is :

 −8 −2 −1  = 2 ≈ 0.5⋅10 cm s where d = 1 a.u. 4  d

90 Dark matter

About half of the neutrino energy is transferred to the muon (i.e. E ≈ 100 GeV , interaction inelasticity is approximately 50%), the neutrino-induced muon event rate in the IceCube neutrino telescope at the South Pole with a cross section of 1 km2 is therefore given −36 2 (   = 0.7⋅10 cm , R ≈ 300 m ) by: 10 −1 N event ≈ 10  N A ice   R ≈ 20 yr . - The atmospheric neutrino background is quite high at these « low » energies,

NBG ~ 2-3 / square degrees / yr

- The neutrino-induced muon flux from solar WIMP annihilation is quite diffuse (from kinematics of the interaction, the typical angle between the outgoing muon and the incoming neutrino is ~5o, much larger than the angular size of the Sun).

- Detection efficiency not best near horizon (where Sun is at SP)

- Higher WIMP masses: potential slowly (fading atmospheric neutrino background) degrades due the the decreasing statistics. - Lower WIMP masses: potental degrades (first slowly, down to mWIMP ~ 100 GeV and then quickly) due to the increasing atmospheric neutrino background, the reduced detector efficiency (identification of short muon tracks) and the decreasing neutrino interaction cross section σ p. 91 IceCube: Set limit on the muon flux from the Sun → neutrino production rate → neutralino annihilation rate → Solar capture rate → scattering cross section

Blue shaded area : models consistent with All AMANDA and IceCube data between 2001- accelerator (break below ~40 GeV) and 2008 (i.e. up to IC-40). The limit is situated cosmological (high mass break due to a relic somewhere between extreme bb & WW channels density overclosing the universe) constraints not excluded yet by direct searches. 92 Indirect dark matter detection neutrinos from annihilating neutralinos in the galaxy Probing the annihilation cross section

- χχ annihilation rate in the galaxy ∝ ρ2. - Secondary neutrinos travel toward the detector

Flux from a given direction Ψ (w.r.t. GC): d  〈 v 〉 d N   ∝ A J   d E 2 d E whereJ  ∝ ∫ d l 2 rl , is the integration of the annihilation rate along the line of sight J(Ψ), d N /d E Is the neutrino multiplicity on self-annihilation of a neutralino pair, 〈 A v 〉 the thermally averaged cross section.

Two types of analyses conducted in IceCube: - galactic anti-center VS the region above the IceCube horizon near the GC: low background, DM profile uncertainties and expected signal - GC, abundant background, large DM profile uncertainties and high expected signal

93 94 Core collapse Supernova end of life of a massive star

SN1987A in Large Magellanic Cloud: >20 neutrinos observed on Earth by IMB, BAKSAN & Kamiokande

Energy release of about 1057 neutrinos in the range 10 – 25 MeV which carry away 99% of the gravitational binding energy released 53 during the explosion, about 3 × 10 erg, over O(10 s) timescale

Φ ≈ (1015) ν /m2 νe O e

SN monitoring: this flux of neutrino may be detected by high energy neutrino telescopes in H2O medium from the coincident increase of the single PMT count rates for about 10 s, predominantly through inverse β-decay + p e n + e   with E e ≈ E 

95 Core collapse Supernova Current detection technique

● 20 MeV positrons in ice have a path length of 9 cm and emit 3750 Cherenkov photons which can be detected with ~7% Photon Detection Efficiency in IceCube (contrary to Mediterranean the background count rate is also small, quasi absent natural radioactivity, dominated by the PMT glass):

IceCube sensor positron effective volume: ~700 m3 @ 20 MeV

The cross section of 20 MeV neutrino: σ ≈ 2 ∙ 10-41 cm2 νep → ne+

3 18 nint = Na/9 proton targets per cm → λint = 1/σnint ≈ 10 cm 3 Pint/cm → N = V Φ / λ = 100 (per sensor) det eff νe int (or a rate increase of about 30 Hz per sensor over 3s)

→ 500'000 detected interactions in a km3 (3.5 Mton

effective volume) of ice (10 M☉, 10 kpc) → SN can be seen up to a distance of significant (5σ) statistical deviation of total

count rate, which is within 3 s: rtot = Nsensor x 3 s x rsensor → 5√rtot = 15000 This is equivalent to the number of detected interactions at d = 10 kpc x (N N / 5√r ) ~ 60 kpc sensor det tot 96 Core collapse Supernova Enhanced detection technique and prospects

Recording of multi-photon events by neighboring sensors: an intermediate step between current technique and full reconstruction.

The information gain may enable a partial characterization of the spectrum, possibly the localization for very nearby SN's (see astro- ph:1106.1937)

MeV resolution on the average energy at 10 kpc from the ratio of coincidental to single hits (prob. of coincidental hits increasing with average energy)

While the signal is much weaker, - also bears much lower noise count rate (order 102 Hz overall detector), coincidental time window of O(0.1 ms)

- dying muon background may spoil a fraction of the potential

97 Core collapse Supernova Status & Future

IceCube dedicated SN data acquisition system: - see a SN exploding at 70 kpc (precursor of the EM burst) - measure its light curve - trigger the SNEWS alert system

Event coincident hit detection: - IceCube does not have such a DAQ system implemented yet. - Similar effort ongoing in ANTARES, using sensor triplet coincidences (Kulikovskiy et al.)

Future: Routine detection of supernovae

- a highly regarded goal bearing a rich astroparticle physics program Kistler, Yüksel et al., (core collapse dynamics, neutrino hierarchy) arXiv:0810.1959

- challenging effective detection volume of O(few) Mton to reach out up to ~5 Mpc (1 SN / year)

→ Necessitates R&D for - deployment, M&O - photo-detectors, ... 98 Digression for geologist / seismologist Earth tomography with high energy neutrinos

Following Cavendish measuring the Earth density, current knowledge on Earth's interior is based on indirect methods based on the study of seismic wave propagation. Neutrinos provide concurrent and direct information on the Earth density: ● Earth is partially opaque at energies above ~10 TeV ● Few 100's of atmospheric neutrino will be detected above 10 TeV (muon reconstructed energy) per year in a cubic km

where (density ρ)

2Rcos  R rd r - f l d l  = ∫0   = ∫Rsin 2 2 1− R/r sin  is the integrated density along a chord 0

This relation f(θ) can be (analytically) inverted, providing a mean to measure ρ(r) . dl

θ After 10 years, a km3 neutrino telescope will distinguish between PREM and homogeneous detector (Gonzales-Garcia et al., PRL 100 (2008) 061802).

99 Diffuse atmospheric neutrino spectrum Unfolding of IC-40

- Find an observable y maximally correlated to Eν, e.g. ΔE in the detector

- Translate observable distribution p(y) into a spectrum dΦ/dEν

→ solve p(y) = A(E,y) dΦ/dEν(E) where A(E,y) is the response kernel, including effects related to interaction, propagation, and detector response (for the event sample at the final analysis level) - Extensive MC studies required to validate the method are necessary

energy 100 Extra-terrestrial neutrino sources diffuse flux of galactic neutrinos A guaranteed flux: CR protons interacting in the galactic disk with the ISM

- ISM density of order ρ = 1 proton / cm3 23 - Residence time at energies between 0.1-1 PeV ~1 Myr or Lres = ct = 3⋅10 cm (Codino/Plouin, ICRC 2003) - pp cross section σ ~ 10-25 cm2 pp ν E → Lint = 1/σ ρ = 1025 cm > pp → optical depth: τ = Lres/Lint = 1/30 pp

→ ν flux is related to the CR flux: Gabici et al., ApP 30 (2008) 180. 3 dΦ /dE (E ) = τ dΦ /dE (E ) Rate in a km telescope ν ν ν pp p p p

where Eν ≅Ep / 30 (Kelner et al., PRD 74 (2006) 034018)

(See Gaisser et al., Phys. Rept 258 (1995) 173 for an alternative derivation) i.e. the diff. neutrino flux around 10 TeV is 10-5 the proton flux (assumed to have spectral index 2.7). This represents O(1-10) events / yr in a km3 telescope above 10 TeV, where this component may start to dominate over the atmospheric neutrino component. 101 Neutrino telescopes status No sources of high energy extraterrestrial neutrinos found as of today

Full sky coverage (ANTARES & IceCube)

Recent sensitivity increase from - great progress realized with data taking and analyses techniques, this research field has gained maturity - detector size cubic km in place

Neutrino telescopes: not only a tool for neutrino astronomy but also - competing with -ray / CR for indirect search for dark matter - atmospheric neutrino beam studies (particle physics, neutrino physics) - cosmic ray detection 10 TeV – 1 EeV (anisotropy, composition, spectrum)

Exciting projects ahead - KM3Net multi cubic km - 30 Mt low energy extension (MeV neutrino burst from SN, GeV neutrinos) - based on the radio detection technique for UHE / GZK neutrinos 102