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ANTARES a Neutrino Telescopein the Mediterranean Sea

31/01/2014

Salvatore Mangano

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Outline

IntroductionResearch Projects ▪ Measurements - Shower reconstruction along muon - Velocity of light - Optical properties ▪ Searches - Gravitational lensing and neutrinos

Achievements/Conclusion

Salvatore Mangano

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2000 - 2001

OPERA

Oscillation Project with

Emulsion-tRacking Apparatus

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2001 - 2005

HERA (H1)

Hadron-Electron

Ring Accelerator

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2006 - 2013

ANTARES

Astronomy with a Neutrino Telescope and

Abyssal environmental RESearch

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ANTARES Collaboration

8 countries31 institutes~150 scientists

X ANTARES site

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ANTARES Detector

In Mediterranean Sea

40 km from Toulon 2.5 km under water

12 Lines (885 PMTs)

Line length ~450 m

Optimized for muonsat TeV energies

Taking high quality data since 2007

450

m

60 m

14.

5 m

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Neutrino Astronomy

Photon: Absorbed by interstellar medium and extragalactic background light (ɣ + ɣ ↔ e + e)

Proton:Deflected by magnetic field (E<1019 eV)and interact with CMB (E>1019 eV → 30 Mpc)

Neutrino: Interact weak (travel cosmological distances)Point back to source emissionSignature of hadronic processesDisadvantage → need large detector volume

Photon

Proton

Neutrino

Main Goal: Find cosmic neutrino sources

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Neutrino Detection

Neutrino

Charged CurrentInteraction

Muon

Cherenkov lightfrom muon

Detection lineswith PMTs

Reconstruction of muon trajectory from timing and positionof PMT hits

Cheap high quality sea water

Sea floor

Earth shielding rejects atmospheric muonsUpward going muon → neutrino candidate from Southern hemisphere

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ANTARES Basics

Detector

108 atmospheric muons per year

103 atmosphericneutrinos per year

??? cosmicneutrinos per year

??? exotic neutrinos per year

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Electromagnetic Showers along Muon Tracks

Salvatore Mangano

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Muon Energy Loss

Energy loss ~ (a + bE)

Below 1 TeV:

Continuous energy loss

Above 1 TeV:

Discrete energy loss

Large energy fluctuation Electromagnetic showers

waterwater

total

ionisation

pair production bremsstrahlungphotonuclear

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Shower Identification Method

Muon emits: continuously Cherenkov photons and sometimes discrete electromagnetic showers

Project photons onto reconstructed muon track

=>Search for clusters/peaks

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Algorithm

1. Reconstruct muon track

2. Calculate photon emission positions

Photons with early arrival times (|20 ns|):

Calculate photon vertex assuming emission underCherenkov angle

Photons with late arrival times (20-250 ns):

Calculate photon vertex assuming spherical emission

3. Search shower candidates with a peak finding algorithm

Data

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Photon Emission along MC Muon Track

all reconstructed emission points of the photons on muon trajectory

hits selected by the algorithm

positions of generated showers along the muon direction

Use MC to quantify performance of shower reconstruction

MC

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Vertical Downgoing Track

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Atmospheric Muon with Two Electromagnetic Showers

Idea: 1. Reconstruct muon trajectory 2. Project photons onto muon track 3. Peak signals shower position

Photon (+)Muon track (black line)Shower (red line)

Photon for track (■)Photon for shower (○)

Photons along track

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Shower Multiplicity

MC shows (Horandel):

Shower energy 0.5TeVMuon energy with shower 3.7TeVPosition resolution 5mShower Efficiency 5%Shower Purity 70%

No reconstruction efficiency used

Main systematic errors:Water absorption lengthPMT acceptance

Published inNIM A675 (2012) 56

Applications: Energy estimator, variable for cosmic-ray composition

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Velocity of Light

Salvatore Mangano

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Method

Pulse width 4 ns for LED and 0.8 ns for LaserFlash at a frequency of 330 Hz

1. Flash light with fixed λ from a given position2. Measure time when light reaches PMT → group velocity of light, refractive indexImportant for timing resolution (Angular resolution)

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Wavelength Spectra of Light Sources

Measured

Simulated at 120 m

Difference between spectra are due to variation of absorption length as a function of wavelength

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Fit Arrival Time at Photomultiplier

Arrival time distribution of each PMT fitted with functionwhich is a convolution of a Gaussian and an exponential.

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Arrival Time as Function of Distance

For one run wavelength = 469 nm

42 runs (data period 2008-2011)

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Velocity of Light in Sea Water

Published inAP 35 (2012) 9

Group velocity of light measured at eight different wavelengths in Mediterranean Sea at a depth of 2.2 km

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Optical Properties

Salvatore Mangano

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Absorption and Scattering Lengthas Function of Wavelength of Light

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Various models exist for absorption and scattering length.Crucial for detector performance.

Smith&Baker

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Method1. Take data with flashing optical beacon

- Plot the hit arrival time distributions for all OMs

2. Simulate many MC samples with different input values: λa and λs

3. Compare hit arrival time distributions from MC samples and data

4. Choose MC with λa and λs which describes best data

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Monte Carlo Samples • Simulation depends on two parameters: s and a

• Generate different MC input parameters, for example:a = 35, 40, 45, 50, 55, 60, 65, 70, 75 m 9 valuess = 35, 40, 45, 50, 55, 60, 65, 70, 75 m 9 values

9 times 9 = 81 MC samples for each data run

• Each generated MC run has his:– detector geometry– charge calibration – background noise – all OMs corrected by efficiency

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Histogram Comparison Compare time distributions from data and MC for many different OMs Calculate χ2 to quantify agreement between data and MC histograms

Data

λ_a = 55 m and λ_s = 50 m

MC describes better data

λ_a = 70 m and λ_s = 80 m

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Absorption vs. Scattering for Line 2

Calculate chi2 for each line and each MC template(in this case for Line 2 for 81 MCs)

Numbers give normalized chi2

Select MC model with minimal chi2

Cross check MC with MC

Errors are to small

Scattering length [m]35 75

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75

Abs

orpt

ion

leng

th [

m]

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Results

Take from lines the simulation with smallest chi2

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Gravitational Lensing and Neutrinos

Salvatore Mangano

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Full-Sky Point Source Search

Published inApJ 760 (2012) 53

ANTARES 2007-2010 data~3000 neutrino candidates (85 % purity)Angular resolution 0.5 +/- 0.1 degrees

No statistical significant signalBest cluster with 2.2σat (-46.5o, -65.0o)

Do we see neutrinos from space?

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Search from Selected Candidates

Gravitational lensing- Well-known prediction

of Einstein´s relativity (with many observations)

- Magnification of cosmic signals (higher fluxes)

- Same geodesic for photons and neutrinos

Advantage: Neutrinos not absorbed by lens

• Look at promising sources → Limit region of sky - Less general than full-sky → Improve sensitivity• Select galactic and extragalactic sources - Consider strong gamma-ray fluxes • Select neutrino sources behind powerful gravitational lens - Consider strong lenses with large magnification

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Galaxy and Quasar Lensed by Galaxy Cluster

Multiple images

Magnification for light between 1 and 100

Lens z= 0.68

Lens mass ~ 1014 Msun

Gravitational light deflection order of tenth of arcsec

Field of view: arcminAngular resolution → Point like for us → No multiple images, but magnification

Gamma emissionPKS1830, JVAS B0218

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Cosmic Neutrino SearchHow to tell there are cosmic neutrinos?(Likelihood ratio, calculate statistics from data)

Hypotheses: All neutrinos are atmospheric

Statistics

If you get this result=>Probably atmospheric neutrinos

Statistics

4 σ

If you get this result=>Cosmic neutrinos

If cosmic neutrinos exist

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Large separation quasar SDSS J1004+4112 is lensed by a galaxy cluster

Gravitational Lens: Best Cluster

X-ray image from Chandra project

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Neutrino Sky Map in Galactic Coordinates51 strong gamma-ray sources and 11 strong lenses

Data unblinding → no significant excess → set upper limits

▪ Neutrino event Strong ɣ-flux Strong lens

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Upper Limits on Neutrino Flux

Limits of ANTARES compared with other experiments

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Achievements/Conclusion• Experience in experimental neutrino astronomy and particle physics (OPERA, H1, ANTARES)

• Co-author of 70 publications

• Main author of two publications

• 15 presentations at international conferences PPC2013 (USA), Moriond 2013 (Italy), ICRC2013, ….

• 50 presentations at ANTARES meeting

• Develop innovative research lines

Salvatore Mangano

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Backup

Salvatore Mangano

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Cosmic “Neutrino” Acceleration• Photon astronomy exists with sources with E > TeV• Neutrinos possibly produced in interactions of high energy nucleons with matter or radiation

• If hadron acceleration: high energy nucleons + hadrons → mesons + hadrons → neutrinos and photons + hadrons

Photon energy ≈ Neutrino energy Photon flux ≈ 2 x Neutrino flux

• Neutrino sky has so far only 2 objects (MeV): 1. Sun 2. SN1987A (few seconds)

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Neutrino flux on Earth

(SN 1987A)

= measured

Water-Cherenkov Detectors in natural environments

Alternative techniques

Solar neutrino experiments

(other components arehypothetical)

Energy range ofNeutrino telescopes {

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Pure Proton Primaries or Pure Iron Primaries versus Data

No way to explain data with onlyproton or iron primaries

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Fit light and heavy nuclei to data

• High shower multiplicity dominated by heavy nuclei• Low shower multiplicity dominated by light nuclei• Fits says data contains 91% light and 9% heavy nuclei

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Gravitational Lens List

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Maximum likelihood search method:

A likelihood ratio is used as test statistics (λ):

Search method uses:1. event direction 2. number of hits in track fit 3. angular error estimate

Search Method

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P-value Calculation for Most Significant Event

Unblind => λobs

Compare λobs with λ distribution of only background case

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Skymap in Equatorial Coordinates of Selected Sources

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Upper Limits for Gravitational Lens Sources

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Upward Going Muons from Charged Current Neutrino Interactions

Cumulative distribution of reconstruction quality variablefor upgoing tracks (2007-2010)

Distribution of zenith angle withquality variable > -5.2 → ~3000 neutrino candidates

Tracks reconstructed by maximization of track likelihoodLikelihood = probability density of observed hit time residualsTime residuals = difference between observed and expected time

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Cosmic Point Source SearchAlgorithm for cluster search usesunbinned maximum likelihood method

In neutrino sky distinguish: - atmospheric neutrinos (background)

isotropic event distribution

- from cosmic neutrinos (signal)

event accumulation

Factor ~3 improved sensitivitycompared to previous result (2007+8 data) ApJL 743 (2011) L14 Main criteria for improvement:• More than twice the statistics• Energy information (gain of 20%)

Probability of discovering a source as a function of signal events (E-2)

For 5σ discovery:~9 events per source

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Full-Sky Hot-Spot

1o

3o

Most signal-like clusterin full-sky search:9 neutrino events in 3o

5 neutrino events in 1o

Likelihood fit assigns:5.1 signal events

Pseudo-Experiments:p-value 2.6%significance = 2.2σ

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Simulation of Gravitational LensingAnimation takenfrom Wikimedia

Simulation of gravitational lensingcaused by massiveobject going pastbackground galaxy

If background source, massive lensing object and observer aligned → Einstein ring