Status and Recent Results of the Acoustic Neutrino Detection Test System AMADEUS Robert Lahmann for the ANTARES Collaboration ARENA 2010, Nantes, 02-July-2010 1 1

Overview of ANTARES and AMADEUS Outline Overview of ANTARES and AMADEUS Mediterranean Sea: Acoustic Properties and Background Ambient Noise Source Direction Reconstruction Work in Progress Conclusions 2 2

Overview of ANTARES and AMADEUS 3

Goals of AMADEUS Main objective: feasibility study for a potential future large-scale acoustic neutrino detector Goals to this end: Long-term background investigations Investigation of background correlations (transient/ambient) Development and tests of data filter and reconstruction algorithms Investigation of different types of acoustic sensors and sensing methods Studies of hybrid (acoustic and optical) detection methods

ANTARES 12 lines with up to 25 storeys each; total of 885 PMTs ANTARES 2500m depth Cable ~2m 12 lines with up to 25 storeys each; total of 885 PMTs + Instrumentation Line (IL07) Positioning system: Acoustic emitter (“pinger”) at anchor of each line Completed 30-May-2008

Principles of Optical and Acoustic Neutrino Detection  Acoustic sensor (hydrophone) array PMT array optical Cherenkov cone cascade  acoustic pressure waves  Cherenkov detector PMT distances in 3D Array: Given by attenuation length (~60m for blue light) Media: water, ice Acoustic detector Sensor distances in 3D Array: ~200m, given by signal geometry (“pancake”) Media: water, ice, homogeneous solids (e.g. salt domes) drawing courtesy L. Thompson (adapted)

Setup of Acoustic Storey with Hydrophones Hydrophone: Piezo sensor with pre-amplifier and band pass filter in PU coating Typical sensitivity: -145 dB re 1V/Pa ~10cm Titanium cylinder with electronics 3 custom designed Acoustic ADC boards 16bit @ 250kHz 7 7 7

AMADEUS Setup 34/36 sensors operational Continuous data taking with ~90% uptime Full detector capabilities (time synchronisation, DAQ,…) Operation started 30-May-2008 Operation started 5-Dec-2007

Piezo sensors + preamplifiers Acoustic Modules Piezo sensors + preamplifiers Design allows for integration of acoustic sensors into same housing of photo sensors → See talk by A. Enzenhöfer 9 9 9 9 9 9

The Onshore Filter System Task: Reduce incoming data rate of ~1.5 TByte/day to ~10 GByte/day System very flexible Local clusters (storeys) advantageous for fast (on-line) processing 10 10

Mediterranean Sea: Acoustic Properties and Background

Instantaneous heating, followed by slow cooling hadronic cascade ≈10m ≈1km  Reminder: Acoustic Signals from Neutrinos Temperature Instantaneous heating, followed by slow cooling Ecasc= 1 EeV @ 1km Adapted from arxiv/0704.1025v1 (Acorne Coll.) 12 12 12

Properties of the Mediterranean Sea (ANTARES site) Speed of sound depends on temperature, salinity, pressure (depth); temperature gradient only relevant up to ~100m below surface

Refraction of Signals Reaching AMADEUS “Open water model”: Using conditions of ANTARES site for complete volume of the simulation Furthest signals from surface to reach AMADEUS: ~30 km distance, J ~ -5.5° arrival angle

Bipolar Pressure Signals (BIPs) Acoustic Background in the Sea Random noise Bipolar (BIP) events Bipolar Pressure Signals (BIPs) Have to measure rate of BIP events: A Adapted fr. astro-ph/0104033 (Lehtinen et al.) One hydrophone in principle sufficient Hydrophone synchronisation not crucial Hydrophone array required Hydrophone synchronisation crucial Determines intrinsic energy threshold Determines fake neutrino rate 15 15 15

Ambient Noise

Ambient Noise: Analysis Method One sensor on IL07 evaluated from 2007-12-05 to 2010-01-22 (~ 2 years) total of 18462 minimum bias samples (~10s each) recorded Removing samples with large components at high frequencies (e.g. “pingers“) and non-gaussian distributions: 13909 samples (75.4%) remaining Integrate noise PSD from 1 to 50kHz

Ambient Noise: Daily Variation Strong variations over a day; most likely due to shipping traffic

Ambient Noise: Statistical Distribution 95% of time noise level is below Median: ≈ 17 mPa Assuming a constant sensor sensitivity of -145 dB re 1V/µPa (lab calibration), the mean noise level is 25 mPa +2 -2 +7 -5

Ambient Noise: Conclusion 95% of time background is better than (~50 mPa) for f = 1 to 50 kHz Assume detection threshold for bipolar signals of S/N = 2: Pthd = 100 mPa  Ethd ≈ 10 EeV More precise measurements to follow (e.g. bandwidth not optimised) Good conditions for neutrino detection (stable threshold, level as expected) expect BIP rate to determine threshold

Source Direction Reconstruction 21 21

Treatment of Neutrino-like (Triggered) Events Calibrate positions of acoustic sensors Reconstruct source directions of BIP signals Combine direction reconstructions to position reconstructions Define fiducial volume Count BIP point sources in volume for different pressure ranges

Position Reconstruction with Hydrophones IL07 L12 Receive signals from emitters on anchors of the 13 lines Reconstruct position of each hydrophone individually using

Position Reconstruction: Angular Resolution Position Reconstruction works excellently Challenge: systematic errors Estimate of systematic error so far: Sufficient for source position reconstruction

Source Direction Reconstruction Formula Pic with Threshold minimize Error: ~3° in φ, < 1° in J 25 25 25

AMADEUS - Source Direction Distribution Direction reconstruction for one storey All types of transient signals included, sea mammals, ships etc. Origin points north to horizon 26 26

AMADEUS - Source Direction Distribution

Work in Progress 28 28

Further Steps Measure density of sources as a function of energy; Subject of Ph.D. thesis C. Richardt; first insights: Fiducial volume must exclude surface “naive” BIP rate from trigger too simple; Need more sophisticated classification → Poster by Max Neff MC simulations tune event classification (  selection, backgr. discrimination) Determine efficiency for neutrino flux Feasibility Study Simulate fake neutrino rate for arbitrary detector design

First Simple Simulations within Framework Use SeaTray framework of KM3NeT/ANTARES, adapted from IceTray framework of IceCube Collaboration  Modular framework, designed for neutrino detection experiments

Conclusions AMADEUS performance is excellent The AMADEUS system has all features of an acoustic neutrino telescope (except size) Can be used as a multi purpose device (studies of neutrino detection, positioning, marine science) Ambient background stable, level as expected Observe very diverse transient background, signal classification crucial Current focus: Work on MC simulations Funded by: 31 31