Hydrophone based calibrator for seawater acoustic detection of UHE neutrinos Omar Veledar ACoRNE collaboration – University of Sheffield Sapienza Universitá.

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Presentation transcript:

Hydrophone based calibrator for seawater acoustic detection of UHE neutrinos Omar Veledar ACoRNE collaboration – University of Sheffield Sapienza Universitá Di Roma 25 – 27 June 2008

Outline Rona array DAQ Calibration Pinger development Deployment Future work

Rona hydrophone array North-West Scotland (ranging hydrophones) Good test bed for future deep sea experiments Existing infrastructure√ Wideband hydrophones√ Omnidirectionality√ Unfiltered data√ All data to shore√ Control over DAQ√ No remote accessX

Rona hydrophone array 8 hydrophones Low noise preamplifiers 1200m x 200m at mid depth in 230m deep sea Hydrophone positioning off during data readout

DAQ Offshore acquisition of amplified unfiltered data (16bit ±1.2 V, 1bit = μV = μPa) FLAC lossless compression (>50%) 8TB RAID interfacing to 16 tape autoloader LT03 tape robot (possible to relocate) Offline signal processing and analysis - unlimited data re-processing Quantum Superloader 3

Calibration - hydrophone Acoustic detection of UHE neutrinos relies on ability to calibrate hydrophones - bipolar acoustic pulse from single omnidirectional source Thermal energy resembling (shape and intensity) that of a neutrino induced shower should be deposited: array - interface pattern analogous to neutrino generated ‘pancake’ Other possibilities: Laser – interesting, but impractical Copper plate current discharge

Calibrator development - progression Laboratory tank Swimming pool Lake (Kelk) Open sea (Rona) Development

Calibrator development - tools Tx – omnidirectional ± 10kHzRx - flat frequency response

Know system and desired output to deduce required excitation pulse Convolution integral (t) y(t) = x(t) * h(t) - complicated Convolution (s) - freq. domain Y(s) = X(s). H(s) Inverse FFT y(t) = IFFT(Y(s)) Impulse response not practical use step response Step response = time integral of impulse response Signal generation - system (hydrophone) inputoutput system & output => excitation pulse Time domain Discrete time signal Impulse Step

Signal generation - signal d / dt step Hydro system H(t) o/p Imp. resp. Deconvolute i/p from sys. & o/p X(s) = Y(s) / H(s) Transform to time domain x(t) = IFFT(X(s)) RECIPE Find step response (of the transmit hydrophone) Generate system TF (model transmit hydrophone) Find excitation signal by deconvoluting required o/p and system TF

Pool – hydrophone modelling Hydrophone step response is recorded at various distances and dejittered

Hydrophone data fitting 5 th order TF used to model hydrophone TF: Mathematical representation of the relationship between the i/p and o/p of a LTI system

Technique verification

Excitation signal Desired acoustic pulse and the estimated hydrophone driving electrical signal Generates 10 1m

Pool - bipolar acoustic pulse Measured at various distances

Rona - field trip The joys of British “Summer”

Future work Repeat Rona deployment at different sea state and over different hydrophones using new excitation pulses An array development using 8 hydrophones Line array – acoustic pancake  Fully autonomous for great depths  Surface deployment => Power Amplifier, easy DAQ, (linearity?) Field data analysis

New excitation signal Restrictive by the hydrophone linearity potentially, can generate up to approximately 60 1m See Bevan et al. – parameterisation: more energy at core of the shower

Array hydrophone count 2 hydrophones 4 hydrophones 8 hydrophones 3 hydrophones 6 hydrophones 10 hydrophones

Array development Acquired RESON hydrophones Developed PIC based hydrophone control Array construction under way

Conclusions Understood and mathematically modelled hydrophone system Successfully generated bipolar acoustic pulses in laboratory and pool conditions Ongoing Rona data analysis Array development Pancake detection

Thank you Questions ?