C. Richardt

Signal classification for acoustic neutrino detection

Abstract This article focuses on signal classification for deep-sea acoustic neutrino detection. In the deep sea, the background of transient signals is very diverse. Approaches like matched filtering are not sufficient to distinguish between neutrino-like signals and other transient signals with similar signature, which are forming the acoustic background for neutrino detection in the deep-sea environment. A classification system based on machine learning algorithms is analysed with the goal to find a robust and effective way to perform this task. For a well-trained model, a testing error on the level of 1% is achieved for strong classifiers like Random Forest and Boosting Trees using the extracted features of the signal as input and utilising dense clusters of sensors instead of single sensors.

Position reconstruction of acoustic sources with the AMADEUS detector

This article focuses on techniques for position reconstruction of acoustic point sources with the AMADEUS setup consisting of 36 acoustic sensors in the Mediterranean Sea. The direction reconstruction of an acoustic point source utilizes the information of the six small-volume hydrophone clusters of AMADEUS individually. Source position reconstruction is then done by combining the directional information of each cluster. The algorithms for direction and position reconstruction are explained and demonstrated using data taken in the deep sea.

Development of combined Opto-Acoustical sensor Modules

Abstract The faint fluxes of cosmic neutrinos expected at very high energies require large instrumented detector volumes. The necessary volumes in combination with a sufficient shielding against background constitute forbidding and complex environments (e.g. the deep sea) as sites for neutrino telescopes. To withstand these environments and to assure the data quality, the sensors have to be reliable and their operation has to be as simple as possible. A compact sensor module design including all necessary components for data acquisition and module calibration would simplify the detector mechanics and ensures the long term operability of the detector. The compact design discussed here combines optical and acoustical sensors inside one module, therefore reducing electronics and additional external instruments for calibration purposes. In this design the acoustical sensor is primary used for acoustic positioning of the module. The module may also be used for acoustic particle detection and marine science if an appropriate acoustical sensor is chosen. First tests of this design are promising concerning the task of calibration. To expand the field of application also towards acoustic particle detection further improvements concerning electromagnetic shielding and adaptation of the single components are necessary.

Acoustic particle detection with the ANTARES detector

The (Antares Modules for Acoustic Detection Under the Sea) AMADEUS system within the (Astronomy with a Neutrino Telescope and Abyss environmental RESsearch) ANTARES neutrino telescope is designed to investigate detection techniques for acoustic signals produced by particle cascades. While passing through a liquid a cascade deposits energy and produces a measurable pressure pulse. This can be used for the detection of neutrinos with energies exceeding  eV. The AMADEUS setup consists of 36 hydrophones grouped in six local clusters measuring about one cubic meter each. This article focuses on acoustic particle detection, the hardware of the AMADEUS detector and techniques used for acoustic signal processing.