https://doi.org/10.1051/epjconf/201713506005
Signal classification and event reconstruction for acoustic neutrino detection in sea water with KM3NeT
Friedrich-Alexander-Universität Erlangen-Nürnberg, Erlangen Centre for Astroparticle Physics, Erwin-Rommel-Str. 1, 91058 Erlangen, Germany
* e-mail: dominik.kiessling@fau.de
Published online: 15 March 2017
The research infrastructure KM3NeT will comprise a multi cubic kilometer neutrino telescope that is currently being constructed in the Mediterranean Sea. Modules with optical and acoustic sensors are used in the detector. While the main purpose of the acoustic sensors is the position calibration of the detection units, they can be used as instruments for studies on acoustic neutrino detection, too. In this article, methods for signal classification and event reconstruction for acoustic neutrino detectors will be presented, which were developed using Monte Carlo simulations. For the signal classification the disk–like emission pattern of the acoustic neutrino signal is used. This approach improves the suppression of transient background by several orders of magnitude. Additionally, an event reconstruction is developed based on the signal classification. An overview of these algorithms will be presented and the efficiency of the classification will be discussed. The quality of the event reconstruction will also be presented.
© The Authors, published by EDP Sciences, 2017
This is an Open Access article distributed under the terms of the Creative Commons Attribution License 4.0, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
