EPJ Web Conf.
Volume 136, 2017RICAP16, 6th Roma International Conference on Astroparticle Physics
|Number of page(s)||4|
|Published online||23 March 2017|
The pLISA project in ASTERICS
1 Istituto Nazionale di Fisica Nucleare (INFN), Sezione di Roma
2 Dipartimento di Fisica “E. R. Caianiello”, Università di Salerno
3 Istituto Nazionale di Fisica Nucleare (INFN), Gruppo Collegato di Salerno
Published online: 29 March 2017
In the framework of Horizon 2020, the European Commission approved the ASTERICS initiative (ASTronomy ESFRI and Research Infrastructure CluSter) to collect knowledge and experiences from astronomy, astrophysics and particle physics and foster synergies among existing research infrastructures and scientific communities, hence paving the way for future ones. ASTERICS aims at producing a common set of tools and strategies to be applied in Astronomy ESFRI facilities. In particular, it will target the so-called multi-messenger approach to combine information from optical and radio telescopes, photon counters and neutrino telescopes. pLISA is a software tool under development in ASTERICS to help and promote machine learning as a unified approach to multivariate analysis of astrophysical data and signals. The library will offer a collection of classification parameters, estimators, classes and methods to be linked and used in reconstruction programs (and possibly also extended), to characterize events in terms of particle identification and energy. The pLISA library aims at offering the software infras tructure for applications developed inside different experiments and has been designed with an effort to extrapolate general, physics-related estimators from the specific features of the data model related to each particular experiment. pLISA is oriented towards parallel computing architectures, with awareness of the opportunity of using GPUs as accelerators demanding specifically optimized algorithms and to reduce the costs of pro cessing hardware requested for the reconstruction tasks. Indeed, a fast (ideally, real-time) reconstruction can open the way for the development or improvement of alert systems, typically required by multi-messenger search programmes among the different experi mental facilities involved in ASTERICS.
© The Authors, published by EDP Sciences, 2017
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