Issue |
EPJ Web of Conf.
Volume 295, 2024
26th International Conference on Computing in High Energy and Nuclear Physics (CHEP 2023)
|
|
---|---|---|
Article Number | 07013 | |
Number of page(s) | 8 | |
Section | Facilities and Virtualization | |
DOI | https://doi.org/10.1051/epjconf/202429507013 | |
Published online | 06 May 2024 |
https://doi.org/10.1051/epjconf/202429507013
Data handling of CYGNO experiment using INFN-Cloud solution
1 LIBPhys, Department of Physics, University of Coimbra, 3004-516 Coimbra, Portugal
2 Dipartimento di Matematica e Fisica, Università Roma TRE, 00146, Roma, Italy
3 Istituto Nazionale di Fisica Nucleare, Sezione di Roma Tre, 00146, Rome, Italy
4 Gran Sasso Science Institute, 67100, L’Aquila, Italy
5 Istituto Nazionale di Fisica Nucleare, Laboratori Nazionali del Gran Sasso, 67100, Assergi, Italy
6 Istituto Nazionale di Fisica Nucleare, Laboratori Nazionali di Frascati, 00044, Frascati, Italy
7 Dipartimento di Fisica, Università La Sapienza di Roma, 00185, Roma, Italy
8 Istituto Nazionale di Fisica Nucleare, Sezione di Roma, 00185, Rome, Italy
9 ENEA Centro Ricerche Frascati, 00044, Frascati, Italy
10 Centro Brasileiro de Pesquisas Físicas, Rio de Janeiro 22290-180, RJ, Brazil
11 Universidade Estadual de Campinas - UNICAMP, Campinas 13083-859, SP, Brazil
12 Universidade Federal de Juiz de Fora, Faculdade de Engenharia, 36036-900, Juiz de Fora, MG, Brasil
13 Department of Physics and Astronomy, University of Sheffield, Sheffield, S3 7RH, UK
14 Dipartimento di Ingegneria Chimica, Materiali e Ambiente, Sapienza Università di Roma, 00185, Roma, Italy
15 INFN-CNAF, Viale Carlo Berti Pichat 6/2, 40127 Bologna, Italy
16 Istituto Nazionale di Fisica Nucleare, Sezione di Perugia, 06123, Perugia, Italy
17 Istituto Nazionale di Fisica Nucleare, Sezione di Bari, 70125, Bari, Italy
* e-mail: giovanni.mazzitelli@lnf.infn.it
Published online: 6 May 2024
The INFN Cloud project was launched at the beginning of 2020, aiming to build a distributed Cloud infrastructure and provide advanced services for the INFN scientific communities. A Platform as a Service (PaaS) was created inside INFN Cloud that allows the experiments to develop and access resources as a Software as a Service (SaaS), and CYGNO is the betatester of this system. The aim of the CYGNO experiment is to realize a large gaseous Time Projection Chamber based on the optical readout of the photons produced in the avalanche multiplication of ionization electrons in a GEM stack. To this extent, CYGNO exploits the progress in commercial scientific Active Pixel Sensors based on Scientific CMOS for Dark Matter search and Solar Neutrino studies. CYGNO, like many other astroparticle experiments, requires a computing model to acquire, store, simulate and analyze data typically far from High Energy Physics (HEP) experiments. Indeed, astroparticle experiments are typically characterized by being less demanding of computing resources with respect to HEP ones but have to deal with unique and unrepeatable data, sometimes collected in extreme conditions, with extensive use of templates and montecarlo, and are often re-calibrated and reconstructed many times for a given data set. Moreover, the varieties and the scale of computing models and requirements are extremely large. In this scenario, the Cloud infrastructure with standardized and optimized services offered to the scientific community could be a useful solution able to match the requirements of many small/medium size experiments. In this work, we will present the CYGNO computing model based on the INFN cloud infrastructure where the experiment software, easily extendible to similar experiments to similar applications on other similar experiments, provides tools as a service to store, archive, analyze, and simulate data.
© The Authors, published by EDP Sciences, 2024
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.
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