Bibliographic Details
| Title: |
Data handling of CYGNO experiment using INFN-Cloud solution |
| Authors: |
Amaro F.D., Antonacci M., Antonietti R., Baracchini E., Benussi L., Bianco S., Borra F., Calanca A., Capoccia C., Caponero M., Cardoso D.S., Cavoto G., Ciangottini D., Costa I.A., D’Imperio G., Dané E., Dho G., Di Giambattista F., Di Marco E., Duma C., Iacoangeli F., Lima Júnior H.P., Kemp E., Lopes G.S.P., Maccarrone G., Mano R.D.P., Marcelo Gregorio R.R., Marques D.J.G., Mazzitelli G., McLean A.G., Meloni P., Messina A., Monteiro C.M.B., Nobrega R.A., Pains I.F., Paoletti E., Passamonti L., Pellegrino C., Petrucci F., Piacentini S., Piccolo D., Pierluigi D., Pinci D., Prajapati A., Renga F., Roque R.J.d.C., Rosatelli F., Russo A., dos Santos J.M.F., Saviano G., Spiga D., Spooner N.J.C., Stalio S., Tesauro R., Tomassini S., Torelli S. |
| Source: |
EPJ Web of Conferences, Vol 295, p 07013 (2024) |
| Publisher Information: |
EDP Sciences, 2024. |
| Publication Year: |
2024 |
| Collection: |
LCC:Physics |
| Subject Terms: |
Physics, QC1-999 |
| More Details: |
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. |
| Document Type: |
article |
| File Description: |
electronic resource |
| Language: |
English |
| ISSN: |
2100-014X |
| Relation: |
https://www.epj-conferences.org/articles/epjconf/pdf/2024/05/epjconf_chep2024_07013.pdf; https://doaj.org/toc/2100-014X |
| DOI: |
10.1051/epjconf/202429507013 |
| Access URL: |
https://doaj.org/article/9b1691f2277249a998b42493de881645 |
| Accession Number: |
edsdoj.9b1691f2277249a998b42493de881645 |
| Database: |
Directory of Open Access Journals |
