50 litres TPC with sCMOS-based optical readout for the CYGNO project

Mazzitelli, G.; Domingues, F. Amaro; Baracchini, E.; Benussi, L.; Bianco, S.; Capoccia, C.; Caponero, M.; Cardoso, Danilo Santos; Cavoto, G.; Cortez, A.F.V.; Costa, I. A.; Dané, E.; Dho, Giorgio; Giambattista, Flaminia Di; Marco, E. Di; D'imperio, Giulia; Iacoangeli, F.; Lima, H.P.; Lopes, G. S.; Maccarrone, G.; Mano, R.D.P.; Gregorio, Robert Renz Marcelo; Marques, David José Gaspar; McLean, Alasdair Gregor; Messina, A.; Monteiro, C. M. B.; Nobrega, R. Antunes; Pains, Igor Fonseca; Paoletti, E.; Passamonti, L.; Pelosi, Sandro; Petrucci, F.; Piacentini, Stefano; Piccolo, D.; Pierluigi, D.; Pinci, D.; Prajapati, A. K.; Renga, F.; Riggio, C.; Rodano, A.; Roque, Rita Joanna da Cruz; Rosatelli, F.; Russo, A.; Santos, J. M. F. dos; Saviano, G.; Spooner, N. J. C.; Tesauro, Roberto; Tomassini, S.; Torelli, Samuele; Tozzi, D.

doi:10.1016/j.nima.2022.167584

Cited by 3 publications

(2 citation statements)

References 7 publications

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“…All studies presented in this paper have been carried out with the newest CYGNO detector, the LIME [7,8]. A sketch of this detector is shown in figure 1.…”

Section: Long Imaging Module (Lime) Detectormentioning

confidence: 99%

Directional iDBSCAN to detect cosmic-ray tracks for the CYGNO experiment

Amaro,

Antonietti,

Baracchini

et al. 2023

Meas. Sci. Technol.

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The CYGNO experiment aims to study rare events related to the search for low-mass Dark Matter and solar neutrino events. One of the main components of background comes from cosmic rays that generate long tracks in the detector's images. The interaction of such particles with the gas releases a variable energy profile along its trajectory to form tracks with multiple cores that can be easily reconstructed erroneously by being split into more than one cluster. Thus, this work offers a newly adapted version of the well-known DBSCAN algorithm, called iDDBSCAN, which exploits the directional characteristics of the clusters found by the DBSCAN to improve its clustering efficiency when dealing with multi-core tracks. A description of this algorithm is given in this paper, including validation of its parameters and assessment of its impact when included in the event selection routine of the experiment. To generate background events, data acquisition was performed with the detector installed in an overground laboratory, leaving it exposed to natural radiation. As a signal of interest, important to characterize many aspects of the detection system in the low energy region, a 55Fe source was used. The achieved results showed that the iDDBSCAN algorithm is capable of improving the background rejection of the experiment, through a more accurate reconstruction of the tracks produced by natural radiation such as cosmic rays, without deteriorating its signal detection efficiency and energy estimation.

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“…All studies presented in this paper have been carried out with the newest CYGNO detector, the LIME [7,8]. A sketch of this detector is shown in figure 1.…”

Section: Long Imaging Module (Lime) Detectormentioning

confidence: 99%

Directional iDBSCAN to detect cosmic-ray tracks for the CYGNO experiment

Amaro,

Antonietti,

Baracchini

et al. 2023

Meas. Sci. Technol.

View full text Add to dashboard Cite

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“…CYGNO group is ending the R&D phase with a prototype, called LIME [7], installed at LNGS, and has been funded by INFN and EU with the INITUM grant, to realize a demonstrator whose installation is scheduled for 2025 to prove that the technology is mature for the construction of O(30m 3 ) detector able to perform physics measurements (see fig. 1).…”

Section: Introductionmentioning

confidence: 99%

Data handling of CYGNO experiment using INFN-Cloud solution

Amaro,

Antonacci,

Antonietti

et al. 2024

EPJ Web of Conf.

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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.

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