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

Amaro, F D; Antonietti, R; Baracchini, E; Benussi, L; Bianco, S; Borra, F; Capoccia, C; Caponero, M; Cardoso, D S; Cavoto, G; Costa, I A; D’Imperio, G; Danè, E; Dho, G; Di Giambattista, F; Di Marco, E; Iacoangeli, F; Kemp, E; Lima Júnior, H P; 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; Petrucci, F; Piacentini, S; Piccolo, D; Pierluigi, D; Pinci, D; Prajapati, A; Renga, F; Roque, R J d C; Rosatelli, F; Russo, A; Saviano, G; Spooner, N J C; Tesauro, R; Tomassini, S; Torelli, S; Tozzi, D; dos Santos, J M F

doi:10.1088/1361-6501/acf402

Cited by 3 publications

(1 citation statement)

References 16 publications

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“…The typical DAQ event size is 12MB and the data rate is determined by the ability to shield the beta/gamma background, that in LIME, with its 50 liters of sensitive volume, is today about 1Hz. The surviving beta/gamma background has to be discriminated by the reconstruction and analysis software [8,9], in order to identify possible nuclear recoils. The reconstruction software applies a set of thresholds, filters and clusterization algorithms producing subsets of data each containing single track events information.…”

Section: Requirementsmentioning

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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Section: Requirementsmentioning

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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HypeX: high yield polarimetry experiment in x-rays

Fiorina,

Baracchini,

Dho

et al. 2024

X-Ray, Optical, and Infrared Detectors for Astronomy XI

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We present the development of a large-volume, increased field-of-view Time Projection Chamber (TPC) for X-ray polarimetry, utilizing a triple-GEM detector with optical readout. Initially optimized for directional Dark Matter searches, this system employs a scientific CMOS (sCMOS) camera and a PMT to detect secondary scintillation light produced during the TPC amplification stage. A prototype TPC with a cylindrical active volume of radius 3.7 cm and height 5 cm was tested at the INAF-IAPS calibration facility in Rome, Tor Vergata to establish the instrument's sensitivity to low-energy electron direction. Complete reconstruction of electrons in the 10-60 keV range with angular resolution down to 15°was measured, resulting in inferred modulation factors up to 0.9. We will present the initial results from our test campaign, which confirm effective photoelectron tracking in the tens of keV range with a strong modulation factor. This innovative approach could extend X-ray polarimetry sensitivity to higher energies and possibly enable the observation of rapid transient phenomena, such as Gamma Ray Bursts (GRBs) and solar flares, thus contributing significantly to X-ray astronomy.

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qCLUE: a quantum clustering algorithm for multi-dimensional datasets

Gopalakrishnan,

Dellantonio,

Di Pilato

et al. 2024

Front. Quantum Sci. Technol.

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Clustering algorithms are at the basis of several technological applications, and are fueling the development of rapidly evolving fields such as machine learning. In the recent past, however, it has become apparent that they face challenges stemming from datasets that span more spatial dimensions. In fact, the best-performing clustering algorithms scale linearly in the number of points, but quadratically with respect to the local density of points. In this work, we introduce qCLUE, a quantum clustering algorithm that scales linearly in both the number of points and their density. qCLUE is inspired by CLUE, an algorithm developed to address the challenging time and memory budgets of Event Reconstruction (ER) in future High-Energy Physics experiments. As such, qCLUE marries decades of development with the quadratic speedup provided by quantum computers. We numerically test qCLUE in several scenarios, demonstrating its effectiveness and proving it to be a promising route to handle complex data analysis tasks – especially in high-dimensional datasets with high densities of points.

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

Cited by 3 publications

References 16 publications

Data handling of CYGNO experiment using INFN-Cloud solution

Data handling of CYGNO experiment using INFN-Cloud solution

HypeX: high yield polarimetry experiment in x-rays

qCLUE: a quantum clustering algorithm for multi-dimensional datasets

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