arXiv subjects

A. Triossi

Publications and source records attributed to A. Triossi.

10 recordsLinked to original sources

arXiv2026

Real-Time Wiener Deconvolution for feature reconstruction in JUNO

In particle physics, experiments generate substantial amounts of data that can be difficult to process without preliminary scaling. To avoid losing potentially crucial data, experimental collaborations are studying novel techniques for real-time data processing to extract features for further physics analysis. A common approach, especially in neutrino physics, is to use FPGAs for data acquisition and pre-processing. This paper presents an advanced Real-Time Wiener deconvolution algorithm designed to leverage the processing capabilities of the FPGA integrated into the readout boards of the Jiangmen Underground Neutrino Observatory (JUNO). The goal is to enable real-time reconstruction of the signal generated by photomultiplier tubes (PMTs) when neutrino interactions are detected. By exploiting online reconstruction of the signal generated by PMTs, we expect to improve the detection of low-energy depositions, such as those produced by transient astrophysical phenomena. These depositions are usually not saved because of the significant background that affects the low end of the energy spectrum, which would result in a large trigger rate, hence a large amount of data required for storage. This paper presents the features of the algorithm, including its ability to manage high-throughput data streams with minimal latency, adaptability, and resilience in discerning the characteristics of input data. Performance is evaluated on a JUNO electronic board. This study further demonstrates the potential of FPGA-based solutions for neutrino physics.

physics.ins-det↗

arXiv2025

A Latency-Constrained, Gated Recurrent Unit (GRU) Implementation in the Versal AI Engine

This work explores the use of the AMD Xilinx Versal Adaptable Intelligent Engine (AIE) to accelerate Gated Recurrent Unit (GRU) inference for latency constrained applications. We present a custom workload distribution framework across the AIE's vector processors and propose a hybrid AIE - Programmable Logic (PL) design to optimize computational efficiency. Our approach explores the parallelization over the rows of the matrices by utilizing as many of the AIE vectorized processors effectively computing all the elements of the resulting vector at the same time, an alternative to cascade stream pipelining.

cs.PF↗

arXiv2025

NUMEXO2: a versatile digitizer for nuclear physics

NUMEXO2 is a 16 channels 14bit/200MHz digitizer and processing board initially developed for gamma-ray spectroscopy (for EXOGAM: EXOtic nuclei GAMma ray). Numexo2 has been gradually extended and improved as a general purpose digitizer to fulfill various needs in nuclear physics detection at GANIL. This was possible thanks to reprogrammable components like FPGAs and the optimization of different algorithms. The originality of this work compared to similar systems is that all numerical operations follow the digital data flow from ADCs, without any storage step of samples. Some details are given on digital processing of the signals, delivered by a large variety of detectors: HPGe, silicon strip detector, ionisation chamber, liquid and plastic scintillators read-out with photomultipliers, Multi Wire Proportional Counter and drift chamber.

physics.ins-det↗

arXiv2024

Interpretable machine learning approach for electron antineutrino selection in a large liquid scintillator detector

Several neutrino detectors, KamLAND, Daya Bay, Double Chooz, RENO, and the forthcoming large-scale JUNO, rely on liquid scintillator to detect reactor antineutrino interactions. In this context, inverse beta decay represents the golden channel for antineutrino detection, providing a pair of correlated events, thus a strong experimental signature to distinguish the signal from a variety of backgrounds. However, given the low cross-section of antineutrino interactions, the development of a powerful event selection algorithm becomes imperative to achieve effective discrimination between signal and backgrounds. In this study, we introduce a machine learning (ML) model to achieve this goal: a fully connected neural network as a powerful signal-background discriminator for a large liquid scintillator detector. We demonstrate, using the JUNO detector as an example, that, despite the already high efficiency of a cut-based approach, the presented ML model can further improve the overall event selection efficiency. Moreover, it allows for the retention of signal events at the detector edges that would otherwise be rejected because of the overwhelming amount of background events in that region. We also present the first interpretable analysis of the ML approach for event selection in reactor neutrino experiments. This method provides insights into the decision-making process of the model and offers valuable information for improving and updating traditional event selection approaches.

physics.ins-det↗

arXiv2024

Distillation and Stripping purification plants for JUNO liquid scintillator

The optical and radiochemical purification of the scintillating liquid, which will fill the central detector of the JUNO experiment, plays a crucial role in achieving its scientific goals. Given its gigantic mass and dimensions and an unprecedented target value of about 3% @ 1 MeV in energy resolution, JUNO has set severe requirements on the parameters of its scintillator, such as attenuation length (Lat>20 m at 430 nm), transparency, light yield, and content of radioactive contaminants (238U,232Th<10-15 g/g). To accomplish these needs, the scintillator will be processed using several purification methods, including distillation in partial vacuum and gas stripping, which are performed in two large scale plants installed at the JUNO site. In this paper, layout, operating principles, and technical aspects which have driven the design and construction of the distil- lation and gas stripping plants are reviewed. The distillation is effective in enhancing the optical properties and removing heavy radio-impurities (238U,232Th, 40K), while the stripping process exploits pure water steam and high-purity nitrogen to extract gaseous contaminants (222Rn, 39Ar, 85Kr, O2) from the scintillator. The plant operating parameters have been tuned during the recent com- missioning phase at the JUNO site and several QA/QC measurements and tests have been performed to evaluate the performances of the plants. Some preliminary results on the efficiency of these purification processes will be shown.

physics.ins-det↗

arXiv2024

Refractive index in the JUNO liquid scintillator

In the field of rare event physics, it is common to have huge masses of organic liquid scintillator as detection medium. In particular, they are widely used to study neutrino properties or astrophysical neutrinos. Thanks to its safety properties (such as low toxicity and high flash point) and easy scalability, linear alkyl benzene is the most common solvent used to produce liquid scintillators for large mass experiments. The knowledge of the refractive index is a pivotal point to understand the detector response, as this quantity (and its wavelength dependence) affects the Cherenkov radiation and photon propagation in the medium. In this paper, we report the measurement of the refractive index of the JUNO liquid scintillator between 260-1064 nm performed with two different methods (an ellipsometer and a refractometer), with a sub percent level precision. In addition, we used an interferometer to measure the group velocity in the JUNO liquid scintillator and verify the expected value derived from the refractive index measurements.

physics.ins-det↗

arXiv2023

Analysis of reactor burnup simulation uncertainties for antineutrino spectrum prediction

Nuclear reactors are a source of electron antineutrinos due to the presence of unstable fission products that undergo $\beta^-$ decay. They will be exploited by the JUNO experiment to determine the neutrino mass ordering and to get very precise measurements of the neutrino oscillation parameters. This requires the reactor antineutrino spectrum to be characterized as precisely as possible both through high resolution measurements, as foreseen by the TAO experiment, and detailed simulation models. In this paper we present a benchmark analysis utilizing Serpent Monte Carlo simulations in comparison with real pressurized water reactor spent fuel data. Our objective is to study the accuracy of fission fraction predictions as a function of different reactor simulation approximations. Then, utilizing the BetaShape software, we construct fissile antineutrino spectra using the summation method, thereby assessing the influence of simulation uncertainties on reactor antineutrino spectrum.

physics.ins-det↗

arXiv2021

Muon detection in electron-positron annihilation for muon collider studies

The investigation of the energy frontier in physics requires novel concepts for future colliders. The idea of a muon collider is very appealing since it would allow to study particle collisions at up to tens of TeV energy, while offering a cleaner experimental environment with respect to hadronic colliders. One key element in the muon collider design is the low-emittance muon production. Recently,the Low EMittance Muon Accelerator (LEMMA) collaboration has explored the muon pair production close to its kinematic threshold by annihilating 45 GeV positrons with electrons in a low Z material target. In this configuration, muons are emerging from the target with a naturally low-emittance. In this paper we describe the performance of a system, to study this production mechanism, that consists in several segmented absorbers with alternating active layers composed of fast Cherenkov detectors together with a muon identification technique based on this detector. Passive layers were made of tungsten. We collected data corresponding to muon and electron beams produced at the H2 line in the North Area of the European Organization for Nuclear Research (CERN) in September 2018.

physics.ins-det↗

arXiv2020

Study of muon pair production from positron annihilation at threshold energy

The muon collider represents one of the most promising solutions for a future machine exploring the high energy frontier, but several challenges due to the 2.2 $μ$sec muon lifetime at rest have to be carefully considered. The LEMMA project is investigating the possibility of producing low emittance muon/antimuon pairs from the e$^+$e$^-$ annihilation process at threshold energy, resulting in small transverse emittance beams without any additional beam cooling. However most of the measurements available are performed at higher $\sqrt{s}$ values. It is therefore necessary to measure muons production in positron annihilation at threshold energy and compare the experimental results with the predictions in this specific energy regime. Apart from being a topic of physical interest by itself, these near to threshold measurements can have a sizeable impact on the estimation of the ultimate luminosity achievable in a muon collider with the LEMMA injection scheme.

hep-ex↗

arXiv2011

Demonstration and Comparison of Operation of Photomultiplier Tubes at Liquid Argon Temperature

Liquified noble gases are widely used as a target in direct Dark Matter searches. Signals from scintillation in the liquid, following energy deposition from the recoil nuclei scattered by Dark Matter particles (e.g. WIMPs), should be recorded down to very low energies by photosensors suitably designed to operate at cryogenic temperatures. Liquid Argon based detectors for Dark Matter searches currently implement photo multiplier tubes for signal read-out. In the last few years PMTs with photocathodes operating down to liquid Argon temperatures (87 K) have been specially developed with increasing Quantum Efficiency characteristics. The most recent of these, Hamamatsu Photonics Mod. R11065 with peak QE up to about 35%, has been extensively tested within the R&D program of the WArP Collaboration. During these testes the Hamamatsu PMTs showed superb performance and allowed obtaining a light yield around 7 phel/keVee in a Liquid Argon detector with a photocathodic coverage in the 12% range, sufficient for detection of events down to few keVee of energy deposition. This shows that this new type of PMT is suited for experimental applications, in particular for new direct Dark Matter searches with LAr-based experiments.

physics.ins-det↗