Search Results (47)

A conceptual design study is presented for a hemispherical, two-chamber water Cherenkov detector instrumented with bladder-embedded light traps. The detector consists of a rigid aluminium vessel enclosing a water volume that is divided into an outer, optically black chamber and a inner, reflective chamber lined by a flexible bladder. Arrays of light-trap modules, based on plastic scintillators with wavelength-shifting elements and thin silicon photomultipliers, are integrated into the bladder and selected inner surfaces. This geometry is intended to enhance muon tagging, increase acceptance for inclined air showers, and enable improved discrimination between electromagnetic and hadronic components. The study describes the mechanical and optical layout of the detector, the baseline aluminium housing, and the use of 3D-printed hexagonal prototypes to validate integration of the bladder and readout electronics. A first-order structural assessment based on thin-shell and plate theory is presented, indicating large safety margins for the hemispherical shells and identifying the flat base as the mechanically most loaded component. While GEANT4 simulations for detector response to extensive air showers in the atmosphere and performance measurements are left to future work, the present study establishes a mechanically validated, costed baseline design and outlines the steps needed to assess its impact in air-shower arrays. Full article

The Lorentz invariance violation (LIV) predicted by some quantum gravity theories would manifest as an energy-dependent speed of light, which may potentially distort the observed temporal profile of photons from astrophysical sources at cosmological distances. The dispersion cancellation (DisCan) algorithm offers a powerful methodology for investigating such effects by employing quantities such as Shannon entropy, which reflects the initial temporal characteristics. In this study, we apply the DisCan algorithm to search for LIV effects in the LHAASO observations of GRB 221009A, combining data from both the Water Cherenkov Detector Array (WCDA) and Kilometer Squared Array (KM2A) detectors that collectively span an energy range of ∼0.2–13 TeV. Our analysis accounts for the uncertainties from both energy resolution and temporal binning. We derive $95\%$ confidence level lower limits on the LIV energy scale of $E_{\mathrm{QG},1}/{10}^{19}\mathrm{GeV}>14.6$ (11.2) for the first-order subluminal (superluminal) scenario, and $E_{\mathrm{QG},2}/{10}^{11}\mathrm{GeV}>13.7$ (12.5) for the second-order subluminal (superluminal) scenario. Full article

Future space detectors for Ultra High Energy neutrinos and cosmic rays will utilize Cherenkov telescopes to detect forward-beamed Cherenkov light produced by charged particles in Extensive Air Showers (EASs). A Cherenkov detector can be equipped with an array of Silicon Photo-Multiplier (SiPM) pixels, which offer several advantages over traditional Photo-Multiplier Tubes (PMTs). SiPMs are compact and lightweight and operate at lower voltages, making them well-suited for space-based experiments. The SiSMUV (SiPM-based Space Monitor for UV-light) is developing a SiPM-based Cherenkov camera for PBR (POEMMA Baloon with Radio) at INFN Napoli. To understand the response of such an instrument, a comprehensive simulation of the response of individual SiPM pixels to incident light is needed. For the accurate simulation of a threshold trigger, this simulation must reproduce the current produced by a SiPM pixel as a function of time. Since a SiPM pixel is made of many individual Avalanche Photo-Diodes (APDs), saturation and pileup in APDs must also be simulated. A Gaussian mixture fit to ADC count spectrum of a SiPM pixel exposed to low levels of laser light at INFN Napoli shows a significant amount of samples between the expected PE (Photo Electron) peaks. Thus, noise sources such as dark counts and afterpulses, which result in partially integrated APD pulses, must be accounted for. With static, reasonable values for noise rates, the simulation chain presented in this work uses the characteristics of individual APDs to produce the aggregate current produced by a SiPM pixel. When many such pulses are simulated and integrated, the ADC spectra generated by low levels of laser light at the INFN Napoli SiSMUV test setup can be accurately reproduced. Full article

In this work, we present a novel compact particle identification (PID) detector concept based on Silicon Photomultipliers (SiPMs) optimized to perform combined Ring-Imaging Cherenkov (RICH) and Time-of-Flight (TOF) measurements using a common photodetector layer. The system consists of a Cherenkov radiator layer separated from a photosensitive surface equipped with SiPMs by an expansion gap. A thin glass slab, acting as a second Cherenkov radiator, is coupled to the SiPMs to perform Cherenkov-based charged particle timing measurements. We assembled a small-scale prototype instrumented with various Hamamatsu SiPM array sensors with pixel pitches ranging from 2 to 3 mm and coupled with 1 mm thick fused silica window. The RICH radiator consisted of a 2 cm thick aerogel tile with a refractive index of 1.03 at 400 nm. The prototype was successfully tested in beam test campaigns at the CERN PS T10 beam line with pions and protons. We measured a single-hit angular resolution of about 4 mrad at the Cherenkov angle saturation value and a time resolution better than 50 ps RMS for charged particles with Z = 1. The present technology makes the proposed SiPM-based PID system particularly attractive for space applications due to the limited detector volumes available. In this work, we present beam test results obtained with the detector prototype and we discuss possible configurations optimized for the identification of ions in space applications. Full article

The study of Ultra-High-Energy Cosmic Rays is made possible by space telescopes that allow for the recording of signals generated by Extensive Air Showers (EAS) on the night side of the Earth’s atmosphere. One of the requirements for these telescopes is the detection of very low photon fluxes, achievable using the latest generation SiPMs characterized by high intrinsic gains, low power consumption, low weight, and robustness against accidental exposure to light. Despite these advantages, some technological issues still need to be addressed, such as the radiation hardness for operation in space. Therefore, the design of a SiPM-based focal surface for UHECR detection must consider the space qualification of SiPM arrays, with the development of compact arrays optimized for low dead-area focal surfaces. SiSMUV (SiPM-based Space Monitor for UV light) is a project dedicated to developing a compact and modular UV detector for use in space telescopes designed to study the fluorescence and Cherenkov signals produced by Ultra-High-Energy Cosmic Rays (UHECRs). Each SiSMUV module incorporates a matrix of SiPMs, a readout ASIC (Radioroc by Weeroc), and an FPGA into a monolithic block. This design enables the acquisition and processing of signals from the sensors. The system can connect to a PC for standalone operation or with back-end electronics for integration into more complex systems. In this paper, we will describe the prototype electronics, the experimental setup and the measurements performed to obtain parameters such as the gain of the SiPMs, and their photon detection efficiency (PDE). We will also present the firmware developed to interface with the readout ASIC and to transmit data to other peripherals. Full article

Cherenkov radiation is a widely used detection mechanism in high-energy and astroparticle physics experiments, particularly in water-based detectors operated by leading cosmic-ray observatories. Its popularity stems from its robustness, cost-effectiveness, and high detection efficiency across a broad range of environmental conditions. In this study, we present a detailed Monte Carlo characterization of a Water Cherenkov Detector (WCD) using the Geant4 simulation toolkit as a general, experiment-independent reference for understanding detector responses to secondary cosmic-ray particles. The detector is modeled to register secondary particles produced by the interaction of high-energy cosmic-ray primaries with the Earth’s atmosphere, which give rise to extensive air showers composed of hadronic, electromagnetic, and muonic components capable of reaching ground level. By simulating the differential energy spectra and angular distributions of these particles at the surface, we evaluate the WCD response in terms of energy deposition, Cherenkov photon production, photoelectron generation at the photomultiplier tube, and the resulting charge spectra. The results establish a systematic and transferable baseline for detector performance characterization and particle identification, providing a physically grounded reference that can support calibration, trigger optimization, and analysis efforts across different WCD-based experiments. Full article

POEMMA-Balloon with Radio (PBR) is designed as a payload for a NASA suborbital Super Pressure Balloon that will circle over the Southern Ocean and a mission duration as long as 50 days. The PBR instrument consists of a 1.1 m aperture Schmidt telescope similar to the POEMMA design with two cameras in its focal surface: a Fluorescence Camera (FC) and a Cherenkov Camera (CC). The CC camera is mainly devoted to the observation of cosmic-ray-induced high-altitude horizontal air showers (HAHAs) and search for neutrino-induced upward-going EAS. It will be made of 2048 SiPMs with a surface of 3 × 3 mm² and a FoV of 12° by 6°, covering a spectral range of 320–900 nm. The CC camera is an innovative detector currently under construction. In this paper, information about its current status will be given. Full article

The Cherenkov effect, whereby a charged particle emits light when traveling faster than the phase velocity of light in a dielectric medium, is widely employed in particle identification techniques. However, Cherenkov light yield is relatively low, typically amounting to only 100–200 visible photons per centimeter of path length in materials like water, plastic, or glass. In this study, we investigate the optical response of FB118, a wavelength-shifting (WLS) plastic developed by Glass to Power, under exposure to ionizing particles. Our measurements confirm the absence of residual scintillation in FB118, allowing for a clean separation of Cherenkov signals. Moreover, the intrinsic WLS properties of the material enable a significant enhancement of light detection in the visible range. These features make FB118 a promising candidate for use in compact Cherenkov detectors, particularly in astroparticle physics experiments where space and power constraints demand efficient, compact solutions. Full article

Monte Carlo simulations of induced extensive air showers (EASs) by ultra-high-energy cosmic rays are widely used in comparison with measured events at experiments to estimate the main cosmic ray characteristics, such as mass, energy, and arrival direction. However, these simulations are computationally expensive, with running time scaling proportionally with the number of radio antennas included. The AugerPrime upgrade of the Pierre Auger Observatory will feature an array of 1660 radio antennas. As a result, simulating a single EAS using the full detector array will take weeks on a single CPU thread. To reduce the simulation time, detectors are commonly pre-selected based on their proximity to the shower core, using a selection ellipse based on the Cherenkov radiation footprint scaled by a fixed constant factor. While effective, this approach often includes many noisy antennas at high zenith angles, reducing computational efficiency. In this paper, we introduce an optimal method for selecting candidate detectors with high predicted signal-to-noise ratio for proton and iron primary cosmic rays, replacing the constant scaling factor with a function of the zenith angle. This approach significantly reduces simulation time—by more than 50% per CPU thread for the heaviest, most inclined showers—without compromising signal quality. Full article

FPGA-RICH is an FPGA-based online partial particle identification system for the NA62 experiment employing AI techniques. Integrated between the readout of the Ring Imaging Cherenkov detector (RICH) and the low-level trigger processor (L0TP+), FPGA-RICH implements a fast pipeline to process in real-time the RICH raw hit data stream, producing trigger primitives containing elaborate physics information—e.g., the number of charged particles in a physics event—that L0TP+ can use to improve trigger decision efficiency. Deployed on a single FPGA, the system combines classical online processing with a compact Neural Network algorithm to achieve efficient event classification while managing the challenging ∼10 MHz throughput requirement of NA62. The streaming pipeline ensures ∼1 $\mathsf{\mu }$s latency, comparable to that of the NA62 detectors, allowing its seamless integration in the existing TDAQ setup as an additional detector. Development leverages High-Level Synthesis (HLS) and the open-source hls4ml package software–hardware codesign workflow, enabling fast and flexible reprogramming, debugging, and performance optimization. We describe the implementation of the full processing pipeline, the Neural Network classifier, their functional validation, performance metrics and the system’s current status and outlook. Full article

Ground-based observations of Very High Energy (VHE) gamma rays from extreme astrophysical sources are significantly influenced by atmospheric conditions. This is due to the atmosphere being an integral part of the detector when utilizing Imaging Atmospheric Cherenkov Telescopes (IACTs). Clouds and dust particles diminish atmospheric transmission of Cherenkov light, thereby impacting the reconstruction of the air showers and consequently the reconstructed gamma-ray spectra. Precise measurements of atmospheric transmission above Cherenkov observatories play a pivotal role in the accuracy of the analysed data, among which the corrections of the reconstructed energies and fluxes of incoming gamma rays, and in establishing observation strategies for different types of gamma-ray emitting sources. The Major Atmospheric Gamma Imaging Cherenkov (MAGIC) telescopes and the Cherenkov Telescope Array Observatory (CTAO), both located on the Observatorio del Roque de los Muchachos (ORM), La Palma, Canary Islands, use different sets of auxiliary instruments for real-time characterisation of the atmosphere. In this paper, historical data taken by MAGIC LIDAR (LIght Detection And Ranging) and CTAO FRAM (F/Photometric Robotic Telescope) are presented. From the atmospheric aerosol transmission profiles measured by the MAGIC LIDAR and CTAO FRAM aerosol optical depth maps, we obtain the characterisation of the clouds above the ORM at La Palma needed for data correction and optimal observation scheduling. Full article

The Latin American Giant Observatory (LAGO) is a ground-based extended cosmic rays observatory designed to study transient astrophysical events, the role of the atmosphere on the formation of secondary particles, and space-weather-related phenomena. With the use of a network of Water Cherenkov Detectors (WCDs), LAGO measures the secondary particle flux, a consequence of the interaction of astroparticles impinging on the atmosphere of Earth. This flux can be grouped into three distinct basic constituents: electromagnetic, muonic, and hadronic components. When a particle enters a WCD, it generates a measurable signal characterized by unique features correlating to the particle’s type and the detector’s specific response. The resulting charge histograms from these signals provide valuable insights into the flux of primary astroparticles and their key characteristics. However, these data are insufficient to effectively distinguish between the contributions of different secondary particles. In this work, we extend our previous research by using detailed simulations of the expected atmospheric response to the primary flux and the corresponding response of our WCDs to atmospheric radiation. This dataset, which was created through the combination of the outputs of the ARTI and Meiga simulation frameworks, simulated the expected WCD signals produced by the flux of secondary particles during one day at the LAGO site in Bariloche, Argentina, situated at 865 m above sea level. This was achieved by analyzing the real-time magnetospheric and local atmospheric conditions for February and March of 2012, where the resultant atmospheric secondary-particle flux was integrated into a specific Meiga application featuring a comprehensive Geant4 model of the WCD at this LAGO location. The final output was modified for effective integration into our machine-learning pipeline. With an implementation of Ordering Points to Identify the Clustering Structure (OPTICS), a density-based clustering algorithm used to identify patterns in data collected by a single WCD, we have further refined our approach to implement a method that categorizes particle groups using advanced unsupervised machine learning techniques. This allowed for the differentiation among particle types and utilized the detector’s nuanced response to each, thus pinpointing the principal contributors within each group. Our analysis has demonstrated that applying our enhanced methodology can accurately identify the originating particles with a high degree of confidence on a single-pulse basis, highlighting its precision and reliability. These promising results suggest the feasibility of future implementations of machine-leaning-based models throughout LAGO’s distributed detection network and other astroparticle observatories for semi-automated, onboard and real-time data analysis. Full article

Ultra-high-energy cosmic rays (UHECRs) are extremely rare energetic particles of ordinary matter in the Universe, traveling astronomical distances before reaching the Earth’s atmosphere. When primary cosmic rays interact with atmospheric nuclei, cascading extensive air showers (EASs) of secondary elementary particles are developed. Radio detectors have proven to be a reliable method for reconstructing the properties of EASs, such as the shower’s axis, its energy, and its maximum (${\mathrm{X}}_{\max }$). This aids in understanding fundamental astrophysical phenomena, like active galactic nuclei and gamma-ray bursts. Concurrently, data science has become indispensable in UHECR research. By applying statistical, computational, and deep learning methods to both real-world and simulated radio data, researchers can extract insights and make predictions. We introduce a convolutional neural network (CNN) architecture designed to classify simulated air shower events as either being generated by protons or by iron nuclei. The classification achieved a stable test error of 10%, with Accuracy and ${\mathrm{F}}_1$ scores of 0.9 and an MCC of 0.8. These metrics indicate strong prediction capability for UHECR’s nuclear composition, based on data that can be gathered by detectors at the world’s largest cosmic rays experiment on Earth, the Pierre Auger Observatory, which includes radio antennas, water Cherenkov detectors, and fluorescence telescopes. Full article

Isotopic composition measurements of singly charged cosmic rays (CR) provide essential insights into CR transport in the Galaxy. The Alpha Magnetic Spectrometer (AMS-02) can identify singly charged isotopes up to about 10 GeV/n. However, their identification presents challenges due to the small abundance of CR deuterons compared to the proton background. In particular, a high accuracy for the velocity measured by a ring-imaging Cherenkov detector (RICH) is needed to achieve a good isotopic mass separation over a wide range of energies. The velocity measurement with the RICH is particularly challenging for $Z=1$ isotopes due to the low number of photons produced in the Cherenkov rings. This faint signal is easily disrupted by noisy hits leading to a misreconstruction of the particles’ ring. Hence, an efficient background reduction process is needed to ensure the quality of the reconstructed Cherenkov rings and provide a correct measurement of the particles’ velocity. Machine learning methods, particularly boosted decision trees, are well suited for this task, but their performance relies on the choice of the features needed for their training phase. While physics-driven feature selection methods based on the knowledge of the detector are often used, machine learning algorithms for automated feature selection can provide a helpful alternative that optimises the classification method’s performance. We compare five algorithms for selecting the feature samples for RICH background reduction, achieving the best results with the Random Forest method. We also test its performance against the physics-driven selection method, obtaining better results. Full article

NUSES is a pathfinder satellite project hosting two detectors: Ziré and Terzina. Ziré focuses on the study of protons and electrons below 250 MeV and MeV gamma rays. Terzina is dedicated to the detection of Cherenkov light produced by ultra-high-energy cosmic rays above 100 PeV and ultra-high-energy Earth-skimming neutrinos in the atmosphere, ensuring a large exposure. This work mainly concerns the description of the Cherenkov camera, composed of SiPMs, for the Terzina telescope. To increase the data-taking period, the NUSES orbit will be Sun-synchronous (with a height of about 550 km), thus allowing Terzina to always point toward the dark side of the Earth’s limb. The Sun-synchronous orbit requires small distances to the poles, and as a consequence, we expect an elevated dose to be received by the SiPMs. Background rates due to the dose accumulated by the SiPM would become a dominant contribution during the last two years of the NUSES mission. In this paper, we illustrate the measured effect of irradiance on SiPM photosensors with a variable-intensity beam of 50 MeV protons up to a 30 Gy total integrated dose. We also show the results of an initial study conducted without considering the contribution of solar wind protons and with an initial geometry with Geant4. The considered geometry included an entrance lens as one of the options in the initial design of the telescope. We characterize the SiPM output signal shape with different μ-cell sizes. We describe the developed parametric SiPM simulation, which is a part of the full Terzina simulation chain. Full article