Search Results (27)

Clouds are essential for regulating the hydrological cycle and Earth’s radiation budget, and their fluctuations over the Tibetan Plateau (TP) have a significant effect on both regional climate dynamics and global atmospheric circulation. Using ground-based Vaisala CL51 ceilometer data and Fengyun-4A (FY-4A) satellite observations from October 2020 to June 2022, this study examines cloud occurrence frequency (COF), cloud vertical structure (including cloud base height (CBH), cloud top height (CTH), and cloud layer stratification), and related macroscopic properties over the Large High Altitude Air Shower Observatory (LHAASO). CL51 and FY-4A had cloud occurrence rates of 43.7% and 37.7%, respectively, over the observation period, with a strong correlation coefficient of 0.82. Given the impact of clouds on Cherenkov light observations by the LHAASO Wide Field of view Cherenkov Telescope Array (WFCTA), we specifically evaluated the cloud occurrence during the operational periods of the LHAASO-WFCTA, finding rates of 34.2% (CL51) and 28.0% (FY-4A), with the lowest rates occurring in the early morning. Due to monsoonal moisture inflow and dry northeasterly winds, seasonal COF changes showed clear peaks in summer (78.8%) and minima in winter (24.8%). Seasonal differences existed in the diurnal COF patterns, with nocturnal prominence in summer/autumn and daytime dominance in spring/winter. The CBH showed daily oscillations, peaking at 18:00 (local solar time) and troughing at 08:00 (local solar time), with seasonal CBH minima in summer/autumn and maxima in spring/winter. Low- and mid-level clouds predominated, with clear diurnal cycles: low- and mid-level clouds rose from morning until midday, while high-level clouds appeared after dusk. Vertical cloud structures were predominantly single-layered (81%), with multi-layered complexity peaking in the summer due to convective activity. The CTH distributions showed unimodal patterns in the fall and winter (1.5–3 km), while in the summer, they showed multimodal extents (up to 12 km). These results improve LHAASO-WFCTA observational scheduling, enhance climate model parameterizations, and deepen our understanding of the dynamics of the TP cloud. 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

Searching for very-high-energy photons arising from dark matter interactions in selected astrophysical environments is a promising strategy to probe the existence and particle nature of dark matter. Among the many particle candidates, motivated by the extensions of the Standard Model, Weakly Interacting Massive Particles (WIMPs) are considered the most compelling candidate for the elusive dark matter in the universe. In this contribution, we report an overview of the important developments in the field of indirect searching for dark matter through cosmic gamma-ray observations. We mainly focus on the role of atmospheric Cherenkov telescopes in probing the dark matter. Finally, we emphasize the opportunities for the Major Atmospheric Cherenkov Experiment (MACE) situated in Hanle, India, to explore WIMPs in the mass range of 200 GeV to 10 TeV for Segue1 and Draco dwarf–spheroidal galaxies. Full article

Imaging Atmospheric Cherenkov Telescopes (IACTs) have revolutionized our understanding of the universe at very high energies (VHEs), enabling groundbreaking discoveries of extreme astrophysical phenomena. These instruments capture the brief flashes of Cherenkov light produced when VHE particles interact with Earth’s atmosphere, providing unique insights into cosmic accelerators and high-energy radiation sources. A fundamental challenge in IACT observations lies in distinguishing the rare gamma-ray signals from an overwhelming background of cosmic-ray events. For every gamma-ray photon detected from even the brightest sources, thousands of cosmic-ray-induced atmospheric showers trigger the telescopes. This profound signal-to-background imbalance necessitates sophisticated discrimination techniques that can effectively isolate genuine gamma-ray events while maintaining high rejection efficiency for cosmic-ray backgrounds. The most common method involves the parametrization of the morphological feature of the shower images. However, we know that gamma-ray and hadron showers also differ in their time evolution. Here, we describe how the pixel time tags (i.e., the record of when each camera pixel is lit up by the incoming shower) can help in the discrimination between photonic and hadronic showers, with a focus on the ASTRI Mini-Array Cherenkov Event Reconstruction. Our methodology employs a Random Forest classifier with optimized hyperparameters, trained on a balanced dataset of gamma and hadron events. The model incorporates feature importance analysis to select the most discriminating temporal parameters from a comprehensive set of time-based features. This machine learning approach enables effective integration of both morphological and temporal information, resulting in improved classification performance, especially at lower energies. Full article

This paper presents the technical design of the pathfinder Barcelona Raman LIDAR (pBRL) for the northern site of the Cherenkov Telescope Array Observatory (CTAO-N) located at the Roque de los Muchachos Observatory (ORM). The pBRL is developed for continuous atmospheric characterization, essential for correcting high-energy gamma-ray observations captured by Imaging Atmospheric Cherenkov Telescopes (IACTs). The LIDAR consists of a steerable telescope with a 1.8 m parabolic mirror and a pulsed Nd:YAG laser with frequency doubling and tripling. It emits at wavelengths of 355 nm and 532 nm to measure aerosol scattering and extinction through two elastic and Raman channels. Built upon a former Cherenkov Light Ultraviolet Experiment (CLUE) telescope, the pBRL’s design includes a Newtonian mirror configuration, a coaxial laser beam, a near-range system, a liquid light guide and a custom-made polychromator. During a one-year test at the ORM, the stability of the LIDAR and semi-remote-controlled operations were tested. This pathfinder leads the way to designing a final version of a CTAO Raman LIDAR which will provide real-time atmospheric monitoring and, as such, ensure the necessary accuracy of scientific data collected by the CTAO-N telescope array. Full article

Observations of Very High Energy (VHE) gamma ray sources using the ground-based Imaging Atmospheric Cherenkov Telescopes (IACTs) play a pivotal role in understanding the non-thermal energetic phenomena and acceleration processes under extreme astrophysical conditions. However, detection of the VHE gamma ray signal from the astrophysical sources is very challenging, as these telescopes detect the photons indirectly by measuring the flash of Cherenkov light from the Extensive Air Showers (EAS) initiated by the cosmic gamma rays in the Earth’s atmosphere. This requires fast detection systems, along with advanced data acquisition and analysis techniques to measure the development of extensive air showers and the subsequent segregation of gamma ray events from the huge cosmic ray background, followed by the physics analysis of the signal. Here, we report the development of a python-based package for analyzing the data from the Major Atmospheric Cherenkov Experiment (MACE), which is operational at Hanle in India. The Python-based MACE data Analysis Package (PyMAP) analyzes data by using advanced methods and machine learning algorithms. Data recorded by the MACE telescope are passed through different utilities developed in the PyMAP to extract the gamma ray signal from a given source direction. We also propose a new image cleaning method called DIOS (Denoising Image of Shower) and compare its performance with the standard image cleaning method. The working performance of DIOS indicates an advantage over the standard method with an improvement of ≈$25\%$ in the sensitivity of MACE. 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

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

The accuracy of cosmic ray observations by the Large High Altitude Air Shower Observatory Wide Field-of-View Cherenkov/Fluorescence Telescope Array (LHAASO-WFCTA) is influenced by variations in aerosols in the atmosphere. The solar photometer (CE318-T) is extensively utilized within the Aerosol Robotic Network as a highly precise and reliable instrument for aerosol measurements. With this CE318-T 23, 254 sets of valid data samples over 394 days from October 2020 to October 2022 at the LHAASO site were obtained. Data analysis revealed that the baseline Aerosol Optical Depth (AOD) and Ångström Exponent (AE) at 440–870 nm (AE_440–870nm) of the aerosols were calculated to be 0.03 and 1.07, respectively, suggesting that the LHAASO site is among the most pristine regions on Earth. The seasonality of the mean AOD is in the order of spring > summer > autumn = winter. The monthly average maximum of AOD_440nm occurred in April (0.11 ± 0.05) and the minimum was in December (0.03 ± 0.01). The monthly average of AE_440–870nm exhibited slight variations. The seasonal characterization of aerosol types indicated that background aerosol predominated in autumn and winter, which is the optimal period for the absolute calibration of the WFCTA. Additionally, the diurnal daytime variations of AOD and AE across the four seasons are presented. Our analysis also indicates that the potential origins of aerosol over the LHAASO in four seasons were different and the atmospheric aerosols with higher AOD probably originate mainly from Northern Myanmar and Northeast India regions. These results are presented for the first time, providing a detailed analysis of aerosol seasonality and origins, which have not been thoroughly documented before in this region, also enriching the valuable materials on aerosol observation in the Hengduan Mountains and Tibetan Plateau. Full article

The development of the latest generation of Imaging Atmospheric Cherenkov Telescopes (IACTs) over recent decades has led to the discovery of new extreme astrophysical phenomena in the very-high-energy (VHE, E > 100 GeV) gamma-ray regime. Time-domain and multi-messenger astronomy are inevitably connected to the physics of transient VHE emitters, which show unexpected (and mostly unpredictable) flaring or exploding episodes at different timescales. These transients often share the physical processes responsible for the production of the gamma-ray emission, through cosmic-ray acceleration, magnetic reconnection, jet production and/or outflows, and shocks interactions. In this review, we present an up-to-date overview of the VHE transients field, spanning from novae to supernovae, neutrino counterparts or fast radio bursts, among others, and we outline the expectations for future facilities. Full article

The ASTRI Mini-Array is an Istituto Nazionale di Astrofisica (INAF) project to build and operate an array of nine Imaging Atmospheric Cherenkov Telescopes (IACTs) at the Teide Astronomical Observatory of the Instituto de Astrofisica de Canarias in Tenerife (Spain) based on a host agreement with INAF and, as such, it will be the largest IACT array until the Cherenkov Telescope Array Observatory starts operations. Implementing the ASTRI Mini-Array poses several challenges from technical, logistic, and management points of view. Starting from the description of the innovative technologies adopted to build the telescopes, we will discuss the solutions adopted to overcome these challenges, making the ASTRI Mini-Array a great instrument to perform deep observations of the galactic and extra-galactic sky at very high energies. 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

The MAGIC (Major Atmospheric Gamma-ray Imaging Cherenkov) Florian Goebel telescopes are a system of two Cherenkov telescopes located on the Canary island of La Palma (Spain), at the Roque de Los Muchachos Observatory, which have been operating in stereo mode since 2009. Their low energy threshold (down to 15 GeV) allows the investigation of Active Galactic Nuclei (AGNs) in the very-high-energy (VHE, E > 100 GeV) gamma-ray range with a sensitivity up to the redshift limit of the existing IACT (Imaging Atmospheric Cherenkov Telescopes) systems. The MAGIC telescopes discovered 36 extragalactic objects emitting VHE gamma-rays and performed comprehensive studies of galaxies and their AGNs, also in a multi-wavelength (MWL) and multi-messenger (MM) context, expanding the knowledge of our Universe. Here, we report on the highlights achieved by the MAGIC collaboration since the beginning of their operations. Full article

The Imaging Atmospheric Cherenkov technique has opened up previously unexplored windows for the study of astrophysical radiation sources in the very high-energy (VHE) regime and is playing an important role in the discovery and characterization of VHE gamma-ray emitters. However, even for the most powerful sources, the data collected by Imaging Atmospheric Cherenkov Telescopes (IACTs) are heavily dominated by the overwhelming background due to cosmic-ray nuclei and cosmic-ray electrons. As a result, the analysis of IACT data necessitates the use of a highly efficient background rejection technique capable of distinguishing a gamma-ray induced signal through identification of shape features in its image. We present a detailed case study of gamma/hadron separation and energy reconstruction. Using a set of simulated data based on the ASTRI Mini-Array Cherenkov telescopes, we have assessed and compared a number of supervised Machine Learning methods, including the Random Forest method, Extra Trees method, and Extreme Gradient Boosting (XGB). To determine the optimal weighting for each method in the ensemble, we conducted extensive experiments involving multiple trials and cross-validation tests. As a result of this thorough investigation, we found that the most sensitive Machine Learning technique applied to our data sample for gamma/hadron segregation is a Stacking Ensemble Method composed of 42% Extra Trees, 28% Random Forest, and 30% XGB. In addition, the best-performing technique for energy estimation is a different Stacking Ensemble Method composed of 45% XGB, 27.5% Extra Trees, and 27.5% Random Forest. These optimal weightings were derived from extensive testing and fine-tuning, ensuring maximum performance for both gamma/hadron separation and energy estimation. Full article

High-energetic gamma rays from astrophysical targets constitute a unique probe for annihilation or decay of heavy particle dark matter (DM). After several decades, diverse null detections have resulted in strong constraints for DM particle masses up to the TeV scale. While the gamma-ray signature is expected to be universal from various targets, uncertainties of astrophysical origin strongly affect and weaken the limits. At the same time, spurious signals may originate from non-DM related processes. The many gamma-ray targets in the extragalactic sky being searched for DM play a crucial role to keep these uncertainties under control and to ultimately achieve an unambiguous DM detection. Lately, a large progress has been made in combined analyses of TeV DM candidates towards different targets by using data from various instruments and over a wide range of gamma-ray energies. These approaches not only resulted in an optimal exploitation of existing data and an improved sensitivity, but also helped to level out target- and instrument-related uncertainties. This review gathers all searches in the extragalactic sky performed so far with the space-borne Fermi-Large Area Telescope, the ground-based imaging atmospheric Cherenkov telescopes, and the High-Altitude Water Cherenkov Gamma-Ray Observatory (HAWC). We discuss the different target classes and provide a complete list of all analyses so far. Full article