Atmospheric Cherenkov Telescopes Research Articles

An Angular Diameter Measurement of β UMa via Stellar Intensity Interferometry with the VERITAS Observatory

We use the Very Energetic Radiation Imaging telescope Array System (VERITAS) imaging air Cherenkov telescope array to obtain the first measured angular diameter of β UMa at visual wavelengths using stellar intensity interferometry (SII) and independently constrain the limb-darkened angular diameter. The age of the Ursa Major moving group has been assessed from the ages of its members, including nuclear member Merak (β UMa), an A1-type subgiant, by comparing effective temperature and luminosity constraints to model stellar evolution tracks. Previous interferometric limb-darkened angular-diameter measurements of β UMa in the near-infrared (Center for High Angular Resolution Astronomy (CHARA) Array, 1.149 ± 0.014 mas) and mid-infrared (Keck Nuller, 1.08 ± 0.07 mas), together with the measured parallax and bolometric flux, have constrained the effective temperature. This paper presents current VERITAS-SII observation and analysis procedures to derive squared visibilities from correlation functions. We fit the resulting squared visibilities to find a limb-darkened angular diameter of 1.07 ± 0.04 (stat) ± 0.05 (sys) mas, using synthetic visibilities from a stellar atmosphere model that provides a good match to the spectrum of β UMa in the optical wave band. The VERITAS-SII limb-darkened angular diameter yields an effective temperature of 9700 ± 200 ± 200 K, consistent with ultraviolet spectrophotometry, and an age of 390 ± 29 ± 32 Myr, using MESA Isochrones and Stellar Tracks. This age is consistent with 408 ± 6 Myr from the CHARA Array angular diameter.

Direct comparison of SiPM and PMT sensor performances in a large-size imaging air Cherenkov telescope

The peak photon detection efficiency (PDE) of silicon photomultipliers (SiPMs) can be as good or better than the PDE of photomultiplier tubes (PMTs). There are experiments where the signal is measured in the presence of a strong, steady background light emission. In these, one needs to accurately evaluate the signal-to-noise ratio. Imaging Atmospheric Cherenkov Telescopes (IACT) observe in the presence of strong noise induced by the light of the night sky. It is certainly interesting to investigate the SiPM performance under operational conditions of IACTs and to compare it with that of the PMTs.For that purpose, we built a SiPM-based detector module, which was installed in one of the imaging cameras of the two Major Atmospheric Gamma-ray Imaging Cherenkov (MAGIC) telescopes in 2015. The experience gained from that module was used to design the second generation of modules of improved performance. Two such modules were installed in 2017.MAGIC is a system of two IACTs located on the Canary Island of La Palma. The mechanical structure of the MAGIC imaging cameras offers the possibility to install up to 6 additional detector modules of 7 pixels each into the open vertices of the hexagonal-shaped camera. This allows us to directly, without making any assumption, compare the performance of the PMT-based modules with that of the SiPM-based prototype modules, where SiPMs from three different manufacturers are used.

Ultra-fast generation of air shower images for Imaging Air Cherenkov Telescopes using Generative Adversarial Networks

For the analysis of data taken by Imaging Air Cherenkov Telescopes (IACTs), a large number of air shower simulations are needed to derive the instrument response. The simulations are very complex, involving computational and memory-intensive calculations, and are usually performed repeatedly for different observation intervals to take into account the varying optical sensitivity of the instrument. The use of generative models based on deep neural networks offers the prospect for memory-efficient storing of huge simulation libraries and cost-effective generation of a large number of simulations in an extremely short time. In this work, we use Wasserstein Generative Adversarial Networks to generate photon showers for an IACT equipped with the FlashCam design, which has more than 1,500 pixels. Using simulations of the H.E.S.S. experiment, we demonstrate the successful generation of high-quality IACT images. The analysis includes a comprehensive study of the generated image quality based on low-level observables and the well-known Hillas parameters that describe the shower shape. We demonstrate for the first time that the generated images have high fidelity with respect to low-level observables, the Hillas parameters, their physical properties, as well as their correlations. The found increase in generation speed in the order of 105 yields promising prospects for fast and memory-efficient simulations of air showers for IACTs.

Application of deep learning methods combined with physical background in wide field of view imaging atmospheric Cherenkov telescopes

Application of deep learning methods combined with physical background in wide field of view imaging atmospheric Cherenkov telescopes

A Very-High-Energy Gamma-Ray View of the Transient Sky

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.

Multi-view Deep Learning for Imaging Atmospheric Cherenkov Telescopes

This research note concerns the application of deep-learning-based multi-view-imaging techniques to data from the High Energy Stereoscopic System Imaging Atmospheric Cherenkov Telescope array. We find that the earlier the fusion of layer information from different views takes place in the neural network, the better our model performs with this data. Our analysis shows that the point in the network where the information from the different views is combined is far more important for the model performance than the method used to combine the information.

The ASTRI Mini-Array: A New Pathfinder for Imaging Cherenkov Telescope Arrays

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.

Observations of the Crab Nebula with MACE (Major Atmospheric Cherenkov Experiment)

The Major Atmospheric Cherenkov Experiment (MACE) is a large size (21 m) Imaging Atmospheric Cherenkov Telescope (IACT) installed at an altitude of 4270 m above sea level at Hanle, Ladakh in northern India. Here we report the detection of Very High Energy (VHE) γ-ray emission from Crab Nebula above 80 GeV. We analyzed ∼ 15 h of data collected at low zenith angle between November 2022 and February 2023. The energy spectrum is well described by a log-parabola function with a flux of ∼(3.46±0.26stat)×10−10TeV−1cm−2s−1, at 400 GeV with spectral index of 2.09±0.06stat and a curvature parameter of 0.08±0.07stat. The γ-rays are detected in an energy range spanning from 80GeV to ∼5TeV. The energy resolution improves from ∼ 34% at an analysis energy threshold of 80GeV to ∼ 21% above 1TeV. The daily light curve and the spectral energy distribution obtained for the Crab Nebula is in agreement with previous measurements, considering statistical and systematic uncertainties.

Performance and first measurements of the MAGIC stellar intensity interferometer

ABSTRACT In recent years, a new generation of optical intensity interferometers has emerged, leveraging the existing infrastructure of Imaging Atmospheric Cherenkov Telescopes (IACTs). The MAGIC telescopes host the MAGIC-SII system (Stellar Intensity Interferometer), implemented to investigate the feasibility and potential of this technique on IACTs. After the first successful measurements in 2019, the system was upgraded and now features a real-time, dead-time-free, 4-channel, GPU-based correlator. These hardware modifications allow seamless transitions between MAGIC’s standard very-high-energy gamma-ray observations and optical interferometry measurements within seconds. We establish the feasibility and potential of employing IACTs as competitive optical Intensity Interferometers with minimal hardware adjustments. The measurement of a total of 22 stellar diameters are reported, 9 corresponding to reference stars with previous comparable measurements, and 13 with no prior measurements. A prospective implementation involving telescopes from the forthcoming Cherenkov Telescope Array Observatory’s Northern hemisphere array, such as the first prototype of its Large-Sized Telescopes, LST-1, is technically viable. This integration would significantly enhance the sensitivity of the current system and broaden the UV-plane coverage. This advancement would enable the system to achieve competitive sensitivity with the current generation of long-baseline optical interferometers over blue wavelengths.

A novel image-correction method for cloud-affected observations with Imaging Atmospheric Cherenkov Telescopes

The presence of clouds during observations with Imaging Atmospheric Cherenkov Telescopes can strongly affect the performance of the instrument due to additional absorption of light and scattering of light beyond the field of view of the instrument. If not corrected for, the presence of clouds leads to increased systematic errors in the results. One approach to correct for the effects of clouds is to include clouds in Monte Carlo simulations to produce models for primary particle classification, and energy and direction estimation. However, this method is challenging due to the dynamic nature of cloudy conditions and requires extensive computational resources. The second approach focuses on correcting the data themselves for cloud effects, which allows the use of standard simulations. However, existing corrections often prioritise the limitation of systematic errors without optimising overall performance. By correcting the data already at the image level, it is possible to improve event reconstruction without the need for specialised simulations. We introduce a novel analysis method based on a geometrical model that can correct the data already at the image level given a vertical transmission profile of a cloud. Using Monte Carlo simulations of an array of four of the Large-Sized Telescopes of the Cherenkov Telescope Array, we investigated the effect of the correction on the image parameters and the performance of the system. We compared the data correction at the camera level with the use of dedicated simulations for clouds with different transmissions and heights. The proposed method efficiently corrects the extinction of light in clouds, eliminating the need for dedicated simulations. Evaluation using Monte Carlo simulations demonstrates improved gamma-ray event reconstruction and overall system performance. Currently used analysis methods for cloud-affected data focus on the correction of the reconstructed energy, however, do not counteract the worsening of the performance parameters. We introduce a novel analysis method, based on a geometrical model that can correct the data already at the image level given a vertical transmission profile of a cloud. Using Monte Carlo simulations of an array of four Large-Sized Telescopes, we investigate the effect of the correction on the image parameters and the performance of the system. The proposed method can efficiently correct the effect of light extinction in the cloud without the need to generate dedicated simulations.

Simultaneously unveiling the EBL and intrinsic spectral parameters of gamma-ray sources with Hamiltonian Monte Carlo

The Extragalactic Background Light (EBL) is the main radiation field responsible for attenuating extragalactic gamma-ray emission at very high energies, but its precise spectral intensity is not fully determined. Therefore, disentangling propagation effects from the intrinsic spectral properties of gamma-ray sources (such as active galactic nuclei, AGN) is the primary challenge to interpret observations of these objects. We present a Bayesian and Markov Chain Monte Carlo approach to simultaneously infer parameters characterizing the EBL and the intrinsic spectra in a combined fit of a set of sources, which has the advantage of easily incorporating the uncertainties of both sets of parameters into one another through marginalization of the posterior distribution. Taking a sample of synthetic blazars observed by the ideal CTA configuration, we study the effects on the EBL constraints of combining multiple observations and varying their exposure. We also apply the methodology to a set of 65 gamma-ray spectra of 36 different AGNs measured by current Imaging Atmospheric Cherenkov Telescopes, using Hamiltonian Monte Carlo as a solution to the difficult task of sampling in spaces with a high number of parameters. We find robust constraints in the mid-IR region while simultaneously obtaining intrinsic spectral parameters for all of these objects. In particular, we identify Markarian 501 (Mkn 501) flare data (HEGRA/1997) as essential for constraining the EBL above 30 μm.

The Case of the Missing Very High-energy Gamma-Ray Bursts: A Retrospective Study of Swift Gamma-Ray Bursts with Imaging Atmospheric Cherenkov Telescopes

Gamma-ray bursts (GRBs) are particle acceleration sites that can emit photons in the very high-energy (VHE) domain through nonthermal processes. From 2004 until 2018, the current generation of Imaging Atmospheric Cherenkov Telescopes (IACTs) did not detect any GRB in the VHE domain. However, from 2018 to 2020, five detections were reported. In this work, we try to solve the case of the missing VHE GBRs prior to 2018. We aim to identify GRBs that might have eluded VHE detection in past years by the H.E.S.S., MAGIC, and VERITAS IACTs. To do so, we study GRBs with known redshift detected by Swift from 2004 until June 2022. We first identify all GRBs that could have been observed by these IACTs since 2004, considering observation conditions and visibility constraints. We assume a relation between the X-rays and the VHE gamma rays based on the VHE GRBs detected to date and combine this with the redshift measurements, instrument response information, and observation conditions to predict the observed VHE gamma-ray flux from the Swift X-Ray Telescope measurements. We report findings on 12 bright low-redshift GRBs that we identify as most likely to have been detected in the VHE domain by current IACTs. The rate of IACT-detectable GRBs with ideal observation conditions is <1 VHE GRB per year with the current configuration. With its lower energy threshold and higher sensitivity, this rate increases to ∼4 VHE GRBs per year with the Cherenkov Telescope Array.

Gamma/Hadron Separation Method for the HADAR Experiment

Ground-based arrays of imaging atmospheric Cherenkov telescopes (IACTs) are the most sensitive γ-ray detectors for energies of approximately 100 GeV and above. One such IACT is the High Altitude Detection of Astronomical Radiation (HADAR) experiment, which uses a large aperture refractive water lens system to capture atmospheric Cherenkov photons (i.e., the imaging atmospheric Cherenkov technique). The telescope array has a low threshold energy and large field of view, and can continuously scan the area of the sky being observed, which is conducive to monitoring and promptly responding to transient phenomena. The process of γ-hadron separation is essential in very-high-energy (>30 GeV) γ-ray astronomy and is a key factor for the successful utilization of IACTs. In this study, Monte Carlo simulations were carried out to model the response of cosmic rays within the HADAR detectors. By analyzing the Hillas parameters and the distance between the event core and the telescope, the distinction between air showers initiated by γ-rays and those initiated by cosmic rays was determined. Additionally, a Quality Factor was introduced to assess the telescope’s ability to suppress the background and to provide a more effective characterization of its performance.

Study of Angular Resolution Using Imaging Atmospheric Cherenkov Technique

Angular resolution is crucial for the detailed study of gamma-ray sources and current Cherenkov telescopes (e.g., HESS, MAGIC, and VERITAS) that operate below tens of TeV. Several gamma-ray sources with a photon energy larger than 100 TeV have been revealed by the LHAASO in recent years; the angular resolution of the LHAASO is around 0.3∘. A gamma-ray detector with an angular resolution of less than 0.1∘ operating beyond 100 TeV is needed to study the detailed morphology of ultra-high-energy gamma-ray sources further. The cost-effectiveness is crucial for such large-area detectors. In this paper, the impact of telescope aperture, field of view, pixel size, optical point spread function, and signal integration time window on angular resolution is studied. These results can provide essential elements for the design of telescope arrays.

A novel energy reconstruction method for the MAGIC stereoscopic observation

We report the successful development of a novel methodology of energy reconstruction for very high energy gamma rays detected with Imaging Atmospheric Cherenkov Telescopes (IACTs). This methodology, based on the machine learning algorithm Random Forest, and named RF-Erec, has been adjusted for being used with data from the Major Atmospheric Gamma-ray Imaging Cherenkov (MAGIC) stereo telescope system, which is a worldwide leading instrument for gamma-ray astronomy in the energy range from about 20GeV to beyond 100TeV.The RF-Erec has been evaluated using different realistic scenarios with Monte Carlo simulated data and real observations from the Crab Nebula (the standard candle for the VHE gamma-ray community). This new methodology has been validated by the MAGIC software board, and it is implemented and ready-to-use in the MAGIC Analysis and Reconstruction Software (MARS). This new methodology, validated by the MAGIC software board, has been implemented and is ready for use in the MAGIC Analysis and Reconstruction Software (MARS). We demonstrate that, in comparison to the previous energy reconstruction methodology for MAGIC data, which relied on Look-Up-Tables (LUTs- Erec) and has been utilized in over 100 scientific publications over the last decade, RF-Erec significantly enhances the energy reconstruction of gamma rays. This improvement extends the capabilities of the MAGIC telescopes.Specifically, when quantifying the energy resolution with the width of a Gaussian fitted to the error distribution (resolution-σ), the RF-Erec energy resolution-σ is 20% at 100 GeV and 11% above 1 TeV for Zenith distances (Zd) below 35 degrees, while it is 20% at 1TeV and 13% above 10TeV for Zd above 55 degrees. For a wide range of the observable energies, the improvement of energy resolution-σ, compared to LUTs-Erec, reaches roughly a factor of two, and the improvement is even larger for high Zd observations. Differently to many other works in the literature, our evaluation also considers the energy dispersion and the actual energy migration of events, where RF-Erec improves the performance of LUTs-Erec by factors of a few. The manuscript also demonstrates the importance of energy reconstruction methods with a small energy migration in order to prevent the appearance of artificial spectral features. These artifacts are particularly important at the high end of the gamma-ray spectra, where a few extra high-energy photons could have dramatic consequences for studies related to the EBL attenuation, Lorentz invariance violation, or searches for Axion-like-particles.

Highlights of the Magic Florian Goebel Telescopes in the Study of Active Galactic Nuclei

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 &gt; 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.

Silicon Photomultiplier selection for Large Array of Imaging Atmospheric Cherenkov Telescopes

A Large Array of imaging atmospheric Cherenkov Telescopes (LACT) will be constructed at the Large High Altitude Air Shower Observatory site to explore the nature of PeV gamma-ray sources. The cameras of LACT will use Silicon Photomultipliers (SiPMs) as the photodetector. A dedicated test system was built to select SiPMs for LACT. The characteristics of six SiPM models from three manufacturers (Hamamatsu, Joinbon, and ON Semiconductor) were evaluated. Based on the characteristics of the candidate SiPMs and their preamplifiers, a Wiener-deconvolution algorithm is implemented to correct the pileup of the SiPM output pulses. The measurement methods and results for breakdown voltage, gain, dark count rate, optical crosstalk, and afterpulsing of the candidate SiPMs are reported in this article.

First intensity interferometry measurements with the H.E.S.S. telescopes

ABSTRACT Intensity interferometry for astrophysical observations has gained increasing interest in the last decade. The method of correlating photon fluxes at different telescopes for high resolution astronomy without access to the phase of the incoming light is insensitive to atmospheric turbulence and does not require high-precision optical path control. The necessary large collection areas can be provided by Imaging Atmospheric Cherenkov Telescopes. Implementation of intensity interferometers to existing telescope systems such as VERITAS and MAGIC has proven to be successful for high-resolution imaging of stars. In 2022 April we equipped two telescopes of the H.E.S.S. array in Namibia with an intensity interferometry setup to measure southern sky stars and star systems during the bright moon period. We mounted an external optical system to the lid of the telescope cameras, which splits the incoming light and feeds it into two photomultipliers in order to measure the zero-baseline correlation within one telescope in addition to the cross-correlation between the telescopes. The optical elements are motorized, which enables live correction of tracking inaccuracies of the telescopes. During the campaign we measured the spatial correlation curves and thereby the angular diameters of λ Sco (Shaula) and σ Sgr (Nunki), while we also performed systematic studies of our interferometer using the multiple star system of α Cru (Acrux).

Generating Synthetic Images of Gamma-Ray Events for Imaging Atmospheric Cherenkov Telescopes Using Conditional Generative Adversarial Networks

Generating Synthetic Images of Gamma-Ray Events for Imaging Atmospheric Cherenkov Telescopes Using Conditional Generative Adversarial Networks

Signal-background separation and energy reconstruction of gamma rays using pattern spectra and convolutional neural networks for the Small-Sized Telescopes of the Cherenkov Telescope Array

Imaging Atmospheric Cherenkov Telescopes (IACTs) detect very-high-energy gamma rays from ground level by capturing the Cherenkov light of the induced particle showers. Convolutional neural networks (CNNs) can be trained on IACT camera images of such events to differentiate the signal from the background and to reconstruct the energy of the initial gamma ray. Pattern spectra provide a 2-dimensional histogram of the sizes and shapes of features comprising an image and they can be used as an input for a CNN to significantly reduce the computational power required to train it. In this work, we generate pattern spectra from simulated gamma-ray and proton images to train a CNN for signal-background separation and energy reconstruction for the Small-Sized Telescopes (SSTs) of the Cherenkov Telescope Array (CTA). A comparison of our results with a CNN directly trained on CTA images shows that the pattern spectra-based analysis is about a factor of three less computationally expensive but not able to compete with the performance of an CTA image-based analysis. Thus, we conclude that the CTA images must be comprised of additional information not represented by the pattern spectra.