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Register a new userComposite mirror facets for ground based gamma ray astronomy
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Composite mirrors for gamma-ray astronomy have been developed to fulfill the specifications required for the next generation of Cherenkov telescopes represented by CTA (Cherenkov Telescope Array). In addition to the basic requirements on focus and reflection efficiency, the mirrors have to be stiff, lightweight, durable and cost efficient. In this paper, the technology developed to produce such mirrors is described, as well as some tests that have been performed to validate them. It is shown that these mirrors comply with the needs of CTA, making them good candidates for use on a significant part of the array.
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During the last two decades Gamma-Ray Astronomy has emerged as a powerful tool to study cosmic ray physics. In fact, photons are not deviated by galactic or extragalactic magnetic fields so their directions bring the information of the production sites and are easier to detect than neutrinos. Thus the search for $gamma$ primarily address in the framework of the search of cosmic ray sources and to the investigation of the phenomena in the acceleration sites. This note is not a place for a review of ground-based gamma-ray astronomy. We will introduce the experimental techniques used to detect photons from ground in the overwhelming background of CRs and briefly describe the experiments currently in data taking or under installation.
Schwarzschild-type aplanatic telescopes with two aspheric mirrors, configured to correct spherical and coma aberrations, are considered for application in gamma-ray astronomy utilizing the ground-based atmospheric Cherenkov technique. We use analytical descriptions for the figures of primary and secondary mirrors and, by means of numerical ray-tracing, we find telescope configurations which minimize astigmatism and maximize effective light collecting area. It is shown that unlike the traditional prime-focus Davies-Cotton design, such telescopes provide a solution for wide field of view gamma-ray observations. The designs are isochronous, can be optimized to have no vignetting across the field, and allow for significant reduction of the plate scale, making them compatible with finely-pixilated cameras, which can be constructed from modern, cost-effective image sensors such as multi-anode PMTs, SiPMs, or image intensifiers.
Following the discovery of the cosmic rays by Victor Hess in 1912, more than 70 years and numerous technological developments were needed before an unambiguous detection of the first very-high-energy gamma-ray source in 1989 was made. Since this discovery the field on very-high-energy gamma-ray astronomy experienced a true revolution: A second, then a third generation of instruments were built, observing the atmospheric cascades from the ground, either through the atmospheric Cherenkov light they comprise, or via the direct detection of the charged particles they carry. Present arrays, 100 times more sensitive than the pioneering experiments, have detected a large number of astrophysical sources of various types, thus opening a new window on the non-thermal Universe. New, even more sensitive instruments are currently being built; these will allow us to explore further this fascinating domain. In this article we describe the detection techniques, the history of the field and the prospects for the future of ground-based very-high-energy gamma-ray astronomy.
This article is the write-up of a rapporteur talk given at the 34th ICRC in The Hague, Netherlands. It attempts to review the results and developments presented at the conference and associated to the vibrant field of ground-based gamma-ray astronomy. In total, it aims to give an overview of the 19 gamma-ray sessions, 84 talks and 176 posters presented at the 34th ICRC on this topic. New technical advances and projects will be described with an emphasis given on the cosmic-ray related studies of the Universe.
Modern detectors of cosmic gamma-rays are a special type of imaging telescopes (air Cherenkov telescopes) supplied with cameras with a relatively large number of photomultiplier-based pixels. For example, the camera of the TAIGA-IACT telescope has 560 pixels of hexagonal structure. Images in such cameras can be analysed by deep learning techniques to extract numerous physical and geometrical parameters and/or for incoming particle identification. The most powerful deep learning technique for image analysis, the so-called convolutional neural network (CNN), was implemented in this study. Two open source libraries for machine learning, PyTorch and TensorFlow, were tested as possible software platforms for particle identification in imaging air Cherenkov telescopes. Monte Carlo simulation was performed to analyse images of gamma-rays and background particles (protons) as well as estimate identification accuracy. Further steps of implementation and improvement of this technique are discussed.
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