We compared convolutional neural networks to the classical boosted decision trees for the separation of atmospheric particle showers generated by gamma rays from the particle-induced background. We conduct the comparison of the two techniques applied to simulated observation data from the Cherenkov Telescope Array. We then looked at the Receiver Operating Characteristics (ROC) curves produced by the two approaches and discuss the similarities and differences between both. We found that neural networks overperformed classical techniques under specific conditions.
A detailed case study of $γ$-hadron segregation for a ground based atmospheric Cherenkov telescope is presented. We have evaluated and compared various supervised machine learning methods such as the Random Forest method, Artificial Neural Network, Linear Discriminant method, Naive Bayes Classifiers,Support Vector Machines as well as the conventional dynamic supercut method by simulating triggering events with the Monte Carlo method and applied the results to a Cherenkov telescope. It is demonstrated that the Random Forest method is the most sensitive machine learning method for $γ$-hadron seg…
In this work we compare two open source machine learning libraries, PyTorch and TensorFlow, as software platforms for rejecting hadron background events detected by imaging air Cherenkov telescopes (IACTs). Monte Carlo simulation for the TAIGA-IACT telescope is used to estimate background rejection quality. A wide variety of neural network algorithms provided by both libraries can easily be tested on various types of data, which is useful for various imaging air Cherenkov experiments. The work is a component of the Astroparticle.online project, which collaborates with the TAIGA and KASCADE exp…
A dramatic progress in the field of computer vision has been made in recent years by applying deep learning techniques. State-of-the-art performance in image recognition is thereby reached with Convolutional Neural Networks (CNNs). CNNs are a powerful class of artificial neural networks, characterized by requiring fewer connections and free parameters than traditional neural networks and exploiting spatial symmetries in the input data. Moreover, CNNs have the ability to automatically extract general characteristic features from data sets and create abstract data representations which can perfo…
In this paper we have introduced a novel method for gamma hadron separation in Imaging Atmospheric Cherenkov Telescopes (IACT) using Quantum Machine Learning. IACTs captures images of Extensive Air Showers (EAS) produced from very high energy gamma rays. We have used the QML Algorithms, Quantum Support Vector Classifier (QSVC) and Variational Quantum Classifier (VQC) for binary classification of the events into signals (Gamma) and background(hadron) using the image parameters. MAGIC Gamma Telescope dataset is used for this study which was generated from Monte Carlo Software Coriska. These quan…
An Approach to Gamma-Hadron Separation via Measurements of the Middle-UV Fraction of EAS emission by an Imaging Atmospheric Cherenkov Telescope with UV-Sensitive SiPM detectors
The upcoming Cherenkov Telescope Array (CTA) project is expected to provide unprecedented sensitivity in the low-energy (<~100 GeV) range for Cherenkov telescopes. Most of the remaining background in this energy range results from misidentified hadron showers. In order to fully exploit the potential of the telescope systems it is worthwhile to look for ways to further improve the available analysis methods for γ/hadron separation. We study the composition of the background for the planned CTA-North array by identifying events composed mostly of a single electromagnetic subcascade or double sub…
Imaging Atmospheric Cherenkov Telescopes (IACTs) are ground-based indirect detectors for cosmic gamma rays with energies above tens of GeV. The major backgrounds for gamma-ray observations in IACTs are cosmic-ray charged particles. The capability to reject these backgrounds is the most important factor determining the gamma-ray sensitivity of IACT systems. Monte Carlo simulations are used to estimate the residual background rates and sensitivity of the systems during the design and construction phase. Uncertainties in the modeling of high-energy hadronic interactions of cosmic rays with nuclei…
The HAWC observatory reconstructs atmospheric showers induced by very high-energy primary cosmic- or gamma-rays. Cosmic-rays with hadronic nature are several orders of magnitude more frequent than primary gammas and therefore it is necessary to perform the best gamma-hadron discrimination for each event to be able to survey the gamma-ray sky. Single vertical muons cause very characteristic signals in the 300 HAWC detectors. Particularly, those events that produce signals in the four PMTs of a tank corresponding to muons traversing the tank in the central region. In such cases exist the correla…
The upcoming Cherenkov Telescope Array (CTA) project is expected to provide unprecedented sensitivity in the low-energy ( <~100 GeV) range for Cherenkov telescopes. In order to exploit fully the potential of the telescopes the standard analysis methods for gamma/hadron separation might need to be revised. We study the composition of the background by identifying events composed mostly of a single electromagnetic subcascade or double subcascade from a π0 (or another neutral meson) decay. We apply the standard simulation and analysis chain of CTA to evaluate the potential of the standard analysi…
Event reconstruction techniques for the wide-angle air Cherenkov detector HiSCORE
广角，非成像空气切伦科夫探测器提供了一种观察宇宙伽马射线的方法，这是对切伦科夫望远镜成像观测的补充。它们的特殊优势在于多TeV到超高能量范围（E > 30 TeV），其中需要大的有效面积，但每个探测器站的光敏面积很小。为了充分利用这一潜力，需要大的站间距，以合理的努力实现大的有效面积。在这样的探测器中，每个事件的信号数量少，成像信息的缺乏，以及切伦科夫光与夜空亮度的信噪比差，对事件重建，特别是伽马强子分离提出了相当大的挑战。本文中提出的事件重建已被开发用于广角探测器HiSCORE，但概念可以更一般地应用。它是在10 TeV至5 PeV的能量范围内的模拟数据进行测试。在测试中，假设一个由22 x 22个探测站组成的规则网格，间距为150 m，覆盖面积为10 km^2。发现单个事件的角分辨率在能量阈值附近为约0.3度，在较高能量下提高到低于0.1度。相对能量分辨率在阈值处为20%，在较高能量处提高到10%。描述了γ强子分离的几个参数。通过这些参数的组合，可以抑制80%至90%的强子背景，而保留约60%的伽马射线事件。在保守的假设下，对于10 km^2的阵列，在100 TeV的伽马射线下，点源对伽马射线源的灵敏度估计约为8 x 10^（-13）erg / s / cm^2。在更乐观的假设下，如果使用100 km^2的阵列，则可以实现约1 x 10^（-13）erg / s / cm^2的…
Very high energy gamma rays entering the atmosphere initiate Extensive Air Showers (EAS). The Cherenkov light induced by an EAS can be observed by ground-based telescopes to study the primary gamma rays. An important parameter of an EAS, determining its evolution, is the height of the first interaction of the primary particle. However, this variable cannot be directly measured by Cherenkov telescopes. We study two simple, independent methods for the estimation of the first interaction height. We test the methods using the Monte Carlo simulations for the 4 Large Size Telescopes (LST) that are p…
This paper investigates the potential to detect tau neutrinos in the energy range of 1-1000 PeV searching for very inclined showers with imaging Cherenkov telescopes. A neutrino induced tau lepton escaping from the Earth may decay and initiate an air shower which can be detected by a fluorescence or Cherenkov telescope. We present here a study of the detection potential of Earth-skimming neutrinos taking into account neutrino interactions in the Earth crust, local matter distributions at various detector sites, the development of tau-induced showers in air and the detection of Cherenkov photon…
This paper investigates the potential to detect tau neutrinos in the energy range of 1-1000 PeV searching for very inclined showers with imaging Cherenkov telescopes. A neutrino induced tau lepton escaping from the Earth may decay and initiate an air shower which can be detected by a fluorescence or Cherenkov telescope. We present here a study of the detection potential of Earth-skimming neutrinos taking into account neutrino interactions in the Earth crust, local matter distributions at various detector sites, the development of tau-induced showers in air and the detection of Cherenkov photon…
Ground-level particle detection is now a well-established approach to TeV gamma-ray astronomy. Detection of Cherenkov light produced in water-filled detection units is a proven and cost-effective method. Here we discuss the optimization of the units towards the future Southern Wide-field Gamma-ray Observatory (SWGO). In this context, we investigate a new type of configuration in which each water Cherenkov detector (WCD) unit in the array comprises two chambers with black or reflective walls and a single photomultiplier tube (PMT) in each chamber. We find that this is a cost-effective approach …
The physics of the non-thermal Universe provides information on the acceleration mechanisms in extreme environments, such as black holes and relativistic jets, neutron stars, supernovae or clusters of galaxies. In the presence of magnetic fields, particles can be accelerated towards relativistic energies. As a consequence, radiation along the entire electromagnetic spectrum can be observed, and extreme environments are also the most likely sources of multi-messenger emission. The most energetic part of the electromagnetic spectrum corresponds to the very-high-energy (VHE, E>100 GeV) gamma-ray …
This Letter of Intent (LoI) describes the outline and plan for the Neutrino Telescope Array (NTA) project. High-energy neutrinos provide unique and indisputable evidence for hadronic acceleration. Recently, IceCube has reported astronomical neutrino candidates in excess of expectation from atmospheric secondaries, but is limited by the water Cherenkov detection method. A next generation high-energy neutrino telescope should be capable of establishing indisputable evidence for cosmic high-energy neutrinos. It should not only have orders-of-magnitude larger sensitivity, but also enough pointing …
