The CLUE UV Čerenkov telescope array has started to take data with 8 telescopes in January 1998. The UV Cerenkov images obtained by the CLUE experiment are very different with respect to the visible ...case, and a new method for reconstructing the shower direction has been worked out. The shower reconstruction is shown and an application to recent data is given.
We aim to characterize the broadband emission from 2FGL J2001.1+4352, which has been associated with the unknown-redshift blazar MG4 J200112+4352. Based on its gamma-ray spectral properties, it was ...identified as a potential very high energy (VHE; E > 100 GeV) gamma-ray emitter. The source was observed with MAGIC first in 2009 and later in 2010 within a multi-instrument observation campaign. The MAGIC observations yielded 14.8 hours of good quality stereoscopic data. The object was monitored at radio, optical and gamma-ray energies during the years 2010 and 2011. The source, named MAGIC J2001+439, is detected for the first time at VHE with MAGIC at a statistical significance of 6.3 {\sigma} (E > 70 GeV) during a 1.3-hour long observation on 2010 July 16. The multi-instrument observations show variability in all energy bands with the highest amplitude of variability in the X-ray and VHE bands. We also organized deep imaging optical observations with the Nordic Optical Telescope in 2013 to determine the source redshift. We determine for the first time the redshift of this BL Lac object through the measurement of its host galaxy during low blazar activity. Using the observational evidence that the luminosities of BL Lac host galaxies are confined to a relatively narrow range, we obtain z = 0.18 +/- 0.04. Additionally, we use the Fermi-LAT and MAGIC gamma-ray spectra to provide an independent redshift estimation, z = 0.17 +/- 0.10. Using the former (more accurate) redshift value, we adequately describe the broadband emission with a one-zone SSC model for different activity states and interpret the few-day timescale variability as produced by changes in the high-energy component of the electron energy distribution.
We study the multifrequency emission and spectral properties of the quasar 3C 279. We observed 3C 279 in very high energy (VHE, E>100GeV) gamma rays, with the MAGIC telescopes during 2011, for the ...first time in stereoscopic mode. We combine these measurements with observations at other energy bands: in high energy (HE, E>100MeV) gamma rays from Fermi-LAT, in X-rays from RXTE, in the optical from the KVA telescope and in the radio at 43GHz, 37GHz and 15GHz from the VLBA, Mets\"ahovi and OVRO radio telescopes and optical polarisation measurements from the KVA and Liverpool telescopes. During the MAGIC observations (February to April 2011) 3C 279 was in a low state in optical, X-ray and gamma rays. The MAGIC observations did not yield a significant detection. These upper limits are in agreement with the extrapolation of the HE gamma-ray spectrum, corrected for extragalactic background light absorption, from Fermi-LAT. The second part of the MAGIC observations in 2011 was triggered by a high activity state in the optical and gamma-ray bands. During the optical outburst the optical electric vector position angle rotatated of about 180 degrees. There was no simultaneous rotation of the 43GHz radio polarisation angle. No VHE gamma rays were detected by MAGIC, and the derived upper limits suggest the presence of a spectral break or curvature between the Fermi-LAT and MAGIC bands. The combined upper limits are the strongest derived to date for the source at VHE and below the level of the previously detected flux by a factor 2. Radiation models that include synchrotron and inverse Compton emissions match the optical to gamma-ray data, assuming an emission component inside the broad line region (BLR) responsible for the high-energy emission and one outside the BLR and the infrared torus causing optical and low-energy emission. We interpreted the optical polarisation with a bent trajectory model.
Neural networks have proved to be versatile and robust for particle
separation in many experiments related to particle astrophysics. We apply these
techniques to separate gamma rays from hadrons for ...the MAGIC Cerenkov
Telescope. Two types of neural network architectures have been used for the
classi cation task: one is the MultiLayer Perceptron (MLP) based on supervised
learning, and the other is the Self-Organising Tree Algorithm (SOTA), which is
based on unsupervised learning. We propose a new architecture by combining
these two neural networks types to yield better and faster classi cation
results for our classi cation problem.
Context. We present the discovery of very high energy (VHE, E > 100GeV) gamma-ray emission from the BL Lac object 1ES 1215+303 by the MAGIC telescopes and simultaneous multi-wavelength data in a ...broad energy range from radio to gamma-rays. Aims. We study the VHE gamma-ray emission from 1ES 1215+303 and its relation to the emissions in other wavelengths. Methods. Triggered by an optical outburst, MAGIC observed the source in January-February 2011 for 20.3 hrs. The target was monitored in the optical R-band by the KVA telescope that also performed optical polarization measurements. We triggered target of opportunity observations with the Swift satellite and obtained simultaneous and quasi-simultaneous data from the Fermi Large Area Telescope and from the Mets\"ahovi radio telescope. We also present the analysis of older MAGIC data taken in 2010. Results. The MAGIC observations of 1ES 1215+303 carried out in January-February 2011 resulted in the first detection of the source at VHE with a statistical significance of 9.4 sigma. Simultaneously, the source was observed in a high optical and X-ray state. In 2010 the source was observed in a lower state in optical, X-ray, and VHE, while the GeV gamma-ray flux and the radio flux were comparable in 2010 and 2011. The spectral energy distribution obtained with the 2011 data can be modeled with a simple one zone SSC model, but it requires extreme values for the Doppler factor or the electron energy distribution.
Gamma ray astronomy is now at the leading edge for studies related both to fundamental physics and astrophysics. The sensitivity of gamma detectors is limited by the huge amount of background, ...constituted by hadronic cosmic rays (typically two to three orders of magnitude more than the signal) and by the accidental background in the detectors. By using the information on the temporal evolution of the Cherenkov light, the background can be reduced. We will present here the results obtained within the MAGIC experiment using a new technique for the reduction of the background. Particle showers produced by gamma rays show a different temporal distribution with respect to showers produced by hadrons; the background due to accidental counts shows no dependence on time. Such novel strategy can increase the sensitivity of present instruments.
The MAGIC Collaboration is building a second telescope, MAGIC II, improving the design of the current MAGIC Telescope. MAGIC II is being built at 85 m of distance from MAGIC I, and will also feature ...a huge reflecting surface of ~240 m\(^2\) of area. One of the improvement is the design for the mirror of MAGIC II, that are lighter and larger, being square of 1 m of side and weighting around 15 kg. For the development and production of the new mirrors, two different techniques, both reliable and affordable in price, were selected: the diamond milling of aluminium surfaces and the cold slumping of thin glass panes. As tests for the second one are still ongoing, we present a description of the diamond milling technique, and its application and performance to the produced mirrors.
Neural networks have proved to be versatile and robust for particle separation in many experiments related to particle astrophysics. We apply these techniques to separate gamma rays from hadrons for ...the MAGIC Cerenkov Telescope. Two types of neural network architectures have been used for the classi cation task: one is the MultiLayer Perceptron (MLP) based on supervised learning, and the other is the Self-Organising Tree Algorithm (SOTA), which is based on unsupervised learning. We propose a new architecture by combining these two neural networks types to yield better and faster classi cation results for our classi cation problem.
Astropart.Phys. 23 (2005) 572-576 In this article we discuss the possibility of using the observations by GLAST
of standard gamma sources, as the Crab Nebula, to calibrate Imaging Air
Cherenkov ...detectors, MAGIC in particular, and optimise their energy resolution.
We show that at around 100 GeV the absolute energy calibration uncertainty of
Cherenkov telescopes can be reduced to <10% by means of such cross-calibration
procedure.
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