LS I +61°303 is one of around ten gamma-ray binaries detected so far which has a spectral energy distribution dominated by MeV-GeV photons. It is located at a distance of 2 kpc and consists of a compact object (black hole or neutron star) in an eccentric orbit around a 10-15Be star, with an orbital period of 26.496 days. The binary orbit modulates the emission ranging from radio to TeV energies. A second, longer, modulation period of 1667 days (the super-orbital period) has also been detected from radio to TeV observations. The VERITAS imaging atmospheric Cherenkov telescope array has been observing LS I +61°303 since 2006, and has accumulated a dataset that fully covers the entire orbit. Increased coverage of the source in the very-high-energy band is currently underway to provide more results on the modulation pattern, super-orbital period, and orbit-to-orbit variability at the highest energies. The spectral measurements at the highest energies will reveal more information about gamma-ray production/absorption mechanisms, the nature of the compact object, and the particle acceleration mechanism. Using >150 hrs of VERITAS data, we present a detailed study of the spectral energy distribution and periodic behavior of this rare gamma-ray source type at very-high energy.
The observation of the transient sky through a multitude of astrophysical messengers has led to several scientific breakthroughs these last two decades thanks to the fast evolution of the observational techniques and strategies employed by the astronomers. Now, it requires to be able to coordinate multi-wavelength and multi-messenger follow-up campaigns with instruments both in space and on ground jointly capable of scanning a large fraction of the sky with a high imaging cadency and duty cycle. In the optical domain, the key challenge of the wide field of view telescopes covering tens to hundreds of square degrees is to deal with the detection, the identification and the classification of hundreds to thousands of optical transient (OT) candidates every night in a reasonable amount of time. In the last decade, new automated tools based on machine learning approaches have been developed to perform those tasks with a low computing time and a high classification efficiency. In this paper, we present an efficient classification method using Convolutional Neural Networks (CNN) to discard many common types of bogus falsely detected in astrophysical images in the optical domain. We designed this tool to improve the performances of the OT detection pipeline of the Ground Wide field Angle Cameras (GWAC) telescopes, a network of robotic telescopes aiming at monitoring the optical transient sky down to R=16 with a 15 seconds imaging cadency. We applied our trained CNN classifier on a sample of 1472 GWAC OT candidates detected by the real-time detection pipeline.
We report the detection and follow-up of a superstellar flare GWAC 181229A with an amplitude of ΔR ∼ 9.5 mag on an M9-type star by SVOM/GWAC and the dedicated follow-up telescopes. The estimated bolometric energy E bol is (5.56–9.25) × 1034 erg, which makes the event one of the most powerful flares seen on ultracool stars. The magnetic strength is inferred to be 3.6–4.7 kG. Thanks to sampling with a cadence of 15 s, a new component near the peak time with a very steep decay is detected in the R-band light curve, followed by the two-component flare template given by Davenport et al. An effective temperature of 5340 ± 40 K is measured by fitting a blackbody shape to the spectrum in the shallower phase during the flare. The filling factors of the flare are estimated to be ∼30% and 19% at the peak time and at 54 minutes after the first detection. The detection of this particular event with large amplitude, huge emitted energy, and a new component demonstrates that high-cadence sky monitoring cooperation with fast follow-up observations is very important for understanding the violent magnetic activity.
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