Monitoring of the radio galaxy M87 during a low emission state from 2012 to 2015 with MAGIC

M87 is one of the closest (z=0.00436) extragalactic sources emitting at very-high-energies (VHE, E > 100 GeV). The aim of this work is to locate the region of the VHE gamma-ray emission and to describe the observed broadband spectral energy distribution (SED) during the low VHE gamma-ray state. The data from M87 collected between 2012 and 2015 as part of a MAGIC monitoring programme are analysed and combined with multi-wavelength data from Fermi-LAT, Chandra, HST, EVN, VLBA and the Liverpool Telescope. The averaged VHE gamma-ray spectrum can be fitted from 100GeV to 10TeV with a simple power law with a photon index of (-2.41 $\pm$ 0.07), while the integral flux above 300GeV is $(1.44 \pm 0.13) \times 10^{-12} cm^{-2} s^{-1}$. During the campaign between 2012 and 2015, M87 is generally found in a low emission state at all observed wavelengths. The VHE gamma-ray flux from the present 2012-2015 M87 campaign is consistent with a constant flux with some hint of variability ($\sim3\sigma$) on a daily timescale in 2013. The low-state gamma-ray emission likely originates from the same region as the flare-state emission. Given the broadband SED, both a leptonic synchrotron self Compton and a hybrid photo-hadronic model reproduce the available data well, even if the latter is preferred. We note, however, that the energy stored in the magnetic field in the leptonic scenario is very low suggesting a matter dominated emission region

Binaries with the eyes of CTA

The binary systems that have been detected in gamma rays have proven very useful to study high-energy processes, in particular particle acceleration, emission and radiation reprocessing, and the dynamics of the underlying magnetized flows. Binary systems, either detected or potential gamma-ray emitters, can be grouped in different subclasses depending on the nature of the binary components or the origin of the particle acceleration: the interaction of the winds of either a pulsar and a massive star or two massive stars; accretion onto a compact object and jet formation; and interaction of a relativistic outflow with the external medium. We evaluate the potentialities of an instrument like the Cherenkov telescope array (CTA) to study the non-thermal physics of gamma-ray binaries, which requires the observation of high-energy phenomena at different time and spatial scales. We analyze the capability of CTA, under different configurations, to probe the spectral, temporal and spatial behavior of gamma-ray binaries in the context of the known or expected physics of these sources. CTA will be able to probe with high spectral, temporal and spatial resolution the physical processes behind the gamma-ray emission in binaries, significantly increasing as well the number of known sources. This will allow the derivation of information on the particle acceleration and emission sites qualitatively better than what is currently available.Comment: 23 pages, 13 figures, accepted for publication in Astroparticle Physics, special issue on Physics with the Cherenkov Telescope Arra

Pulsar Prospects for the Cherenkov Telescope Array

In the last few years, the Fermi-LAT telescope has discovered over a 100 pulsars at energies above 100 MeV, increasing the number of known gamma-ray pulsars by an order of magnitude. In parallel, imaging Cherenkov telescopes, such as MAGIC and VERITAS, have detected for the first time VHE pulsed gamma-rays from the Crab pulsar. Such detections have revealed that the Crab VHE spectrum follows a power-law up to at least 400 GeV, challenging most theoretical models, and opening wide possibilities of detecting more pulsars from the ground with the future Cherenkov Telescope Array (CTA). In this contribution, we study the capabilities of CTA for detecting Fermi pulsars. For this, we extrapolate their spectra with "Crab-like" power-law tails in the VHE range, as suggested by the latest MAGIC and VERITAS results.Comment: 4 pages, 3 figures. In Proceedings of the 2012 Heidelberg Symposium on High Energy Gamma-Ray Astronomy. All CTA contributions at arXiv:1211.184

Sharing by Design: Data and Decentralized Commons

Ambitious international data-sharing initiatives have existed for years in fields such as genomics, earth science, and astronomy. But to realize the promise of large-scale sharing of scientific data, intellectual property (IP), data privacy, national security, and other legal and policy obstacles must be overcome. While these issues have attracted significant attention in the corporate world, they have been less appreciated in academic and governmental settings, where solving issues of legal interoperability among data pools in different jurisdictions has taken a back seat to addressing technical challenges. Yet failing to account for legal and policy issues at the outset of a large transborder data-sharing project can lead to undue resource expenditures and data-sharing structures that may offer fewer benefits than hoped. We propose a framework to help planners create data-sharing arrangements with a focus on critical early-stage design decisions including options for legal interoperability

EEG-Based User Reaction Time Estimation Using Riemannian Geometry Features

Riemannian geometry has been successfully used in many brain-computer interface (BCI) classification problems and demonstrated superior performance. In this paper, for the first time, it is applied to BCI regression problems, an important category of BCI applications. More specifically, we propose a new feature extraction approach for Electroencephalogram (EEG) based BCI regression problems: a spatial filter is first used to increase the signal quality of the EEG trials and also to reduce the dimensionality of the covariance matrices, and then Riemannian tangent space features are extracted. We validate the performance of the proposed approach in reaction time estimation from EEG signals measured in a large-scale sustained-attention psychomotor vigilance task, and show that compared with the traditional powerband features, the tangent space features can reduce the root mean square estimation error by 4.30-8.30%, and increase the estimation correlation coefficient by 6.59-11.13%.Comment: arXiv admin note: text overlap with arXiv:1702.0291