155 research outputs found
Search for Galactic dark matter substructures with Cherenkov telescopes
Weakly interacting massive dark matter (DM) particles are expected to
self-annihilate or decay, generating high-energy photons in these processes.
This establishes the possibility for indirect detection of DM by \gamma-ray
telescopes. For probing the secondary products of DM, accurate knowledge about
the DM density distribution in potential astrophysical targets is crucial. In
this contribution, the prospects for the detection of subhalos in the Galactic
DM halo with present and future imaging atmospheric Cherenkov telescopes (IACT)
are investigated. The source count distribution and angular power spectra for
\gamma-rays originating from annihilating DM in subhalos are calculated from
N-body simulation results. To study the systematic uncertainties coming from
the modeling of the DM density distribution, parameters describing the
\gamma-ray yield from subhalos are varied in 16 benchmark models. We conclude
that Galactic subhalos of annihilating DM are probably too faint to be a
promising target for IACT observations, even with the prospective Cherenkov
Telescope Array (CTA).Comment: 8 pages, 5 figures. Included in Proceedings of the 34th International
Cosmic Ray Conference, The Hague, The Netherlands (July 30 - August 6, 2015
VHE Observations of the Binary Candidate HESS J0632+057 with H.E.S.S. and VERITAS
HESS J0632+057 is an unidentified gamma-ray source located in the Monoceros
region, probably associated with the massive Be star MWC 148. H.E.S.S. and
VERITAS observations in the very high energy (VHE) range combined with Swift
X-ray data indicate that this object is a new member of the elusive gamma-ray
binary class. We present here results of VHE gamma-ray observations from
VERITAS and HESS at energies above 100 GeV taken over more than six years. The
observations confirm HESS J0632+057 as a point-like VHE source with a
significance of more than 12 standard deviations. The VHE gamma-ray results are
discussed in the context of contemporaneous X-ray observations with Swift XRT.Comment: Presented at the 32nd ICRC, Beijing, 201
Optimal strategies for observation of active galactic nuclei variability with Imaging Atmospheric Cherenkov Telescopes
Variable emission is one of the defining characteristic of active galactic
nuclei (AGN). While providing precious information on the nature and physics of
the sources, variability is often challenging to observe with time- and
field-of-view-limited astronomical observatories such as Imaging Atmospheric
Cherenkov Telescopes (IACTs). In this work, we address two questions relevant
for the observation of sources characterized by AGN-like variability: what is
the most time-efficient way to detect such sources, and what is the
observational bias that can be introduced by the choice of the observing
strategy when conducting blind surveys of the sky. Different observing
strategies are evaluated using simulated light curves and realistic instrument
response functions of the Cherenkov Telescope Array (CTA), a future gamma-ray
observatory. We show that strategies that makes use of very small observing
windows, spread over large periods of time, allows for a faster detection of
the source, and are less influenced by the variability properties of the
sources, as compared to strategies that concentrate the observing time in a
small number of large observing windows. Although derived using CTA as an
example, our conclusions are conceptually valid for any IACTs facility, and in
general, to all observatories with small field of view and limited duty cycle.Comment: 14 pages, 11 figure
Improved /hadron separation for the detection of faint gamma-ray sources using boosted decision trees
Imaging atmospheric Cherenkov telescopes record an enormous number of
cosmic-ray background events. Suppressing these background events while
retaining -rays is key to achieving good sensitivity to faint
-ray sources. The differentiation between signal and background events
can be accomplished using machine learning algorithms, which are already used
in various fields of physics. Multivariate analyses combine several variables
into a single variable that indicates the degree to which an event is
-ray-like or cosmic-ray-like. In this paper we will focus on the use of
boosted decision trees for /hadron separation. We apply the method to
data from the Very Energetic Radiation Imaging Telescope Array System
(VERITAS), and demonstrate an improved sensitivity compared to the VERITAS
standard analysis.Comment: accepted for publication in Astroparticle Physic
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