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Register a new userTiming analysis techniques at large core distances for multi-TeV gamma ray astronomy
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We present an analysis technique that uses the timing information of Cherenkov images from extensive air showers (EAS). Our emphasis is on distant, or large core distance gamma-ray induced showers at multi-TeV energies. Specifically, combining pixel timing information with an improved direction reconstruction algorithm, leads to improvements in angular and core resolution as large as ~40% and ~30%, respectively, when compared with the same algorithm without the use of timing. Above 10 TeV, this results in an angular resolution approaching 0.05 degrees, together with a core resolution better than ~15 m. The off-axis post-cut gamma-ray acceptance is energy dependent and its full width at half maximum ranges from 4 degrees to 8 degrees. For shower directions that are up to ~6 degrees off-axis, the angular resolution achieved by using timing information is comparable, around 100 TeV, to the on-axis angular resolution. The telescope specifications and layout we describe here are geared towards energies above 10 TeV. However, the methods can in principle be applied to other energies, given suitable telescope parameters. The 5-telescope cell investigated in this study could initially pave the way for a larger array of sparsely spaced telescopes in an effort to push the collection area to >10 km2. These results highlight the potential of a `sparse array approach in effectively opening up the energy range above 10 TeV.
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The High Energy Stereoscopic System (H.E.S.S.) is one of the currently operating Imaging Atmospheric Cherenkov Telescopes. H.E.S.S. operates in the broad energy range from a few tens of GeV to more than 50 TeV reaching its best sensitivity around 1 TeV. In this contribution, we present an analysis technique, which is optimised for the detection at the highest energies accessible to H.E.S.S. and aimed to improve the sensitivity above 10 TeV. It includes the employment of improved event direction reconstruction and gamma-hadron separation. For the first time, also extensive air showers with event offsets up to 4.5$^{circ}$ from the camera centre are considered in the analysis, thereby increasing the effective Field-of-View of H.E.S.S. from 5$^{circ}$ to 9$^{circ}$. Key performance parameters of the new high-energy analysis are presented and its applicability demonstrated for representative hard-spectrum sources in the Milky Way.
The field of TeV gamma-ray astronomy has produced many exciting results over the last decade. Both the source catalogue, and the range of astrophysical questions which can be addressed, continue to expand. This article presents a topical review of the field, with a focus on the observational results of the imaging atmospheric Cherenkov telescope arrays. The results encompass pulsars and their nebulae, supernova remnants, gamma-ray binary systems, star forming regions and starburst and active galaxies.
How should we invest our available resources to best sustain astronomys track record of discovery, established over the past few decades? Two strong hints come from (1) our history of astronomical discoveries and (2) literature citation patterns that reveal how discovery and development activities in science are strong functions of team size. These argue that progress in astronomy hinges on support for a diversity of research efforts in terms of team size, research tools and platforms, and investment strategies that encourage risk taking. These ideas also encourage us to examine the implications of the trend toward big team science and survey science in astronomy over the past few decades, and to reconsider the common assumption that progress in astronomy always means trading up to bigger apertures and facilities. Instead, the considerations above argue that we need a balanced set of investments in small- to large-scale initiatives and team sizes both large and small. Large teams tend to develop existing ideas, whereas small teams are more likely to fuel the future with disruptive discoveries. While large facilities are the value investments that are guaranteed to produce discoveries, smaller facilities are the growth stocks that are likely to deliver the biggest science bang per buck, sometimes with outsize returns. One way to foster the risk taking that fuels discovery is to increase observing opportunity, i.e., create more observing nights and facilitate the exploration of science-ready data.
The field of time-domain astrophysics has entered the era of Multi-messenger Astronomy (MMA). One key science goal for the next decade (and beyond) will be to characterize gravitational wave (GW) and neutrino sources using the next generation of Extremely Large Telescopes (ELTs). These studies will have a broad impact across astrophysics, informing our knowledge of the production and enrichment history of the heaviest chemical elements, constrain the dense matter equation of state, provide independent constraints on cosmology, increase our understanding of particle acceleration in shocks and jets, and study the lives of black holes in the universe. Future GW detectors will greatly improve their sensitivity during the coming decade, as will near-infrared telescopes capable of independently finding kilonovae from neutron star mergers. However, the electromagnetic counterparts to high-frequency (LIGO/Virgo band) GW sources will be distant and faint and thus demand ELT capabilities for characterization. ELTs will be important and necessary contributors to an advanced and complete multi-messenger network.
The analysis and combination of data from different gamma-ray instruments involves the use of collaboration proprietary software and case-by-case methods. The effort of defining a common data format for high-level data, namely event lists and instrument response functions (IRFs), has recently started for very-high-energy gamma-ray instruments, driven by the upcoming Cherenkov Telescope Array (CTA). In this work we implemented this prototypical data format for a small set of MAGIC, VERITAS, FACT, and H.E.S.S. Crab nebula observations, and we analyzed them with the open-source gammapy software package. By combining data from $Fermi$-LAT, and from four of the currently operating imaging atmospheric Cherenkov telescopes, we produced a joint maximum likelihood fit of the Crab nebula spectrum. Aspects of the statistical errors and the evaluation of systematic uncertainty are also commented upon, along with the release format of spectral measurements. The results presented in this work are obtained using open-access on-line assets that allow for a long-term reproducibility of the results.
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