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The Cherenkov Telescope Array
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The Cherenkov Telescope Array Observatory (CTAO) is a next-generation facility for ground-based very high energy gamma ray astronomy. CTAO will be operated as an open observatory. With two sites, in the northern and southern hemispheres, the Cherenkov Telescope Array CTA will provide full-sky coverage, improving sensitivity by an order of magnitude over current instruments, with a wide gamma ray energy coverage from 20 GeV to 300 TeV. CTA will use telescope arrays composed of three types of telescopes, optimized to cover different energy ranges. The large telescopes covering the lowest energies provide rapid slewing capability, for follow-up of transients. Key Science Projects (KSPs) are developed to form a significant part of the CTAO observing program during the first decade of operation, providing legacy data sets such as surveys or deep observations of key targets.
Forward citations
Cited by 5 Pith papers
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Predicting Multiwavelength Emission Associated with X-Ray Flares and Extended Emission of Gamma-Ray Bursts
A one-zone synchrotron model of GRB X-ray flares predicts UV and VHE counterparts detectable together about once every three years, separating jet dissipation radius and Lorentz factor regimes.
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Prediction of radio-quiet gamma-ray pulsar distances using the Fundamental Plane relation
Distances for 62 radio-quiet gamma-ray pulsars are predicted for the first time using a fundamental plane relation fitted with OLS, random forest, and support vector regression on Fermi 3PC data.
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Hunting Star-Forming Galaxies in the Gamma-Ray Domain
A revised GeV Lgamma-SFR correlation and SFR-scaled spectra suggest about a dozen star-forming galaxies, including M83, M33, NGC 1068, NGC 4945, and Circinus, may be detectable by CTAO, LHAASO, or SWGO.
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Searching for dark matter annihilating into light long-lived mediators from stars inside dwarf spheroidal galaxies
Fermi-LAT observations of ten dwarf spheroidals place upper limits on dark matter-nucleon scattering by modeling stellar capture and annihilation through long-lived mediators.
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GraphNeT 2.0 -- A Deep Learning Library for Neutrino Telescopes
A detector-agnostic deep learning library for neutrino telescopes is updated to support multiple model architectures and experiment-specific data conversion.
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