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SNEWS 2.0: A Next-Generation SuperNova Early Warning System for Multi-messenger Astronomy

Author(s)
Winslow, Lindley
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Creative Commons Attribution 4.0 International License https://creativecommons.org/licenses/by/4.0
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Abstract
<jats:title>Abstract</jats:title> <jats:p>The next core-collapse supernova in the Milky Way or its satellites will represent a once-in-a-generation opportunity to obtain detailed information about the explosion of a star and provide significant scientific insight for a variety of fields because of the extreme conditions found within. Supernovae in our galaxy are not only rare on a human timescale but also happen at unscheduled times, so it is crucial to be ready and use all available instruments to capture all possible information from the event. The first indication of a potential stellar explosion will be the arrival of a bright burst of neutrinos. Its observation by multiple detectors worldwide can provide an early warning for the subsequent electromagnetic fireworks, as well as signal to other detectors with significant backgrounds so they can store their recent data. The supernova early warning system (SNEWS) has been operating as a simple coincidence between neutrino experiments in automated mode since 2005. In the current era of multi-messenger astronomy there are new opportunities for SNEWS to optimize sensitivity to science from the next galactic supernova beyond the simple early alert. This document is the product of a workshop in June 2019 towards design of SNEWS 2.0, an upgraded SNEWS with enhanced capabilities exploiting the unique advantages of prompt neutrino detection to maximize the science gained from such a valuable event.</jats:p>
Date issued
2021
URI
https://hdl.handle.net/1721.1/142360
Department
Massachusetts Institute of Technology. Department of Physics
Journal
New Journal of Physics
Publisher
IOP Publishing
Citation
Winslow, Lindley. 2021. "SNEWS 2.0: A Next-Generation SuperNova Early Warning System for Multi-messenger Astronomy." New Journal of Physics, 23 (3).
Version: Final published version

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