BEGIN:VCALENDAR VERSION:2.0 PRODID:-//linuxsoftware.nz//NONSGML Joyous v1.4//EN BEGIN:VEVENT SUMMARY:A next-generation gamma-ray observatory powered by machine learnin g techniques DTSTART:20230302T110000Z DTEND:20230302T130000Z DTSTAMP:20260623T225632Z UID:3941d0fc-6196-4ba2-9098-23abf9d7589c SEQUENCE:5 CREATED:20230301T085456Z DESCRIPTION:Abstract:The Southern Wide-field Gamma-ray Observatory (SWGO) is the next-generation ground-based gamma-ray observatory to survey the So uthern hemisphere sky. The experiment\, currently in an R&\;D phase\, i s expected to have a large array of a few square kilometers composed of wa ter Cherenkov detectors (WCDs) placed at a high altitude (4.4 km a.s.l. or higher) in South America. Such an ambitious project requires the design o f a high-performance and cost-effective WCD to cope with the observatory n eeds\, particularly the capability to identify shower muons\, which is ess ential to ensure excellent gamma/hadron discrimination.In this work\, it i s shown that efficient muon tagging (and counting) can be achieved using w ater Cherenkov detectors with a reduced water volume and multiple PMTs\, p rovided that the PMT signal spatial and time patterns are interpreted by a n analysis based on Machine Learning (ML).The proposed WCDs would highly b oost the physics capabilities of SWGO\, enabling it to cover\, with a wide field of view\, a wide energy range\, from low energies ($\\sim$ 100 GeV) up to the PeV region. LAST-MODIFIED:20230301T085624Z LOCATION:Online (Password: 267692) URL:http://df.vps.tecnico.ulisboa.pt/pt/eventos/a-next-generation-gamma-ra y-observatory-powered-by-machine-learning-techniques/ X-ALT-DESC;FMTTYPE=text/html:

Abstract:
The Southern Wide-field Gamma-ray Observatory (SWGO) is the next-generat ion ground-based gamma-ray observatory to survey the Southern hemisphere s ky. The experiment\, currently in an R&\;D phase\, is expected to have a large array of a few square kilometers composed of water Cherenkov detec tors (WCDs) placed at a high altitude (4.4 km a.s.l. or higher) in South A merica.

Such an ambitious project requires the design of a high- performance and cost-effective WCD to cope with the observatory needs\, pa rticularly the capability to identify shower muons\, which is essential to ensure excellent gamma/hadron discrimination.

In this work\, it is shown that efficient muon tagging (and counting) can be achieved using water Cherenkov detectors with a reduced water volume and multiple PMTs\, provided that the PMT signal spatial and time patterns are interpreted by an analysis based on Machine Learning (ML).
The proposed WCDs would hi ghly boost the physics capabilities of SWGO\, enabling it to cover\, with a wide field of view\, a wide energy range\, from low energies ($\\sim$ 10 0 GeV) up to the PeV region.

END:VEVENT END:VCALENDAR