scholarly journals Mass hierarchy discrimination with atmospheric neutrinos in large volume ice/water Cherenkov detectors

2013 ◽  
Vol 2013 (4) ◽  
Author(s):  
D. Franco ◽  
C. Jollet ◽  
A. Kouchner ◽  
V. Kulikovskiy ◽  
A. Meregaglia ◽  
...  
Keyword(s):  
Large Volume ◽  
Mass Hierarchy ◽  
Atmospheric Neutrinos ◽  
Cherenkov Detectors ◽  
Water Cherenkov Detectors ◽  
Ice Water

scholarly journals Neutrino mass hierarchy determination via atmospheric neutrinos with future detectors

2008 ◽  
Vol 136 (4) ◽  
pp. 042015
Author(s):  
Raj Gandhi ◽  
Pomita Ghoshal ◽  
Srubabati Goswami ◽  
Poonam Mehta ◽  
S Uma Sankar ◽  
...  
Keyword(s):  
Neutrino Mass ◽  
Mass Hierarchy ◽  
Atmospheric Neutrinos ◽  
Neutrino Mass Hierarchy

scholarly journals CNNs for enhanced background discrimination in DSNB searches in large-scale water-Gd detectors

2021 ◽  
Vol 2021 (11) ◽  
pp. 051
Author(s):  
D. Maksimović ◽  
M. Nieslony ◽  
M. Wurm
Keyword(s):  
Large Scale ◽  
Neutral Current ◽  
Direct Analysis ◽  
Atmospheric Neutrinos ◽  
Observation Window ◽  
Novel Method ◽  
Supernova Neutrino ◽  
Large Water ◽  
Water Cherenkov Detectors

Abstract Gadolinium-loading of large water Cherenkov detectors is a prime method for the detection of the Diffuse Supernova Neutrino Background (DSNB). While the enhanced neutron tagging capability greatly reduces single-event backgrounds, correlated events mimicking the IBD coincidence signature remain a potentially harmful background. Neutral-Current (NC) interactions of atmospheric neutrinos potentially dominate the DSNB signal especially in the low-energy range of the observation window that reaches from about 12 to 30 MeV. The present paper investigates a novel method for the discrimination of this background. Convolutional Neural Networks (CNNs) offer the possibility for a direct analysis and classification of the PMT hit patterns of the prompt events. Based on the events generated in a simplified SuperKamiokande-like detector setup, we find that a trained CNN can maintain a signal efficiency of 96% while reducing the residual NC background to 2% of the original rate. Comparing to recent predictions of the DSNB signal and measurements of the NC background levels in Super-Kamiokande, the corresponding signal-to-background ratio is about 4:1, providing excellent conditions for a DSNB discovery.

scholarly journals Simultaneous particles influence on the LAGO’s Water Cherenkov Detectors signals

2021 ◽  
Author(s):  
Luis Otiniano ◽  
Iván Sidelnik ◽  
Mauricio Suárez-Durán ◽  
Christian Sarmiento-Cano ◽  
Hernán Asorey
Keyword(s):  
Cherenkov Detectors ◽  
Water Cherenkov Detectors

scholarly journals A Project to Install Water-Cherenkov Detectors in the Antarctic Peninsula as part of the LAGO Detection Network

2016 ◽  
Author(s):  
Sergio Dasso ◽  
Adriana María Gulisano ◽  
Jimmy Joel Masías-Meza ◽  
Hernán Asorey ◽  
Keyword(s):  
Antarctic Peninsula ◽  
Cherenkov Detectors ◽  
Water Cherenkov Detectors ◽  
The Antarctic
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