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Neural Networks approach to event reconstruction for the GAPS experiment
GAPS Collaboration
Physics
Center for Particle and Gravitational Astrophysics
Research output
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Contribution to journal
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Conference article
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peer-review
Overview
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Dive into the research topics of 'Neural Networks approach to event reconstruction for the GAPS experiment'. Together they form a unique fingerprint.
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Keyphrases
Spectrometer
100%
Neural Network Method
100%
Particle Identification
100%
Event Reconstruction
100%
Antiparticle
100%
Low Energy
33%
Accurate Determination
33%
Ultra-low
33%
Machine Learning Techniques
33%
Novel Technique
33%
Dark Matter Annihilation
33%
Energy Deposition
33%
Antinuclei
33%
Galactic Halo
33%
Austral Summer
33%
Antideuteron
33%
Exotic Atoms
33%
Astrophysical Backgrounds
33%
Dark Matter Decay
33%
Balloon Experiment
33%
First Flight
33%
Deposition Pattern
33%
Summer 2022
33%
Physics
Neural Network
100%
Antiparticle
100%
Dark Matter
33%
Machine Learning
33%
Galactic Halos
33%
Exotic Atom
33%