Deep neural networks for energy and position reconstruction in EXO-200
Work
Year: 2018
Type: article
Abstract: We apply deep neural networks (DNN) to data from the EXO-200 experiment. In the studied cases, the DNN is able to reconstruct the relevant parameters—total energy and position—directly from raw digiti... more
Source: Journal of Instrumentation
Institutions SLAC National Accelerator Laboratory, Stanford University, University of Alabama, Friedrich-Alexander-Universität Erlangen-Nürnberg, Indiana University Bloomington +20 more
Cites: 28
Cited by: 46
Related to: 10
FWCI: 2.289
Citation percentile (by year/subfield): 85.84
Subfield: Nuclear and High Energy Physics
Field: Physics and Astronomy
Domain: Physical Sciences
Sustainable Development Goal Affordable and clean energy
Open Access status: green