activity
20142022
most citedBackground rejection in NEXT using deep neural networks

66 citations · 131 across the 5 of their papers we have counts for

collaborators

5 papers

hep-ex2022

Cosmic ray muon clustering for the MicroBooNE liquid argon time projection chamber using sMask-RCNN

MicroBooNE collaboration, P. Abratenko, R. An +188

In this article, we describe a modified implementation of Mask Region-based Convolutional Neural Networks (Mask-RCNN) for cosmic ray muon clustering in a liquid argon TPC and appli…

physics.ins-det201666 cited

Background rejection in NEXT using deep neural networks

NEXT Collaboration, J. Renner, A. Farbin +64

We investigate the potential of using deep learning techniques to reject background events in searches for neutrinoless double beta decay with high pressure xenon time projection c…

physics.ins-det20142 cited

Results of the material screening program of the NEXT experiment

T. Dafni, V. Alvarez, I. Bandac +67

The 'Neutrino Experiment with a Xenon TPC (NEXT)', intended to investigate neutrinoless double beta decay, requires extremely low background levels. An extensive material screening…

physics.ins-det201436 cited

Radiopurity assessment of the tracking readout for the NEXT double beta decay experiment

S. Cebrián, J. Pérez, I. Bandac +68

The Neutrino Experiment with a Xenon Time-Projection Chamber (NEXT) is intended to investigate the neutrinoless double beta decay of 136Xe, which requires a severe suppression of p…

physics.ins-det201427 cited

Characterisation of NEXT-DEMO using xenon K X-rays

NEXT Collaboration, D. Lorca, J. Martín-Albo +63

The NEXT experiment aims to observe the neutrinoless double beta decay of Xe in a high pressure gas TPC using electroluminescence (EL) to amplify the signal from ionization…