Related papers: DNN-based Signal Processing for Liquid Argon Time …
The ArgoNeuT liquid argon time projection chamber has collected thousands of neutrino and antineutrino events during an extended run period in the NuMI beam-line at Fermilab. This paper focuses on the main aspects of the detector layout and…
Recurrent Neural Networks (RNN) are extensively employed for processing sequential data such as time series. Reservoir computing (RC) has drawn attention as an RNN framework due to its fixed network that does not require training, making it…
The Deep Underground Neutrino Experiment (DUNE) is a 40-kton underground liquid argon time-projection-chamber (LAr TPC) detector, for long-baseline neutrino oscillation studies and for neutrino astrophysics and nucleon decay searches.…
Underground physics experiments such as dark matter direct detection need to keep control of the background contribution. Hosting these experiments in underground facilities helps to minimize certain background sources such as the cosmic…
We present work on the detection of neutral particles via nuclear recoils in gas-filled Time Projection Chambers (TPCs). We employ Gas Electron Multipliers (GEMs) to amplify the signal and silicon pixel electronics to detect the avalanche…
A 10 kilo-tonne dual-phase liquid argon TPC is one of the detector options considered for the Deep Underground Neutrino Experiment (DUNE). The detector technology relies on amplification of the ionisation charge in ultra-pure argon vapour…
The ICARUS liquid argon time projection chamber (LArTPC) neutrino detector has been taking physics data since 2022 as part of the Short-Baseline Neutrino (SBN) Program. This paper details the equalization of the response to charge in the…
Deep Neural Networks (DNNs) can achieve state-of-the-art accuracy in many computer vision tasks, such as object counting. Object counting takes two inputs: an image and an object query and reports the number of occurrences of the queried…
Deep learning methods based synthetic aperture radar (SAR) image target recognition tasks have been widely studied currently. The existing deep methods are insufficient to perceive and mine the scattering information of SAR images,…
In time-varying fading channels, channel coefficients are estimated using pilot symbols that are transmitted every coherence interval. For channels with high Doppler spread, the rapid channel variations over time will require considerable…
A number of liquid argon time projection chambers (LAr TPC's) are being build or are proposed for neutrino experiments on long- and short baseline beams. For these detectors a distortion in the drift field due to geometrical or physics…
Accurate predictions of peptide retention times (RT) in liquid chromatography have many applications in mass spectrometry-based proteomics. Herein, we present DeepRT, a deep learning based software for peptide retention time prediction.…
MicroBooNE (the Micro Booster Neutrino Experiment) is a short-baseline neutrino experiment based on the technology of a liquid-argon time-projection chamber (LArTPC), and has recently completed its first year of data-taking in the Fermilab…
Scintillation light is used in liquid argon (LAr) neutrino detectors to provide a trigger signal, veto information against cosmic rays, and absolute event timing. In this work, we discuss additional opportunities offered by detectors with…
In liquid argon time projection chambers exposed to neutrino beams and running on or near surface levels, cosmic muons and other cosmic particles are incident on the detectors while a single neutrino-induced event is being recorded. In…
In this paper we report on the evidence for ionization track signals from cosmic ray muons and Compton electrons in a Time Projection Chamber (TPC) filled with liquid Argon and doped with different fractions of Nitrogen. This study has been…
Explainability of deep neural networks is one of the most challenging and interesting problems in the field. In this study, we investigate the topic focusing on the interpretability of deep learning-based registration methods. In…
The Deep Underground Neutrino Experiment (DUNE) is a long-baseline neutrino oscillation experiment aiming to measure the oscillation parameters with an unprecedented precision that will allow determining the CP violation phase in the…
Massive underground detectors can be considered as sort of observatories for rare physics phenomena like astrophysical neutrino detection and nucleon decay searches. We briefly overview the past tracking calorimeters developed for nucleon…
We describe in these GLA2011 proceedings the software package LArSoft, a toolkit to perform simulation, analysis and reconstruction with the Liquid Argon (LAr) Time Projection Chambers (TPCs) within the US program of proposed detectors. We…