319 citations · 1.8k across the 29 of their papers we have counts for
29 papers
Reconstruction of interactions in the ProtoDUNE-SP detector with Pandora
DUNE Collaboration, A. Abed Abud, B. Abi +1220
The Pandora Software Development Kit and algorithm libraries provide pattern-recognition logic essential to the reconstruction of particle interactions in liquid argon time project…
Reconstruction of Large Radius Tracks with the Exa.TrkX pipeline
Chun-Yi Wang, Xiangyang Ju, Shih-Chieh Hsu +22
Particle tracking is a challenging pattern recognition task at the Large Hadron Collider (LHC) and the High Luminosity-LHC. Conventional algorithms, such as those based on the Kalm…
A Gaseous Argon-Based Near Detector to Enhance the Physics Capabilities of DUNE
A. Abed Abud, B. Abi, R. Acciarri +1239
This document presents the concept and physics case for a magnetized gaseous argon-based detector system (ND-GAr) for the Deep Underground Neutrino Experiment (DUNE) Near Detector.…
Tau Neutrinos in the Next Decade: from GeV to EeV
Roshan Mammen Abraham, Jaime Alvarez-Muñiz, Carlos A. Argüelles +63
Tau neutrinos are the least studied particle in the Standard Model. This whitepaper discusses the current and expected upcoming status of tau neutrino physics with attention to the…
Accelerating the Inference of the Exa.TrkX Pipeline
Alina Lazar, Xiangyang Ju, Daniel Murnane +21
Recently, graph neural networks (GNNs) have been successfully used for a variety of particle reconstruction problems in high energy physics, including particle tracking. The Exa.Tr…
Search for active-sterile antineutrino mixing using neutral-current interactions with the NOvA experiment
M. A. Acero, P. Adamson, L. Aliaga +196
This Letter reports results from the first long-baseline search for sterile antineutrinos mixing in an accelerator-based antineutrino-dominated beam. The rate of neutral-current in…
Performance of a Geometric Deep Learning Pipeline for HL-LHC Particle Tracking
Xiangyang Ju, Daniel Murnane, Paolo Calafiura +21
The Exa.TrkX project has applied geometric learning concepts such as metric learning and graph neural networks to HEP particle tracking. Exa.TrkX's tracking pipeline groups detecto…
Search for Slow Magnetic Monopoles with the NOvA Detector on the Surface
NOvA Collaboration, M. A. Acero, P. Adamson +196
We report a search for a magnetic monopole component of the cosmic-ray flux in a 95-day exposure of the NOvA experiment's Far Detector, a 14 kt segmented liquid scintillator detect…
Prospects for Beyond the Standard Model Physics Searches at the Deep Underground Neutrino Experiment
DUNE Collaboration, B. Abi, R. Acciarri +970
The Deep Underground Neutrino Experiment (DUNE) will be a powerful tool for a variety of physics topics. The high-intensity proton beams provide a large neutrino flux, sampled by a…
First results on ProtoDUNE-SP liquid argon time projection chamber performance from a beam test at the CERN Neutrino Platform
DUNE Collaboration, B. Abi, A. Abed Abud +987
The ProtoDUNE-SP detector is a single-phase liquid argon time projection chamber with an active volume of m. It is installed at the CERN Neutrino Plat…
Track Seeding and Labelling with Embedded-space Graph Neural Networks
Nicholas Choma, Daniel Murnane, Xiangyang Ju +16
To address the unprecedented scale of HL-LHC data, the Exa.TrkX project is investigating a variety of machine learning approaches to particle track reconstruction. The most promisi…
Adjusting Neutrino Interaction Models and Evaluating Uncertainties using NOvA Near Detector Data
NOvA Collaboration, M. A. Acero, P. Adamson +192
The two-detector design of the NOvA neutrino oscillation experiment, in which two functionally identical detectors are exposed to an intense neutrino beam, aids in canceling leadin…
Supernova neutrino detection in NOvA
NOvA Collaboration, M. A. Acero, P. Adamson +199
The NOvA long-baseline neutrino experiment uses a pair of large, segmented, liquid-scintillator calorimeters to study neutrino oscillations, using GeV-scale neutrinos from the Ferm…
Search for multi-messenger signals in NOvA coincident with LIGO/Virgo detections
NOvA Collaboration, M. A. Acero, P. Adamson +177
Using the NOvA neutrino detectors, a broad search has been performed for any signal coincident with 28 gravitational wave events detected by the LIGO/Virgo Collaboration between Se…
First measurement of neutrino oscillation parameters using neutrinos and antineutrinos by NOvA
M. A. Acero, P. Adamson, L. Aliaga +196
The NOvA experiment has made a -significant observation of appearance in a 2 GeV beam at a distance of 810 km. Using protons on tar…
Observation of seasonal variation of atmospheric multiple-muon events in the NOvA Near Detector
M. A. Acero, P. Adamson, L. Aliaga +188
Using two years of data from the NOvA Near Detector at Fermilab, we report a seasonal variation of cosmic ray induced multiple-muon event rates which has an opposite phase to the s…
Design and construction of the MicroBooNE Cosmic Ray Tagger system
MicroBooNE collaboration, C. Adams, M. Alrashed +171
The MicroBooNE detector utilizes a liquid argon time projection chamber (LArTPC) with an 85 t active mass to study neutrino interactions along the Booster Neutrino Beam (BNB) at Fe…
First Measurement of Charged-Current Production on Argon with a LArTPC
MicroBooNE collaboration, C. Adams, M. Alrashed +172
We report the first measurement of the flux-integrated cross section of charged-current single production on argon. This measurement is performed with the MicroBooNE…
A Deep Neural Network for Pixel-Level Electromagnetic Particle Identification in the MicroBooNE Liquid Argon Time Projection Chamber
MicroBooNE collaboration, C. Adams, M. Alrashed +170
We have developed a convolutional neural network (CNN) that can make a pixel-level prediction of objects in image data recorded by a liquid argon time projection chamber (LArTPC) f…
Comparison of νμ-Ar multiplicity distributions observed by MicroBooNE to GENIE model predictions
C. Adams, R. An, J. Anthony +162
We measure a large set of observables in inclusive charged current muon neutrino scattering on argon with the MicroBooNE liquid argon time projection chamber operating at Fermilab.…
Ionization Electron Signal Processing in Single Phase LArTPCs II. Data/Simulation Comparison and Performance in MicroBooNE
MicroBooNE collaboration, C. Adams, R. An +168
The single-phase liquid argon time projection chamber (LArTPC) provides a large amount of detailed information in the form of fine-grained drifted ionization charge from particle t…
Ionization Electron Signal Processing in Single Phase LArTPCs I. Algorithm Description and Quantitative Evaluation with MicroBooNE Simulation
MicroBooNE collaboration, C. Adams, R. An +166
We describe the concept and procedure of drifted-charge extraction developed in the MicroBooNE experiment, a single-phase liquid argon time projection chamber (LArTPC). This techni…
The Pandora multi-algorithm approach to automated pattern recognition of cosmic-ray muon and neutrino events in the MicroBooNE detector
MicroBooNE collaboration, R. Acciarri, C. Adams +145
The development and operation of Liquid-Argon Time-Projection Chambers for neutrino physics has created a need for new approaches to pattern recognition in order to fully exploit t…
Measurement of cosmic-ray reconstruction efficiencies in the MicroBooNE LArTPC using a small external cosmic-ray counter
MicroBooNE collaboration, R. Acciarri, C. Adams +148
The MicroBooNE detector is a liquid argon time projection chamber at Fermilab designed to study short-baseline neutrino oscillations and neutrino-argon interaction cross-section. D…