177 citations · 2.7k across the 164 of their papers we have counts for
21 papers · 1 filter
Measurement of the Atmospheric Muon Rate with the MicroBooNE Liquid Argon TPC
MicroBooNE collaboration, C. Adams, M. Alrashed +187
MicroBooNE is a near-surface liquid argon (LAr) time projection chamber (TPC) located at Fermilab. We measure the characterisation of muons originating from cosmic interactions in…
Semantic Segmentation with a Sparse Convolutional Neural Network for Event Reconstruction in MicroBooNE
MicroBooNE collaboration, P. Abratenko, M. Alrashed +180
We present the performance of a semantic segmentation network, SparseSSNet, that provides pixel-level classification of MicroBooNE data. The MicroBooNE experiment employs a liquid…
High-performance Generic Neutrino Detection in a LArTPC near the Earth's Surface with the MicroBooNE Detector
MicroBooNE collaboration, P. Abratenko, M. Alrashed +186
Large Liquid Argon Time Projection Chambers (LArTPCs) are being increasingly adopted in neutrino oscillation experiments because of their superb imaging capabilities through the co…
Neutrino Event Selection in the MicroBooNE Liquid Argon Time Projection Chamber using Wire-Cell 3-D Imaging, Clustering, and Charge-Light Matching
MicroBooNE collaboration, P. Abratenko, M. Alrashed +182
An accurate and efficient event reconstruction is required to realize the full scientific capability of liquid argon time projection chambers (LArTPCs). The current and future neut…
Measurement of Differential Cross Sections for -Ar Charged-Current Interactions with Protons and no Pions in the Final State with the MicroBooNE Detector
MicroBooNE collaboration, P. Abratenko, M. Alrashed +182
We present an analysis of MicroBooNE data with a signature of one muon, no pions, and at least one proton above a momentum threshold of 300 MeV/c (CC0Np). This is the first diff…
A Convolutional Neural Network for Multiple Particle Identification in the MicroBooNE Liquid Argon Time Projection Chamber
MicroBooNE collaboration, P. Abratenko, M. Alrashed +184
We present the multiple particle identification (MPID) network, a convolutional neural network (CNN) for multiple object classification, developed by MicroBooNE. MPID provides the…
The Continuous Readout Stream of the MicroBooNE Liquid Argon Time Projection Chamber for Detection of Supernova Burst Neutrinos
MicroBooNE collaboration, P. Abratenko, M. Alrashed +185
The MicroBooNE continuous readout stream is a parallel readout of the MicroBooNE liquid argon time projection chamber (LArTPC) which enables detection of non-beam events such as th…
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…
Measurement of Space Charge Effects in the MicroBooNE LArTPC Using Cosmic Muons
MicroBooNE collaboration, P. Abratenko, M. Alrashed +184
Large liquid argon time projection chambers (LArTPCs), especially those operating near the surface, are susceptible to space charge effects. In the context of LArTPCs, the space ch…
Speeding up Particle Track Reconstruction using a Parallel Kalman Filter Algorithm
Steven Lantz, Kevin McDermott, Michael Reid +16
One of the most computationally challenging problems expected for the High-Luminosity Large Hadron Collider (HL-LHC) is determining the trajectory of charged particles during event…
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…
Long-baseline neutrino oscillation physics potential of the DUNE experiment
DUNE Collaboration, B. Abi, R. Acciarri +966
The sensitivity of the Deep Underground Neutrino Experiment (DUNE) to neutrino oscillation is determined, based on a full simulation, reconstruction, and event selection of the far…
First Measurement of Differential Charged Current Quasielastic-like -Argon Scattering Cross Sections with the MicroBooNE Detector
P. Abratenko, M. Alrashed, R. An +181
We report on the first measurement of flux-integrated single differential cross sections for charged-current (CC) muon neutrino () scattering on argon with a muon and a proton…
Deep Underground Neutrino Experiment (DUNE), Far Detector Technical Design Report, Volume II: DUNE Physics
B. Abi, R. Acciarri, Mario A. Acero +958
The preponderance of matter over antimatter in the early universe, the dynamics of the supernovae that produced the heavy elements necessary for life, and whether protons eventuall…
Graph Neural Networks for Particle Reconstruction in High Energy Physics detectors
Xiangyang Ju, Steven Farrell, Paolo Calafiura +20
Pattern recognition problems in high energy physics are notably different from traditional machine learning applications in computer vision. Reconstruction algorithms identify and…
Vertex-Finding and Reconstruction of Contained Two-track Neutrino Events in the MicroBooNE Detector
MicroBooNE collaboration, P. Abratenko, M. Alrashed +186
We describe algorithms developed to isolate and accurately reconstruct two-track events that are contained within the MicroBooNE detector. This method is optimized to reconstruct t…
Reconstruction of Charged Particle Tracks in Realistic Detector Geometry Using a Vectorized and Parallelized Kalman Filter Algorithm
Giuseppe Cerati, Peter Elmer, Brian Gravelle +14
One of the most computationally challenging problems expected for the High-Luminosity Large Hadron Collider (HL-LHC) is finding and fitting particle tracks during event reconstruct…
Reconstruction for Liquid Argon TPC Neutrino Detectors Using Parallel Architectures
Sophie Berkman, Giuseppe Cerati, Brian Gravelle +3
Neutrinos are particles that interact rarely, so identifying them requires large detectors which produce lots of data. Processing this data with the computing power available is be…
Deep Underground Neutrino Experiment (DUNE), Far Detector Technical Design Report, Volume III: DUNE Far Detector Technical Coordination
B. Abi, R. Acciarri, Mario A. Acero +958
The preponderance of matter over antimatter in the early universe, the dynamics of the supernovae that produced the heavy elements necessary for life, and whether protons eventuall…
Deep Underground Neutrino Experiment (DUNE), Far Detector Technical Design Report, Volume I: Introduction to DUNE
B. Abi, R. Acciarri, Mario A. Acero +958
The preponderance of matter over antimatter in the early universe, the dynamics of the supernovae that produced the heavy elements necessary for life, and whether protons eventuall…