The Pandora multi-algorithm approach to automated pattern recognition of cosmic-ray muon and neutrino events in the MicroBooNE detector

@article{Acciarri2018ThePM,
  title={The Pandora multi-algorithm approach to automated pattern recognition of cosmic-ray muon and neutrino events in the MicroBooNE detector},
  author={R. Acciarri and Claudia Adams and Rui An and J. Anthony and Jonathan Asaadi and Martin Auger and L. Bagby and Supraja Balasubramanian and Bruce R. Baller and Chris P. Barnes and Giles David Barr and Matthew Bass and F. Bay and M. R. Bishai and A. Blake and T. Bolton and Leslie Camilleri and David Caratelli and Benjamin P. Carls and R. Castillo Fernandez and F. Cavanna and Hucheng Chen and Eric D. Church and Davio Cianci and E. O. Cohen and Gabriel H. Collin and Janet M. Conrad and M. E. Convery and J. I. Crespo-Anad{\'o}n and Marco del Tutto and Drew Devitt and Steven Dytman and B. Eberly and Antonio Ereditato and L. Escudero Sanchez and Jessica N. Esquivel and A. A. Fadeeva and B. T. Fleming and W. Foreman and A. P. Furmanski and D. Garcia-Gamez and Gerald T. Garvey and Victor Genty and Damian Goeldi and Sowjanya Gollapinni and Nicholas Graf and Elena Gramellini and Herbert Greenlee and Ryan Grosso and R. Guenette and Ariana Hackenburg and Pip Hamilton and O. Hen and Jeremy Hewes and C. Hill and Johnny Ho and Glenn Horton-Smith and Adrien Hourlier and E. C. Huang and C. W. James and J. Jan de Vries and C-M. Jen and L X Jiang and R. A. Johnson and Jyothirmai Joshi and Hans Jostlein and David Kaleko and G. Karagiorgi and Wesley Ketchum and Brian Kirby and M. Kirby and Thomas R. Kobilarcik and Igor E. Kreslo and A. Laube and Yaqiao Li and Adam Robert Andover Lister and B. R. Littlejohn and S. Lockwitz and David Lorca and W. C. Louis and Martin Luethi and Bengt Lundberg and X. Luo and Alberto Marchionni and C. Mariani and J. S. Marshall and D. A. Martinez Caicedo and V. Meddage and Tia Miceli and Geoffrey B. Mills and Jarrett Moon and M. Mooney and Craig D. Moore and J. Mousseau and R. Murrells and Donna Lynne Naples and Paul Joseph Nienaber and J. A. Nowak and Ornella Palamara and Vittorio Paolone and Vassilios G. Papavassiliou and Stephen F. Pate and Žarko Pavlovi{\'c} and Eliezer Piasetzky and Donald T. Porzio and Gregory W. Pulliam and Xin Qian and J L Raaf and A. Rafique and Leon S. Rochester and C. Rudolf von Rohr and B. Russell and D. W. Schmitz and Anne Schukraft and William Seligman and M. H. Shaevitz and James Sinclair and Alexandria Smith and Erica Snider and M. Soderberg and S. S{\"o}ldner-Rembold and Stefano Roberto Soleti and Panagiotis Spentzouris and Joshua Spitz and John St. John and Thomas Strauss and A. Szelc and N. J. Tagg and Kazuhiro Terao and M. A. Thomson and M. Toups and Y. T. Tsai and S. Tufanli and Tracy Usher and Wouter Van De Pontseele and Richard Van De Water and Brett Viren and M. Weber and D. A. Wickremasinghe and Stephen Wolbers and Taritree Wongjirad and Katherine Woodruff and T. Yang and Lauren E. Yates and Geralyn P. Zeller and J. Zennamo and C. C. Zhang},
  journal={The European Physical Journal. C, Particles and Fields},
  year={2018},
  volume={78}
}
  • R. Acciarri, C. Adams, +144 authors C. Zhang
  • Published 10 August 2017
  • Physics, Medicine
  • The European Physical Journal. C, Particles and Fields
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 the imaging capabilities offered by this technology. Whereas the human brain can excel at identifying features in the recorded events, it is a significant challenge to develop an automated, algorithmic solution. The Pandora Software Development Kit provides functionality to aid the design and implementation of pattern… 
Neutrino event selection in the MicroBooNE liquid argon time projection chamber using Wire-Cell 3D imaging, clustering, and charge-light matching
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 neutrino experiments
Measurement of cosmic-ray reconstruction efficiencies in the MicroBooNE LArTPC using a small external cosmic-ray counter
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. Due to its location
Wire-Cell 3D Pattern Recognition Techniques for Neutrino Event Reconstruction in Large LArTPCs: Algorithm Description and Quantitative Evaluation with MicroBooNE Simulation
Wire-Cell is a 3D event reconstruction package for liquid argon time projection chambers. Through geometry, time, and drifted charge from multiple readout wire planes, 3D space points with associated
Neutron-antineutron oscillation search with MicroBooNE and DUNE
The Deep Underground Neutrino Experiment (DUNE) is an international project planned for measurements in neutrino physics and astrophysics and searches for phenomena predicted by theories Beyond the
Search for a Low Energy Excess in MicroBooNE
MicroBooNE (the Micro Booster Neutrino Experiment) is a liquid argon time-projection chamber (TPC) experiment designed for short-baseline neutrino physics, currently running at Fermilab. It aims to
Search for Electron Neutrinos in Multiple Topologies with the MicroBooNE Experiment
  • 2020
This note presents the status of the measurement of electron neutrinos from the Fermilab Booster Neutrino Beamline (BNB) with the MicroBooNE experiment. The analysis is aimed at investigating the
Cosmic Ray Background Removal With Deep Neural Networks in SBND
TLDR
This work demonstrates a novel application of deep learning techniques to remove background particles by applying deep learning on full detector images from the SBND detector, the near detector in the Fermilab Short-Baseline Neutrino Program.
Scalable, End-to-End, Deep-Learning-Based Data Reconstruction Chain for Particle Imaging Detectors
TLDR
This paper introduces an endto-end, ML-based data reconstruction chain for Liquid Argon Time Projection Chambers (LArTPCs), the state-of-the-art in precision imaging at the intensity frontier of neutrino physics.
Deep Underground Neutrino Experiment (DUNE), Far Detector Technical Design Report, Volume I: Introduction to DUNE
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 eventually decay -- these
REU REPORT-SUMMER 2019 Refining Reconstruction for the MicroBooNE Single Photon Search
  • 2019
This report details a study on a new cut which could be added to the section process NC∆ radiative decay events to improve measurement. MicroBooNE is an experiment at Fermilab National Accelerator
...
1
2
3
4
5
...

References

SHOWING 1-10 OF 10 REFERENCES
The Pandora software development kit for pattern recognition
TLDR
The implementation of the Pandora software development kit is described, which aids the process of designing, implementing and running pattern recognition algorithms, which addressing two pattern recognition problems in High Energy Physics.
The GENIE * Neutrino Monte Carlo Generator
Abstract GENIE [1] is a new neutrino event generator for the experimental neutrino physics community. The goal of the project is to develop a ‘canonical’ neutrino interaction physics Monte Carlo
Particle flow calorimetry and the PandoraPFA algorithm
Abstract The Particle Flow (PFlow) approach to calorimetry promises to deliver unprecedented jet energy resolution for experiments at future high energy colliders such as the proposed International
Performance of Particle Flow Calorimetry at CLIC
The particle flow approach to calorimetry can provide unprecedented jet energy resolution at a future high energy collider, such as the International Linear Collider (ILC). However, the use of
Precise 3D track reconstruction algorithm for the ICARUS T600 liquid argon time projection chamber detector
Liquid Argon Time Projection Chamber (LAr TPC) detectors offer charged particle imaging capability with remarkable spatial resolution. Precise event reconstruction procedures are critical in order to
Noise Characterization and Filtering in the MicroBooNE Liquid Argon TPC
The low-noise operation of readout electronics in a liquid argon time projection chamber (LArTPC) is critical to properly extract the distribution of ionization charge deposited on the wire planes of
The MiniBooNE Collaboration
MicroBooNE Collaboration], JINST
  • 2017
A . A . Aguilar - Arevalo et al . [ MiniBooNE Collaboration ]
  • Eur . Phys . J . C Methods A
  • 2009
FERMILAB - CONF - 17 - 052 - CD 14 . C . Andreopoulos et al . , Nucl . Instrum
  • Phys . Rev . D