Related papers: Scaling the training of particle classification on…

Convolutional Neural Networks Applied to Neutrino Events in a Liquid Argon Time Projection Chamber

We present several studies of convolutional neural networks applied to data coming from the MicroBooNE detector, a liquid argon time projection chamber (LArTPC). The algorithms studied include the classification of single particle images,…

Instrumentation and Detectors · Physics 2023-02-17 MicroBooNE collaboration , R. Acciarri , C. Adams , R. An , J. Asaadi , M. Auger , L. Bagby , B. Baller , G. Barr , M. Bass , F. Bay , M. Bishai , A. Blake , T. Bolton , L. Bugel , L. Camilleri , D. Caratelli , B. Carls , R. Castillo Fernandez , F. Cavanna , H. Chen , E. Church , D. Cianci , G. H. Collin , J. M. Conrad , M. Convery , J. I. Crespo-Anadón , M. Del Tutto , D. Devitt , S. Dytman , B. Eberly , A. Ereditato , L. Escudero Sanchez , J. Esquivel , B. T. Fleming , W. Foreman , A. P. Furmanski , G. T. Garvey , V. Genty , D. Goeldi , S. Gollapinni , N. Graf , E. Gramellini , H. Greenlee , R. Grosso , R. Guenette , A. Hackenburg , P. Hamilton , O. Hen , V Hewes , C. Hill , J. Ho , G. Horton-Smith , C. James , J. Jan de Vries , C. -M. Jen , L. Jiang , R. A. Johnson , B. J. P. Jones , J. Joshi , H. Jostlein , D. Kaleko , G. Karagiorgi , W. Ketchum , B. Kirby , M. Kirby , T. Kobilarcik , I. Kreslo , A. Laube , Y. Li , A. Lister , B. R. Littlejohn , S. Lockwitz , D. Lorca , W. C. Louis , M. Luethi , B. Lundberg , X. Luo , A. Marchionni , C. Mariani , J. Marshall , D. A. Martinez Caicedo , V. Meddage , T. Miceli , G. B. Mills , J. Moon , M. Mooney , C. D. Moore , J. Mousseau , R. Murrells , D. Naples , P. Nienaber , J. Nowak , O. Palamara , V. Paolone , V. Papavassiliou , S. F. Pate , Z. Pavlovic , D. Porzio , G. Pulliam , X. Qian , J. L. Raaf , A. Rafique , L. Rochester , C. Rudolf von Rohr , B. Russell , D. W. Schmitz , A. Schukraft , W. Seligman , M. H. Shaevitz , J. Sinclair , E. L. Snider , M. Soderberg , S. Söldner-Rembold , S. R. Soleti , P. Spentzouris , J. Spitz , J. St. John , T. Strauss , A. M. Szelc , N. Tagg , K. Terao , M. Thomson , M. Toups , Y. -T. Tsai , S. Tufanli , T. Usher , R. G. Van de Water , B. Viren , M. Weber , J. Weston , D. A. Wickremasinghe , S. Wolbers , T. Wongjirad , K. Woodruff , T. Yang , G. P. Zeller , J. Zennamo , C. Zhang

Automated proton track identification in MicroBooNE using gradient boosted decision trees

MicroBooNE is a liquid argon time projection chamber (LArTPC) neutrino experiment that is currently running in the Booster Neutrino Beam at Fermilab. LArTPC technology allows for high-resolution, three-dimensional representations of…

Instrumentation and Detectors · Physics 2017-10-04 Katherine Woodruff , the MicroBooNE Collaboration

A Deep Neural Network for Pixel-Level Electromagnetic Particle Identification in the MicroBooNE Liquid Argon Time Projection Chamber

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) for the first time. We describe the network design, training…

High Energy Physics - Experiment · Physics 2023-02-17 MicroBooNE collaboration , C. Adams , M. Alrashed , R. An , J. Anthony , J. Asaadi , A. Ashkenazi , M. Auger , S. Balasubramanian , B. Baller , C. Barnes , G. Barr , M. Bass , F. Bay , A. Bhat , K. Bhattacharya , M. Bishai , A. Blake , T. Bolton , L. Camilleri , D. Caratelli , I. Caro Terrazas , R. Carr , R. Castillo Fernandez , F. Cavanna , G. Cerati , Y. Chen , E. Church , D. Cianci , E. Cohen , G. H. Collin , J. M. Conrad , M. Convery , L. Cooper-Troendle , J. I. Crespo-Anadon , M. Del Tutto , D. Devitt , A. Diaz , K. Duffy , S. Dytman , B. Eberly , A. Ereditato , L. Escudero Sanchez , J. Esquivel , J. J. Evans , A. A. Fadeeva , R. S. Fitzpatrick , B. T. Fleming , D. Franco , A. P. Furmanski , D. Garcia-Gamez , G. T. Garvey , V. Genty , D. Goeldi , S. Gollapinni , O. Goodwin , E. Gramellini , H. Greenlee , R. Grosso , R. Guenette , P. Guzowski , A. Hackenburg , P. Hamilton , O. Hen , V Hewes , C. Hill , G. A. Horton-Smith , A. Hourlier , E. -C. Huang , C. James , J. Jan de Vries , L. Jiang , R. A. Johnson , J. Joshi , H. Jostlein , Y. -J. Jwa , G. Karagiorgi , W. Ketchum , B. Kirby , M. Kirby , T. Kobilarcik , I. Kreslo , Y. Li , A. Lister , B. R. Littlejohn , S. Lockwitz , D. Lorca , W. C. Louis , M. Luethi , B. Lundberg , X. Luo , A. Marchionni , S. Marcocci , C. Mariani , J. Marshall , J. Martin-Albo , D. A. Martinez Caicedo , A. Mastbaum , V. Meddage , T. Mettler , G. B. Mills , K. Mistry , A. Mogan , J. Moon , M. Mooney , C. D. Moore , J. Mousseau , M. Murphy , R. Murrells , D. Naples , P. Nienaber , J. Nowak , O. Palamara , V. Pandey , V. Paolone , A. Papadopoulou , V. Papavassiliou , S. F. Pate , Z. Pavlovic , E. Piasetzky , D. Porzio , G. Pulliam , X. Qian , J. L. Raaf , A. Rafique , L. Rochester , M. Ross-Lonergan , C. Rudolf von Rohr , B. Russell , D. W. Schmitz , A. Schukraft , W. Seligman , M. H. Shaevitz , R. Sharankova , J. Sinclair , A. Smith , E. L. Snider , M. Soderberg , S. Soldner-Rembold , S. R. Soleti , P. Spentzouris , J. Spitz , J. St. John , T. Strauss , K. Sutton , S. Sword-Fehlberg , A. M. Szelc , N. Tagg , W. Tang , K. Terao , M. Thomson , R. T. Thornton , M. Toups , Y. -T. Tsai , S. Tufanli , T. Usher , W. Van De Pontseele , R. G. Van de Water , B. Viren , M. Weber , H. Wei , D. A. Wickremasinghe , K. Wierman , Z. Williams , S. Wolbers , T. Wongjirad , K. Woodruff , T. Yang , G. Yarbrough , L. E. Yates , G. P. Zeller , J. Zennamo , C. Zhang

Evaluation of Portable Programming Models to Accelerate LArTPC Detector Simulations

The Liquid Argon Time Projection Chamber (LArTPC) technology is widely used in high energy physics experiments, including the upcoming Deep Underground Neutrino Experiment (DUNE). Accurately simulating LArTPC detector responses is essential…

Instrumentation and Detectors · Physics 2023-03-01 Zhihua Dong , Kyle Knoepfel , Meifeng Lin , Brett Viren , Haiwang Yu

LArTPC hit-based topology classification with quantum machine learning and symmetry

We present a new approach to separate track-like and shower-like topologies in liquid argon time projection chamber (LArTPC) experiments for neutrino physics using quantum machine learning. Effective reconstruction of neutrino events in…

Instrumentation and Detectors · Physics 2026-03-25 Callum Duffy , Marcin Jastrzebski , Stefano Vergani , Leigh H. Whitehead , Ryan Cross , Andrew Blake , Sarah Malik , John Marshall

Demonstration and performance of an online data selection algorithm for liquid argon time projection chambers using MicroBooNE

The MicroBooNE detector is a liquid argon time projection chamber (LArTPC) that produces three-dimensional images of particle interactions using ionization charge collected by anode wire plane arrays and scintillation light collected by a…

High Energy Physics - Experiment · Physics 2026-02-12 MicroBooNE collaboration , P. Abratenko , D. Andrade Aldana , L. Arellano , J. Asaadi , A. Ashkenazi , S. Balasubramanian , B. Baller , A. Barnard , G. Barr , D. Barrow , J. Barrow , V. Basque , J. Bateman , B. Behera , O. Benevides Rodrigues , S. Berkman , A. Bhat , M. Bhattacharya , V. Bhelande , A. Binau , M. Bishai , A. Blake , B. Bogart , T. Bolton , M. B. Brunetti , L. Camilleri , D. Caratelli , F. Cavanna , G. Cerati , A. Chappell , Y. Chen , J. M. Conrad , M. Convery , L. Cooper-Troendle , J. I. Crespo-Anadon , R. Cross , M. Del Tutto , S. R. Dennis , P. Detje , R. Diurba , Z. Djurcic , K. Duffy , S. Dytman , B. Eberly , P. Englezos , A. Ereditato , J. J. Evans , C. Fang , B. T. Fleming , W. Foreman , D. Franco , A. P. Furmanski , F. Gao , D. Garcia-Gamez , S. Gardiner , G. Ge , S. Gollapinni , E. Gramellini , P. Green , H. Greenlee , L. Gu , W. Gu , R. Guenette , P. Guzowski , L. Hagaman , M. D. Handley , O. Hen , A. Hergenhan , M. Harrison , S. Hawkins , C. Hilgenberg , G. A. Horton-Smith , A. Hussain , B. Irwin , M. S. Ismail , C. James , X. Ji , J. H. Jo , A. Johnson , R. A. Johnson , D. Kalra , G. Karagiorgi , W. Ketchum , A. Kelly , M. Kirby , T. Kobilarcik , K. Kumar , N. Lane , J. -Y. Li , Y. Li , K. Lin , B. R. Littlejohn , L. Liu , S. Liu , W. C. Louis , X. Luo , T. Mahmud , N. Majeed , C. Mariani , J. Marshall , N. Martinez , D. A. Martinez Caicedo , F. Martinez Lopez , M. G. Manuel Alves , S. Martynenko , A. Mastbaum , I. Mawby , N. McConkey , B. McConnell , L. Mellet , J. Mendez , J. Micallef , T. Mohayai , A. Mogan , M. Mooney , A. F. Moor , C. D. Moore , L. Mora Lepin , M. A. Hernandez Morquecho , M. M. Moudgalya , S. Mulleria Babu , D. Naples , A. Navrer-Agasson , N. Nayak , M. Nebot-Guinot , C. Nguyen , L. Nguyen , J. Nowak , N. Oza , O. Palamara , N. Pallat , V. Paolone , A. Papadopoulou , V. Papavassiliou , H. Parkinson , S. F. Pate , N. Patel , Z. Pavlovic , E. Piasetzky , K. Pletcher , I. Pophale , X. Qian , J. L. Raaf , V. Radeka , A. Rafique , M. Reggiani-Guzzo , J. Rodriguez Rondon , M. Rosenberg , M. Ross-Lonergan , I. Safa , D. W. Schmitz , A. Schukraft , W. Seligman , M. H. Shaevitz , R. Sharankova , J. Shi , L. Silva , E. L. Snider , S. Soldner-Rembold , J. Spitz , M. Stancari , J. St. John , T. Strauss , A. M. Szelc , N. Taniuchi , K. Terao , C. Thorpe , D. Torbunov , D. Totani , M. Toups , A. Trettin , Y. -T. Tsai , J. Tyler , M. A. Uchida , T. Usher , B. Viren , J. Wang , L. Wang , M. Weber , H. Wei , A. J. White , S. Wolbers , T. Wongjirad , K. Wresilo , W. Wu , E. Yandel , T. Yang , L. E. Yates , H. W. Yu , G. P. Zeller , J. Zennamo , C. Zhang , Y. Zhang

Accelerating Deep Neural Networks for Real-time Data Selection for High-resolution Imaging Particle Detectors

This paper presents the custom implementation, optimization, and performance evaluation of convolutional neural networks on field programmable gate arrays, for the purposes of accelerating deep neural network inference on large,…

Instrumentation and Detectors · Physics 2022-01-14 Yeon-Jae Jwa , Giuseppe Di Guglielmo , Luca P. Carloni , Georgia Karagiorgi

Reconstruction for Liquid Argon TPC Neutrino Detectors Using Parallel Architectures

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 becoming more difficult as the detectors increase in size to…

Instrumentation and Detectors · Physics 2021-02-03 Sophie Berkman , Giuseppe Cerati , Brian Gravelle , Boyana Norris , Allison Reinsvold Hall , Michael Wang

Recent results from MicroBooNE

Modelling and reconstructing neutrino-nucleus scattering is difficult, but it is crucial to do it precisely to enable next-generation oscillation measurements. Liquid argon time projection chambers (LArTPCs), such as MicroBooNE, can be the…

High Energy Physics - Experiment · Physics 2025-06-05 Holly B. Parkinson , for the MicroBooNE Collaboration

Scalable, Proposal-free Instance Segmentation Network for 3D Pixel Clustering and Particle Trajectory Reconstruction in Liquid Argon Time Projection Chambers

Liquid Argon Time Projection Chambers (LArTPCs) are high resolution particle imaging detectors, employed by accelerator-based neutrino oscillation experiments for high precision physics measurements. While images of particle trajectories…

Instrumentation and Detectors · Physics 2020-07-08 Dae Heun Koh , Pierre Côte de Soux , Laura Dominé , François Drielsma , Ran Itay , Qing Lin , Kazuhiro Terao , Ka Vang Tsang , Tracy Usher

Scalable, End-to-End, Deep-Learning-Based Data Reconstruction Chain for Particle Imaging Detectors

Recent inroads in Computer Vision (CV) and Machine Learning (ML) have motivated a new approach to the analysis of particle imaging detector data. Unlike previous efforts which tackled isolated CV tasks, this paper introduces an end-to-end,…

High Energy Physics - Experiment · Physics 2021-02-02 Francois Drielsma , Kazuhiro Terao , Laura Dominé , Dae Heun Koh

Augmented Signal Processing in Liquid Argon Time Projection Chambers with a Deep Neural Network

The Liquid Argon Time Projection Chamber (LArTPC) is an advanced neutrino detector technology widely used in recent and upcoming accelerator neutrino experiments. It features a low energy threshold and high spatial resolution that allow for…

Instrumentation and Detectors · Physics 2021-03-24 Haiwang Yu , Mary Bishai , Wenqiang Gu , Meifeng Lin , Xin Qian , Yihui Ren , Andrea Scarpelli , Brett Viren , Hanyu Wei , Hongzhao Yu , Kwang Min Yu , Chao Zhang

Calorimetric classification of track-like signatures in liquid argon TPCs using MicroBooNE data

The MicroBooNE liquid argon time projection chamber located at Fermilab is a neutrino experiment dedicated to the study of short-baseline oscillations, the measurements of neutrino cross sections in liquid argon, and to the research and…

Instrumentation and Detectors · Physics 2022-01-05 MicroBooNE collaboration , P. Abratenko , R. An , J. Anthony , J. Asaadi , A. Ashkenazi , S. Balasubramanian , B. Baller , C. Barnes , G. Barr , V. Basque , L. Bathe-Peters , O. Benevides Rodrigues , S. Berkman , A. Bhanderi , A. Bhat , M. Bishai , A. Blake , T. Bolton , L. Camilleri , D. Caratelli , I. Caro Terrazas , R. Castillo Fernandez , F. Cavanna , G. Cerati , Y. Chen , E. Church , D. Cianci , J. M. Conrad , M. Convery , L. Cooper-Troendle , J. I. Crespo-Anadon , M. Del Tutto , S. R. Dennis , D. Devitt , R. Diurba , R. Dorrill , K. Duffy , S. Dytman , B. Eberly , A. Ereditato , J. J. Evans , R. Fine , G. A. Fiorentini Aguirre , R. S. Fitzpatrick , B. T. Fleming , N. Foppiani , D. Franco , A. P. Furmanski , D. Garcia-Gamez , S. Gardiner , G. Ge , S. Gollapinni , O. Goodwin , E. Gramellini , P. Green , H. Greenlee , W. Gu , R. Guenette , P. Guzowski , L. Hagaman , E. Hall , P. Hamilton , O. Hen , G. A. Horton-Smith , A. Hourlier , R. Itay , C. James , X. Ji , L. Jiang , J. H. Jo , R. A. Johnson , Y. J. Jwa , N. Kamp , N. Kaneshige , G. Karagiorgi , W. Ketchum , M. Kirby , T. Kobilarcik , I. Kreslo , R. LaZur , I. Lepetic , K. Li , Y. Li , K. Lin , B. R. Littlejohn , W. C. Louis , X. Luo , K. Manivannan , C. Mariani , D. Marsden , J. Marshall , D. A. Martinez Caicedo , K. Mason , A. Mastbaum , N. McConkey , V. Meddage , T. Mettler , K. Miller , J. Mills , K. Mistry , T. Mohayai , A. Mogan , J. Moon , M. Mooney , A. F. Moor , C. D. Moore , L. Mora Lepin , J. Mousseau , M. Murphy , D. Naples , A. Navrer-Agasson , R. K. Neely , J. Nowak , M. Nunes , O. Palamara , V. Paolone , A. Papadopoulou , V. Papavassiliou , S. F. Pate , A. Paudel , Z. Pavlovic , E. Piasetzky , I. Ponce-Pinto , S. Prince , X. Qian , J. L. Raaf , V. Radeka , A. Rafique , M. Reggiani-Guzzo , L. Ren , L. C. J. Rice , L. Rochester , J. Rodriguez Rondon , H. E. Rogers , M. Rosenberg , M. Ross-Lonergan , G. Scanavini , D. W. Schmitz , A. Schukraft , W. Seligman , M. H. Shaevitz , R. Sharankova , J. Sinclair , A. Smith , E. L. Snider , M. Soderberg , S. Soldner-Rembold , P. Spentzouris , J. Spitz , M. Stancari , J. St. John , T. Strauss , K. Sutton , S. Sword-Fehlberg , A. M. Szelc , N. Tagg , W. Tang , K. Terao , C. Thorpe , D. Totani , M. Toups , Y. -T. Tsai , M. A. Uchida , T. Usher , W. Van De Pontseele , B. Viren , M. Weber , H. Wei , Z. Williams , S. Wolbers , T. Wongjirad , M. Wospakrik , N. Wright , W. Wu , E. Yandel , T. Yang , G. Yarbrough , L. E. Yates , G. P. Zeller , J. Zennamo , C. Zhang

Optimizing the Hit Finding Algorithm for Liquid Argon TPC Neutrino Detectors Using Parallel Architectures

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 becoming even more difficult as the detectors increase in size…

Instrumentation and Detectors · Physics 2022-02-02 Sophie Berkman , Giuseppe Cerati , Kyle Knoepfel , Marc Mengel , Allison Reinsvold Hall , Michael Wang , Brian Gravelle , Boyana Norris

Towards Designing Scalable Quantum-Enhanced Generative Networks for Neutrino Physics Experiments with Liquid Argon Time Projection Chambers

Generative modeling for high-resolution images in Liquid Argon Time Projection Chambers (LArTPC), used in neutrino physics experiments, presents significant challenges due to the complexity and sparsity of the data. This work explores the…

Quantum Physics · Physics 2024-10-17 Andrea Delgado , Diego Venegas-Vargas , Adam Huynh , Kevon Carroll

Improving neutrino energy estimation of charged-current interaction events with recurrent neural networks in MicroBooNE

We present a deep learning-based method for estimating the neutrino energy of charged-current neutrino-argon interactions. We employ a recurrent neural network (RNN) architecture for neutrino energy estimation in the MicroBooNE experiment,…

High Energy Physics - Experiment · Physics 2024-06-17 MicroBooNE collaboration , P. Abratenko , O. Alterkait , D. Andrade Aldana , L. Arellano , J. Asaadi , A. Ashkenazi , S. Balasubramanian , B. Baller , A. Barnard , G. Barr , D. Barrow , J. Barrow , V. Basque , J. Bateman , O. Benevides Rodrigues , S. Berkman , A. Bhanderi , A. Bhat , M. Bhattacharya , M. Bishai , A. Blake , B. Bogart , T. Bolton , J. Y. Book , M. B. Brunetti , L. Camilleri , Y. Cao , D. Caratelli , F. Cavanna , G. Cerati , A. Chappell , Y. Chen , J. M. Conrad , M. Convery , L. Cooper-Troendle , J. I. Crespo-Anadon , R. Cross , M. Del Tutto , S. R. Dennis , P. Detje , R. Diurba , Z. Djurcic , R. Dorrill , K. Duffy , S. Dytman , B. Eberly , P. Englezos , A. Ereditato , J. J. Evans , R. Fine , B. T. Fleming , W. Foreman , D. Franco , A. P. Furmanski , F. Gao , D. Garcia-Gamez , S. Gardiner , G. Ge , S. Gollapinni , E. Gramellini , P. Green , H. Greenlee , L. Gu , W. Gu , R. Guenette , P. Guzowski , L. Hagaman , O. Hen , C. Hilgenberg , G. A. Horton-Smith , Z. Imani , B. Irwin , M. S. Ismail , C. James , X. Ji , J. H. Jo , R. A. Johnson , Y. J. Jwa , D. Kalra , N. Kamp , G. Karagiorgi , W. Ketchum , M. Kirby , T. Kobilarcik , I. Kreslo , N. Lane , I. Lepetic , J. -Y. Li , Y. Li , K. Lin , B. R. Littlejohn , H. Liu , W. C. Louis , X. Luo , C. Mariani , D. Marsden , J. Marshall , N. Martinez , D. A. Martinez Caicedo , S. Martynenko , A. Mastbaum , I. Mawby , N. McConkey , V. Meddage , J. Mendez , J. Micallef , K. Miller , K. Mistry , T. Mohayai , A. Mogan , M. Mooney , A. F. Moor , C. D. Moore , L. Mora Lepin , M. M. Moudgalya , S. Mulleria Babu , D. Naples , A. Navrer-Agasson , N. Nayak , M. Nebot-Guinot , J. Nowak , N. Oza , O. Palamara , N. Pallat , V. Paolone , A. Papadopoulou , V. Papavassiliou , H. Parkinson , S. F. Pate , N. Patel , Z. Pavlovic , E. Piasetzky , K. Pletcher , I. Pophale , X. Qian , J. L. Raaf , V. Radeka , A. Rafique , M. Reggiani-Guzzo , L. Ren , L. Rochester , J. Rodriguez Rondon , M. Rosenberg , M. Ross-Lonergan , I. Safa , G. Scanavini , D. W. Schmitz , A. Schukraft , W. Seligman , M. H. Shaevitz , R. Sharankova , J. Shi , E. L. Snider , M. Soderberg , S. Soldner-Rembold , J. Spitz , M. Stancari , J. St. John , T. Strauss , A. M. Szelc , W. Tang , N. Taniuchi , K. Terao , C. Thorpe , D. Torbunov , D. Totani , M. Toups , A. Trettin , Y. -T. Tsai , J. Tyler , M. A. Uchida , T. Usher , B. Viren , M. Weber , H. Wei , A. J. White , S. Wolbers , T. Wongjirad , M. Wospakrik , K. Wresilo , W. Wu , E. Yandel , T. Yang , L. E. Yates , H. W. Yu , G. P. Zeller , J. Zennamo , C. Zhang

Graph Neural Network for Neutrino Physics Event Reconstruction

Liquid Argon Time Projection Chamber (LArTPC) detector technology offers a wealth of high-resolution information on particle interactions, and leveraging that information to its full potential requires sophisticated automated reconstruction…

Data Analysis, Statistics and Probability · Physics 2025-06-27 V Hewes , Adam Aurisano , Giuseppe Cerati , Jim Kowalkowski , Claire Lee , Wei-keng Liao , Daniel Grzenda , Kaushal Gumpula , Xiaohe Zhang

DNN-based Signal Processing for Liquid Argon Time Projection Chambers

We investigate a deep learning-based signal processing for liquid argon time projection chambers (LArTPCs), a leading detector technology in neutrino physics. Identifying regions of interest (ROIs) in LArTPCs is challenging due to signal…

Instrumentation and Detectors · Physics 2025-10-30 Avinay Bhat , Mun Jung Jung , Gray Putnam , Haiwang Yu

Energy reconstruction and calibration techniques of the DUNE LArTPC

The Liquid Argon Time Projection Chamber (LArTPC) technology is currently a preferred choice for neutrino experiments and beyond the standard model physics searches such as nucleon decay and dark matter. The Deep Underground Neutrino…

High Energy Physics - Experiment · Physics 2025-01-03 Praveen Kumar

Large-Scale Deep Learning for Multi-Jet Event Classification

We report the largest scale deep learning with High Performance Computing (HPC) to physics analysis with the CMS simulation data in proton-proton collisions at 13 TeV. We build a Convolutional Neural Network (CNN) model that takes low-level…

High Energy Physics - Experiment · Physics 2023-06-01 Jiwoong Kim , Dongsung Bae , Kihyeon Cho , Junghwan Goh , Jaegyoon Hahm , Taeyoung Hong , Soonwook Hwang , Minsik Kim , Sungwon Kim , Tongil Kim , Chang-Seong Moon , Hunjoo Myung , Hokyeong Nam , Changhyun Yoo , Hwidong Yoo