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To be able to achieve their physics goals, future neutrino-oscillation experiments will need to reconstruct the neutrino energy with very high accuracy. In this work, we analyze how the energy reconstruction may be affected by realistic…

High Energy Physics - Phenomenology · Physics 2015-10-23 Artur M. Ankowski , Omar Benhar , Pilar Coloma , Patrick Huber , Chun-Min Jen , Camillo Mariani , Davide Meloni , Erica Vagnoni

At the High Luminosity Large Hadron Collider (HL-LHC), traditional track reconstruction techniques that are critical for analysis are expected to face challenges due to scaling with track density. Quantum annealing has shown promise in its…

Fast 4$\pi$ solid angle particle track recognition has been a challenge in particle physics for a long time, especially in using nuclear emulsion detectors. The recent advances in computing technology opened the way for its realization. A…

Instrumentation and Detectors · Physics 2015-06-18 A. Ariga , T. Ariga

This paper presents a novel method for the reconstruction of interaction vertices in particle collision data. The algorithm is an agglomerative clustering technique designed for high-luminosity environments in current and future…

Instrumentation and Detectors · Physics 2017-05-02 Federico Meloni

We present a potential improvement over the standard method developed to determine antineutrino directionality in inverse-beta-decay detectors. The previously developed method for quantifying directionality in monolithic and segmented…

We previously developed an automatic track scanning system which enables the detection of large-angle nuclear fragments in the nuclear emulsion films of the OPERA experiment. As a next step, we have investigated this system's track…

Instrumentation and Detectors · Physics 2015-06-23 T. Fukuda , S. Fukunaga , H. Ishida , T. Matsumoto , T. Matsuo , S. Mikado , S. Nishimura , S. Ogawa , H. Shibuya , J. Sudou , A. Ariga , S. Tufanli

Most of existing detection pipelines treat object proposals independently and predict bounding box locations and classification scores over them separately. However, the important semantic and spatial layout correlations among proposals are…

Computer Vision and Pattern Recognition · Computer Science 2016-08-19 Jianan Li , Xiaodan Liang , Jianshu Li , Tingfa Xu , Jiashi Feng , Shuicheng Yan

Tensor-valued data arise naturally in multidimensional signal and imaging problems, such as biomedical imaging. When incorporated into generalized linear models (GLMs), naive vectorization can destroy their multi-way structure and lead to…

Machine Learning · Statistics 2026-04-07 Xiao Liang , Shuang Li

The performance demands of future particle-physics experiments investigating the high-energy frontier pose a number of new challenges, forcing us to find improved solutions for the detection, identification, and measurement of final-state…

Instrumentation and Detectors · Physics 2022-03-31 Jan Kieseler , Giles C. Strong , Filippo Chiandotto , Tommaso Dorigo , Lukas Layer

For over a decade now, physical and energy constraints have limited clock speed improvements in commodity microprocessors. Instead, chipmakers have been pushed into producing lower-power, multi-core processors such as GPGPU, ARM and Intel…

We present results from parallelizing the unpacking and clustering steps of the raw data from the silicon strip modules for reconstruction of charged particle tracks. Throughput is further improved by concurrently processing multiple events…

This report reviews methods of pattern recognition and event reconstruction used in modern high energy physics experiments. After a brief introduction into general concepts of particle detectors and statistical evaluation, different…

Data Analysis, Statistics and Probability · Physics 2009-11-10 Rainer Mankel

Charged particle reconstruction is one the most computationally heavy components of the full event reconstruction of Large Hadron Collider (LHC) experiments. Looking to the future, projections for the High Luminosity LHC (HL-LHC) indicate a…

Safety-critical infrastructures, such as bridges, are periodically inspected to check for existing damage, such as fatigue cracks and corrosion, and to guarantee the safe use of the infrastructure. Visual inspection is the most frequent…

Computer Vision and Pattern Recognition · Computer Science 2024-03-29 Andrii Kompanets , Remco Duits , Davide Leonetti , Nicky van den Berg , H. H. , Snijder

In this work, we develop a novel technique for reconstructing images from projection-based nano- and microtomography. Our contribution focuses on enhancing reconstruction quality, particularly for specimen composed of homogeneous material…

Computer Vision and Pattern Recognition · Computer Science 2025-09-09 Anuraag Mishra , Andrea Gilch , Benjamin Apeleo Zubiri , Jan Rolfes , Frauke Liers

Restoring images affected by various types of degradation, such as noise, blur, or improper exposure, remains a significant challenge in computer vision. While recent trends favor complex monolithic all-in-one architectures, these models…

Computer Vision and Pattern Recognition · Computer Science 2026-03-31 Joanna Wiekiera , Martyna Zur

While supervised object detection methods achieve impressive accuracy, they generalize poorly to images whose appearance significantly differs from the data they have been trained on. To address this in scenarios where annotating data is…

Computer Vision and Pattern Recognition · Computer Science 2019-07-19 Isinsu Katircioglu , Helge Rhodin , Victor Constantin , Jörg Spörri , Mathieu Salzmann , Pascal Fua

Multi-Object Tracking (MOT) has gained extensive attention in recent years due to its potential applications in traffic and pedestrian detection. We note that tracking by detection may suffer from errors generated by noise detectors, such…

Computer Vision and Pattern Recognition · Computer Science 2023-03-14 ZongTan Li

This paper presents the reconstruction and performance evaluation of the FASER$\nu$ emulsion detector, which aims to measure interactions from neutrinos produced in the forward direction of proton-proton collisions at the CERN Large Hadron…

Instrumentation and Detectors · Physics 2025-05-05 FASER Collaboration , Roshan Mammen Abraham , Xiaocong Ai , Saul Alonso Monsalve , John Anders , Claire Antel , Akitaka Ariga , Tomoko Ariga , Jeremy Atkinson , Florian U. Bernlochner , Tobias Boeckh , Jamie Boyd , Lydia Brenner , Angela Burger , Franck Cadou , Roberto Cardella , David W. Casper , Charlotte Cavanagh , Xin Chen , Kohei Chinone , Dhruv Chouhan , Andrea Coccaro , Stephane Débieu , Ansh Desai , Sergey Dmitrievsky , Radu Dobre , Monica D'Onofrio , Sinead Eley , Yannick Favre , Deion Fellers , Jonathan L. Feng , Carlo Alberto Fenoglio , Didier Ferrere , Max Fieg , Wissal Filali , Elena Firu , Haruhi Fujimori , Edward Galantay , Ali Garabaglu , Stephen Gibson , Sergio Gonzalez-Sevilla , Yuri Gornushkin , Carl Gwilliam , Daiki Hayakawa , Michael Holzbock , Shih-Chieh Hsu , Zhen Hu , Giuseppe Iacobucci , Tomohiro Inada , Luca Iodice , Sune Jakobsen , Hans Joos , Enrique Kajomovitz , Takumi Kanai , Hiroaki Kawahara , Alex Keyken , Felix Kling , Daniela Köck , Pantelis Kontaxakis , Umut Kose , Rafaella Kotitsa , Peter Krack , Susanne Kuehn , Thanushan Kugathasan , Lorne Levinson , Botao Li , Jinfeng Liu , Yi Liu , Margaret S. Lutz , Jack MacDonald , Chiara Magliocca , Toni Mäkelä , Lawson McCoy , Josh McFayden , Andrea Pizarro Medina , Matteo Milanesio , Théo Moretti , Keiko Moriyama , Mitsuhiro Nakamura , Toshiyuki Nakano , Laurie Nevay , Motoya Nonaka , Yuma Ohara , Ken Ohashi , Kazuaki Okui , Hidetoshi Otono , Hao Pang , Lorenzo Paolozzi , Pawan Pawan , Brian Petersen , Titi Preda , Markus Prim , Michaela Queitsch-Maitland , Juan Rojo , Hiroki Rokujo , André Rubbia , Jorge Sabater-Iglesias , Osamu Sato , Paola Scampoli , Kristof Schmieden , Matthias Schott , Christiano Sebastiani , Anna Sfyrla , Davide Sgalaberna , Mansoora Shamim , Savannah Shively , Yosuke Takubo , Noshin Tarannum , Ondrej Theiner , Simon Thor , Eric Torrence , Oscar Ivan Valdes Martinez , Svetlana Vasina , Benedikt Vormwald , Yuxiao Wang , Eli Welch , Monika Wielers , Benjamin James Wilson , Jialin Wu , Johannes Martin Wuthrich , Yue Xu , Stefano Zambito , Shunliang Zhang , Xingyu Zhao

This work presents a generalized muon trajectory estimation (GMTE) algorithm to estimate the path of a muon in either uniform or nonuniform media. The use of cosmic ray muons in nuclear nonproliferation and safeguards verification…

Computational Physics · Physics 2018-04-18 Stylianos Chatzidakis , Zhengzhi Liu , Jason P. Hayward , John M. Scaglione