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Related papers: Charged Particle Tracking in Real-Time Using a Ful…

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We present a measurement of the charged particle reconstruction inefficiency inside of jet cores, using data collected by the ATLAS experiment in 2015 of $pp$ collisions produced at the LHC, at a center-of-mass energy of 13 TeV. The…

High Energy Physics - Experiment · Physics 2017-01-04 Jason D. Mansour

Particle track reconstruction is traditionally computationally challenging due to the combinatorial nature of the tracking algorithms employed. Recent developments have focused on novel algorithms with graph neural networks (GNNs), which…

Data Analysis, Statistics and Probability · Physics 2025-06-05 Jay Chan , Brandon Wang , Paolo Calafiura

The combinatorics of track seeding has long been a computational bottleneck for triggering and offline computing in High Energy Physics (HEP), and remains so for the HL-LHC. Next-generation pixel sensors will be sufficiently fine-grained to…

Magnetic Particle Imaging is an emerging imaging modality through which it is possible to detect tracers containing superparamagnetic nanoparticles. The exposure of the particles to dynamic magnetic fields generates a non-linear response…

Numerical Analysis · Mathematics 2024-06-19 Vladyslav Gapyak , Thomas März , Andreas Weinmann

Methods to extract information from the tracking of mobile objects/particles have broad interest in biological and physical sciences. Techniques based on simple criteria of proximity in time-consecutive snapshots are useful to identify the…

Data Analysis, Statistics and Probability · Physics 2015-03-13 M. Chertkov , L. Kroc , F. Krzakala , M. Vergassola , L. Zdeborová

Reconstruction of displaced vertices is a cornerstone of both precision flavour physics and searches for long-lived particles (LLPs) at colliders. While existing vertexing algorithms are highly optimised for primary and short-lived…

High Energy Physics - Phenomenology · Physics 2025-10-02 Jonathan Kriewald

Traffic forecasting is a challenging problem due to complex road networks and sudden speed changes caused by various events on roads. A number of models have been proposed to solve this challenging problem with a focus on learning…

Machine Learning · Computer Science 2022-03-09 Hyunwook Lee , Seungmin Jin , Hyeshin Chu , Hongkyu Lim , Sungahn Ko

Tracking calculations of charged particles in electromagnetic fields require in principle the simultaneous solution of the equation of motion and of Maxwell's equations. In many tracking codes a simpler and more efficient approach is used:…

Accelerator Physics · Physics 2012-01-26 M. Dohlus , K. Flottmann , C. Henning

Charged particle transport is an important energy transport mode in the combustion process of inertial confinement fusion plasma. On the one hand, charged particles inside the hot spot have a strong non-equilibrium effect, so it is…

Plasma Physics · Physics 2023-09-26 Chang Liu , Bao Du , Peng Song

Real-time data filtering and selection -- or trigger -- systems at high-throughput scientific facilities such as the experiments at the Large Hadron Collider (LHC) must process extremely high-rate data streams under stringent bandwidth,…

This paper presents an investigation of the use of interest point detection algorithms from image processing applied to reconstruction of interactions in high granularity tracking detectors. Their purpose is to extract keypoints from the…

Instrumentation and Detectors · Physics 2014-11-21 Ben Morgan

We present a new particle tracking algorithm to accurately resolve large deformation and rotational motion fields, which takes advantage of both local and global particle tracking algorithms. We call this method the ScalE and Rotation…

Particle filters flexibly represent multiple posterior modes nonparametrically, via a collection of weighted samples, but have classically been applied to tracking problems with known dynamics and observation likelihoods. Such generative…

Machine Learning · Computer Science 2024-04-16 Ali Younis , Erik Sudderth

Detector simulation and reconstruction are a significant computational bottleneck in particle physics. We develop Particle-flow Neural Assisted Simulations (Parnassus) to address this challenge. Our deep learning model takes as input a…

Data Analysis, Statistics and Probability · Physics 2024-11-22 Etienne Dreyer , Eilam Gross , Dmitrii Kobylianskii , Vinicius Mikuni , Benjamin Nachman , Nathalie Soybelman

We describe a novel approach to statistical learning from particles tracked while moving in a random environment. The problem consists in inferring properties of the environment from recorded snapshots. We consider here the case of a fluid…

Information Theory · Computer Science 2008-06-09 Michael Chertkov , Lukas Kroc , Massimo Vergassola

Phenomenological proposals of searches for new, long-lived particles face a challenge when estimating the reconstruction efficiency of displaced charged-particle tracks. The efficiency depends not only on the charged-particle's momentum…

High Energy Physics - Experiment · Physics 2025-01-03 Emilie Bertholet , Abner Soffer

A particle flow event-reconstruction algorithm has been successfully deployed in the CMS experiment and is nowadays used by most of the analyses. It aims at identifying and reconstructing individually each particle arising from the LHC…

High Energy Physics - Experiment · Physics 2014-02-03 Florian Beaudette

Charged particle track reconstruction in silicon detectors of collider experiments in high-multiplicity events, such as heavy-ion collisions at LHC, is a difficult and resource-demanding process. The first phase of the procedure is the…

High Energy Physics - Experiment · Physics 2025-09-03 Petr Balek , Tomasz Bold , Michal Naworyta

This report presents recent results on track reconstruction and alignment with the silicon tracker of the CMS experiment at the LHC, obtained with a full detector simulation. After an overview of the layout of the tracker and its material…

Instrumentation and Detectors · Physics 2007-05-23 F. -P. Schilling

We present the study of an end-to-end multi-track reconstruction algorithm for the central drift chamber of the Belle II experiment at the SuperKEKB collider using Graph Neural Networks for an unknown number of particles. The algorithm uses…

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