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Related papers: A Common Tracking Software Project

200 papers

To support the variety of Big Data use cases, many Big Data related systems expose a large number of user-specifiable configuration parameters. Highlighted in our experiments, a MySQL deployment with well-tuned configuration parameters…

Distributed, Parallel, and Cluster Computing · Computer Science 2017-08-09 Yuqing Zhu , Jianxun Liu , Mengying Guo , Wenlong Ma , Yungang Bao

For decades, track association has been a challenging problem in marine surveillance, which involves the identification and association of vessel observations over time. However, the Automatic Identification System (AIS) has provided a new…

Machine Learning · Computer Science 2023-04-05 Md Asif Bin Syed , Imtiaz Ahmed

We present the design and performance analysis of a new integrated track reconstruction code developed for the STAR experiment at RHIC. The code is meant to replace multiple previous tracking codes written in FORTRAN many years ago, and to…

Nuclear Experiment · Physics 2007-05-23 A. Rose

The physics goals of the next Large Hadron Collider run include high precision tests of the Standard Model and searches for new physics. These goals require detailed comparison of data with computational models simulating the expected data…

Distributed, Parallel, and Cluster Computing · Computer Science 2019-08-14 Mikhail Borodin , Kaushik De , Jose Garcia Navarro , Dmitry Golubkov , Alexei Klimentov , Tadashi Maeno , David South , Alexandre Vaniachine

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

This paper introduces AutoGCN, a generic Neural Architecture Search (NAS) algorithm for Human Activity Recognition (HAR) using Graph Convolution Networks (GCNs). HAR has gained attention due to advances in deep learning, increased data…

Computer Vision and Pattern Recognition · Computer Science 2024-03-13 Felix Tempel , Inga Strümke , Espen Alexander F. Ihlen

The use of deep learning techniques in detecting anomalies in time series data has been an active area of research with a long history of development and a variety of approaches. In particular, reconstruction-based unsupervised anomaly…

Artificial Intelligence · Computer Science 2023-02-21 Jinsheng Yang , Yuanhai Shao , ChunNa Li

Traffic Atomic Activity which describes traffic patterns for topological intersection dynamics is a crucial topic for the advancement of intelligent driving systems. However, existing atomic activity datasets are collected from an…

Computer Vision and Pattern Recognition · Computer Science 2025-03-25 Zihao Chen , Hsuanyu Wu , Chi-Hsi Kung , Yi-Ting Chen , Yan-Tsung Peng

The main challenge of Multi-Object Tracking~(MOT) lies in maintaining a continuous trajectory for each target. Existing methods often learn reliable motion patterns to match the same target between adjacent frames and discriminative…

Computer Vision and Pattern Recognition · Computer Science 2023-04-18 Zheng Qin , Sanping Zhou , Le Wang , Jinghai Duan , Gang Hua , Wei Tang

The LUXE experiment is a new experiment in planning in Hamburg, which will study Quantum Electrodynamics at the strong-field frontier. LUXE intends to measure the positron production rate in this unprecedented regime by using, among others,…

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

Reconstructing the trajectories of charged particles in high-energy collisions requires high precision to ensure reliable event reconstruction and accurate downstream physics analyses. In particular, both precise hit selection and…

High Energy Physics - Experiment · Physics 2026-04-27 Andrea Coccaro , Francesco Armando Di Bello , Lucrezia Rambelli , Stefano Rosati , Carlo Schiavi

Sensors in cyber-physical systems often capture interconnected processes and thus emit correlated time series (CTS), the forecasting of which enables important applications. The key to successful CTS forecasting is to uncover the temporal…

Machine Learning · Computer Science 2023-02-28 Xinle Wu , Dalin Zhang , Miao Zhang , Chenjuan Guo , Bin Yang , Christian S. Jensen

The process of association and tracking of sensor detections is a key element in providing situational awareness. When the targets in the scenario are dense and exhibit high maneuverability, Multi-Target Tracking (MTT) becomes a challenging…

Machine Learning · Computer Science 2020-11-20 Rishabh Verma , R Rajesh , MS Easwaran

As unmanned aircraft systems (UASs) continue to integrate into the U.S. National Airspace System (NAS), there is a need to quantify the risk of airborne collisions between unmanned and manned aircraft to support regulation and standards…

Distributed, Parallel, and Cluster Computing · Computer Science 2021-10-26 Andrew Weinert , Marc Brittain , Ngaire Underhill , Christine Serres

mkFit is an implementation of the Kalman filter-based track reconstruction algorithm that exploits both thread- and data-level parallelism. In the past few years the project transitioned from the R&D phase to deployment in the Run-3 offline…

Network simulators play a crucial role in evaluating the performance of large-scale systems. However, existing simulators rely heavily on synthetic microbenchmarks or narrowly focus on specific domains, limiting their ability to provide…

Distributed, Parallel, and Cluster Computing · Computer Science 2025-05-15 Siyuan Shen , Tommaso Bonato , Zhiyi Hu , Pasquale Jordan , Tiancheng Chen , Torsten Hoefler

A track finding algorithm has been developed for reconstruction of e+e- pairs. It combines the information of the electromagnetic calorimeter with the information provided by the Tracker. Results on reconstruction efficiency of converted…

Data Analysis, Statistics and Probability · Physics 2017-08-23 Nancy Marinelli

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

The ATLAS experiment at the Large Hadron Collider has a broad physics programme ranging from precision measurements to direct searches for new particles and new interactions, requiring ever larger and ever more accurate datasets of…

High Energy Physics - Experiment · Physics 2024-11-25 ATLAS Collaboration