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Nowadays, scientific databases have become the bread-and-butter of particle physicists. These databases must be maintained and checked repeatedly to insure the accuracy of their content. The COMPETE collaboration aims at motivating data…

High-energy physics experiments face extreme data rates, requiring real-time trigger systems to reduce event throughput while preserving sensitivity to rare processes. Trigger systems are typically constructed as modular chains of…

High Energy Physics - Experiment · Physics 2026-03-10 Noah Clarke Hall , Ioannis Xiotidis , Nikos Konstantinidis , David W. Miller

One of the biggest challenges in the High-Luminosity LHC (HL- LHC) era will be the significantly increased data size to be recorded and analyzed from the collisions at the ATLAS and CMS experiments. ServiceX is a software R&D project in the…

The simulation of the ATLAS detector is a major challenge, given the complexity of the detector and the demanding environment of the LHC. The apparatus, one of the biggest and most complex ever designed, requires a detailed, flexible and,…

Data Analysis, Statistics and Probability · Physics 2007-05-23 A. Rimoldi , A. Dell'Acqua

Many organizations routinely analyze large datasets using systems for distributed data-parallel processing and clusters of commodity resources. Yet, users need to configure adequate resources for their data processing jobs. This requires…

Distributed, Parallel, and Cluster Computing · Computer Science 2022-06-02 Lauritz Thamsen , Dominik Scheinert , Jonathan Will , Jonathan Bader , Odej Kao

The trigger selection capabilities of the ATLAS detector have been significantly enhanced for the LHC Run- 2 in order to cope with the higher event rates and with the large number of simultaneous interactions (pile-up) per protonproton…

High Energy Physics - Experiment · Physics 2020-09-18 Pierre-Hugues Beauchemin

We demonstrate CEDAR, an application for automating data science (DS) tasks with an agentic setup. Solving DS problems with LLMs is an underexplored area that has immense market value. The challenges are manifold: task complexities, data…

Machine Learning · Computer Science 2026-04-23 Rishiraj Saha Roy , Chris Hinze , Luzian Hahn , Fabian Kuech

In today's Web and social network environments, query workloads include ad hoc and OLAP queries, as well as iterative algorithms that analyze data relationships (e.g., link analysis, clustering, learning). Modern DBMSs support ad hoc and…

Databases · Computer Science 2012-08-02 Svilen R. Mihaylov , Zachary G. Ives , Sudipto Guha

The vast majority of scientific contributions in the field of computational systems biology are based on mathematical models. These models can be broadly classified as either dynamic (kinetic) models or steady-state (constraint-based)…

Other Quantitative Biology · Quantitative Biology 2025-04-17 Moritz E. Beber

The data volumes stored in telescope archives is constantly increasing due to the development and improvements in the instrumentation. Often the archives need to be stored over a distributed storage architecture, provided by independent…

Instrumentation and Methods for Astrophysics · Physics 2022-02-07 Y. G. Grange , V. N. Pandey , X. Espinal , R. Di Maria , A. P. Millar

A novel model of the data selection, acquisition and analysis for a multi-purpose and multi-component high-energy-physics experiment is presented. Its departure point is the freedom and the responsibility given to the different physics…

High Energy Physics - Experiment · Physics 2008-12-19 Mieczyslaw Witold Krasny

Classification of high-dimensional low sample size (HDLSS) data poses a challenge in a variety of real-world situations, such as gene expression studies, cancer research, and medical imaging. This article presents the development and…

Machine Learning · Statistics 2026-05-27 Jyotishka Ray Choudhury , Aytijhya Saha , Sarbojit Roy , Subhajit Dutta

HRDBMS is a novel distributed relational database that uses a hybrid model combining the best of traditional distributed relational databases and Big Data analytics platforms such as Hive. This allows HRDBMS to leverage years worth of…

Databases · Computer Science 2019-01-28 Jason Arnold , Boris Glavic , Ioan Raicu

The HEP community is approaching an era were the excellent performances of the particle accelerators in delivering collision at high rate will force the experiments to record a large amount of information. The growing size of the datasets…

ATLAS Open Data for Education delivers proton--proton collision data from the ATLAS experiment at CERN to the public along with open-access resources for education and outreach. To date ATLAS has released a substantial amount of data from 8…

High Energy Physics - Experiment · Physics 2025-03-03 Giovanni Guerrieri

Despite growing interest in process analysis and mining for data-aware specifications, alignment-based conformance checking for declarative process models has focused on pure control-flow specifications, or mild data-aware extensions…

The High Level Trigger (HLT) of the future ALICE heavy-ion experiment has to reduce its input data rate of up to 25 GB/s to at most 1.25 GB/s for output before the data is written to permanent storage. To cope with these data rates a large…

Distributed, Parallel, and Cluster Computing · Computer Science 2009-09-29 Timm M. Steinbeck

The CMS experiment at CERN has released research-quality data from particle collisions at the LHC since 2014. Almost all data from the first LHC run in 2010-2012 with the corresponding simulated samples are now in the public domain, and…

High Energy Physics - Experiment · Physics 2021-09-08 Kati Lassila-Perini , Clemens Lange , Edgar Carrera Jarrin , Matthew Bellis

An evolved real-time data processing strategy is proposed for high-energy physics experiments, and its implementation at the LHCb experiment is presented. The reduced event model allows not only the signal candidate firing the trigger to be…

High Energy Physics - Experiment · Physics 2019-06-05 R. Aaij , S. Benson , M. De Cian , A. Dziurda , C. Fitzpatrick , E. Govorkova , O. Lupton , R. Matev , S. Neubert , A. Pearce , H. Schreiner , S. Stahl , M. Vesterinen

Data-intensive science is increasingly reliant on real-time processing capabilities and machine learning workflows, in order to filter and analyze the extreme volumes of data being collected. This is especially true at the energy and…

Artificial Intelligence · Computer Science 2021-04-21 Chinmaya Mahesh , Kristin Dona , David W. Miller , Yuxin Chen