Browsing by Subject "high energy physics"

Now showing 1 - 5 of 5

Access status: Open Access ,
Computational challenges in the measurement of heavy-ion collision event characteristics with the atlas experiment at the LHC
(Wydawnictwa AGH, 2015) Maj, Klaudia; Bołd, Tomasz; Grabowska-Bołd, Iwona
Heavy-ion collisions at extreme energies are expected to recreate conditions present in the early universe, producing a state of matter called the Quark Gluon Plasma (QGP). This state is characterized by very low viscosity resembling the properties of a perfect fluid. In such a medium, density fluctuations can easily propagate. In experimental practice, the size of these fluctuations is estimated by measuring the angular correlation of the particles produced. The aim of this paper is to present results of the measurements of the azimuthal anisotropy of charged particles produced in heavy-ion collisions with the ATLAS detector using the LHC Grid infrastructure for bulk processing of the data and resources available at the Tier-2 computing center for the final analysis stage.
Access status: Open Access ,
Developing artificial intelligence in the cloud: the AI_INFN Platform
(Wydawnictwa AGH, 2025) Anderlini, Lucio; Barbetti, Matteo; Bianchini, Giulio; Ciangottini, Diego; Dal Pra, Stefano; Michelotto, Diego; Petrini, Rosa; Spiga, Daniele
The INFN CSN5-funded project AI_INFN (“artificial intelligence at INFN”) aims to promote ML and AI adoption within INFN by providing comprehensive support, including state of-the-art hardware and cloud-native solutions within INFN Cloud. This facilitates efficient sharing of hardware accelerators with out hindering the institute’s diverse research activities. AI_INFN advances from a Virtual-Machine-based model to a flexible Kubernetes-based platform, offering features such as JWT-based authentication, JupyterHub multitenant interface, distributed file system, customizable conda environments, and specialized monitoring and accounting systems. It also enables virtual nodes in the cluster, offloading computing payloads to remote resources through the Virtual Kubelet technology, with InterLink as provider. This setup can manage workflows across various providers and hardware types, which is crucial for scientific use cases that require dedicated infrastructures for different parts of the workload. Results of initial tests to validate its production applicability, emerging case studies and integration scenarios are presented.
Access status: Open Access ,
Machine learning based event reconstruction for the MUonE experiment
(Wydawnictwa AGH, 2024) Zdybał, Miłosz; Kucharczyk, Marcin; Wolter, Marcin
A proof-of-concept solution based on the machine learning techniques has been implemented and tested within the MUonE experiment designed to search for New Physics in the sector of anomalous magnetic moment of a muon. The results of the DNN based algorithm are comparable to the classical reconstruction, reducing enormously the execution time for the pattern recognition phase. The present implementation meets the conditions of classical reconstruction, providing an advantageous basis for further studies.
Access status: Open Access ,
The ATLAS experiment on-line monitoring and filtering as an example of real-time application
(Wydawnictwa AGH, 2008) Korcyl, Krzysztof; Szymocha, Tadeusz; Funika, Włodzimierz; Kitowski, Jacek; Słota, Renata; Bałos, Kazimierz; Dutka, Łukasz; Guzy, Krzysztof; Kryza, Tomir; Pieczykolan, Jan
The ATLAS detector, recording LHC particles' interactions, produces events with rate of 40 MHz and size of 1.6 MB. The processes with new and interesting physics phenomena are very rare, thus an efficient on-line filtering system (trigger) is necessary. The asynchronous part of that system relays on few thousands of computing nodes running the filtering software. Applying refined filtering criteria results in increase of processing times what may lead to lack of processing resources installed on CERN site. We propose extension to this part of the system based on submission of the real-time filtering tasks into the Grid.
Access status: Open Access ,
The ATLAS experiment simulations as the computing challenge for the ACK CYFRONET AGH
(Wydawnictwa AGH, 2008) Kaczmarska, Anna Ewa; Małecki, Paweł; Szymocha, Tadeusz; Richter-Wąs, Elżbieta
The present High Energy Physics (HEP) experiments require unprecedented amount of computing power and storage space. We present the WLCG structure of the LHC computing, which will be used to perform data processing required by the ATLAS collaboration. We also describe the ATLAS detector full simulation chain. Finally, we quantify the computing needs and up-to-date usage of the ACK CYFRONET AGH resources by the ATLAS detector simulations.