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CS3 2025 - Cloud Storage Synchronization and Sharing
No full textOnedata [1] is a high-performance, distributed data management system designed for global infrastructures. It provides seamless access to heterogeneous storage resources and supports diverse use cases ranging from personal data management to large-scale scientific computations. Leveraging a fully distributed architecture, Onedata facilitates the creation of hybrid cloud environments that integrate private and public cloud resources. The system enables users to collaborate, share, and publish data while supporting high-performance computations on distributed datasets via various interfaces, including POSIX-compliant native mounts, pyfs (Python filesystem) plugins, REST/CDMI APIs, and an S3 protocol (currently in beta).
Recent advancements in Onedata include the development of the *fs.onedatarestfs* Python library, a lightweight *pyfilesystem* client built upon the *OnedataFileRESTClient* library. Within the scope of the EuroScienceGateway project [2], these libraries have been instrumental in integrating Onedata with the Galaxy Project [3] , an open-source platform for data analysis workflows predominantly used in the life sciences. This integration has resulted in a new File Source Plugin and an Object Store for Galaxy. The File Source Plugin enables users to import and export datasets between Onedata and Galaxy, while the Object Store integration allows Onedata to function as a backend storage system for Galaxy datasets. This implementation takes advantage of Onedata’s distributed architecture, creating a synergy with Galaxy’s distributed network of Pulsar endpoints (workflow execution services). By tracking data distribution, it opens the door to locality-aware, smart workflow scheduling, which can reduce data transfer costs, processing delays, and energy usage.
Onedata is currently deployed in several European projects, including EUreka3D [4], EuroScienceGateway [2], DOME [5], and InterTwin [6]. In these projects, Onedata provides a data transparency layer for managing large, distributed datasets in dynamic, hybrid cloud environments with containerized deployments.
Acknowledgements. This work is co-financed by the Polish Ministry of Education and Science under the program entitled International Co-financed Projects (projects no. 5398/DIGITAL/2023/2 and 5399/DIGITAL/2023/2)
References:
1. Onedata. https://onedata.org.
2. EuroScienceGateway Project: Open Infrastructure for Data-Driven Research. https://galaxyproject.org/projects/esg/.
3. The Galaxy Project. https://galaxyproject.org/.
4. EUreka3D: European Union’s REKonstructed in 3D. https://eureka3d.eu.
5. DOME: A Distributed Open Marketplace for Europe Cloud and Edge Services. https://dome-marketplace.eu.
6. InterTwin: Interdisciplinary Digital Twin Engine for Science. https://intertwin.eu
CS3 2025 - Cloud Storage Synchronization and Sharing
No full textInnovations in Artificial Intelligence have led to it becoming an integral part of the society and finding applications in a variety of fields. We analyzed recent requests and cases which we have faced ourselves and came to the conclusion that the use of AI in this or that field is somehow related to documents.
In this session, we will:
• find out what is the connection between document editors and AI;
• highlight what benefits and issues AI can bring to users when working with documents;
• cover AI implementation into office software using the experience of ONLYOFFICE
Magnetoelectric Decoupling in Bismuth Ferrite
No full textIt is still an open question if magnetoelectric coupling occurs at the atomic scale in multiferroic BiFeO3. Nuclear solid-state techniques monitor local fields at the atomic scale. Using such an approach, we show that, contrary to our own expectation, ferroelectric and magnetic ordering in bismuth ferrite (BiFeO3 or BFO) decouple at the unit-cell level. Time differential perturbed angular correlation (TDPAC) data at temperatures below, close, and above the magnetic Néel temperature show that the coupling of the ferroelectric order to magnetization is completely absent at the bismuth site. It is common understanding that the antiferromagnetic order and the cycloidal ordering due to the Dzyaloshinskii-Moriya interaction generate a net zero magnetization of the sample canceling out any magnetoelectric effect at the macroscopic level. Our previous data show that a very large coupling of magnetic moment and electrical distortions arises on the magnetic sublattice (Fe site). The oxygen octahedra around the iron site experience a large tilt due to the onset of magnetic ordering. Nevertheless, the Bi-containing complementary sublattice carrying the largest part of ferroelectric order is practically unaffected by this large structural change in its direct vicinity. The magnetoelectric coupling thus vanishes already at the unit cell level. These experimental results agree well with an ab initio density functional theory (DFT) calculation
Efficient many-jet event generation with Flow Matching
No full textWe apply for the first time the Flow Matching method to the problem of phase-space sampling for event generation in high-energy collider physics. By training the model to remap the random numbers used to generate the momenta and helicities of the scattering matrix elements as implemented in the portable partonic event generator Pepper, we find substantial efficiency improvements in the studied processes. We focus our study on the highest final-state multiplicities in Drell--Yan and top--antitop pair production used in simulated samples for the Large Hadron Collider, which computationally are the most relevant ones. We find that the unweighting efficiencies improve by factors of 150 and 17, respectively, when compared to the standard approach of using a Vegas-based optimisation. We also compare Continuous Normalizing Flows trained with Flow Matching against the previously studied Normalizing Flows based on Coupling Layers and find that the former leads to better results, faster training and a better scaling behaviour across the studied multiplicity range
The DAQ software for ATLAS Inner Pixel Tracker system testing for HL-LHC
No full textThe ATLAS experiment is preparing for the High-Luminosity LHC era, by replacing thecurrent innermost detector with an advanced all-silicon tracker (pixels and strips) to withstandradiation damage and increased particle activity. Pixel module quality control tests span variousproduction stages which necessitates a robust data acquisition software capable of handling highdata rates for fast readout and performing calibrations at MHz frequencies on several front-endssimultaneously. Yet Another Rapid Readout software, adaptable to diverse hardware platformsincluding ATLAS Phase-II readout board, facilitates these testing scenarios. This contributionhighlights YARR's key features and developments towards benchmarking the performance of the ATLASinner tracker pixel modules using the official ATLAS Phase-II readout system
Searches for exotic particles in multileptonic final states with the ATLAS detector using full Run-2 data
No full textOver the past years, the need for an extension of the Standard
Model (SM) has become more and more clear, so high-energy physics experiments
must explore Beyond the SM (BSM) scenarios, which now constitute an important
part of the ATLAS experiment physics program. Searches for multileptonic
final states have favourable signatures thanks to the low number of SM processes
procuding events with high lepton multiplicity, as these would worsen the signalto-
background ratio. In the context of Left-Right Symmetric Model (LRSM) and
the Type-III See-Saw mechanism, New Physics events are searched for in several
processes, like the production of doubly charged Higgs bosons and the production
of heavy neutral or charged leptons. The final states investigated can also involve
same-sign light leptons, allowing lepton-number-violation foreseen by the LRSM.
ATLAS BSM searches exploring these scenarios with full LHC Run-2 data, for a total
luminosity of 139 fb at a centre-of-mass energy of = 13TeV in collisions, are here presented
Evaluating the performance and long-term stability with LHC-like background irradiation of RPC detectors with CO2-based gas mixtures
No full textResistive Plate Chamber (RPC) detectors at CERN’s LHC experiments traditionally use a Freon-based gas mixture containing C2H2F4 (R-134a) and SF6, both of which are high global warming potential (GWP) gases. To reduce greenhouse gas (GHG) emissions, operational costs, and optimise RPC performance, one possible mid-term solution is the gas mixture with a substitution of 30% of R-134a with CO2 in the standard RPC gas mixture. This gas mixture was successfully adopted in the ATLAS RPC system since August 2023. This study investigates the detector’s performance when CO2 is introduced into the standard gas mixture to minimise emissions while maintaining compatibility with current CERN RPC systems. Conducted at the CERN Gamma Irradiation Facility (GIF++), this research uses a 12 TBq 137Cs source and a muon beam to simulate the LHC experiment’s background radiation. The setup includes 2 mm single-gap High-Pressure Laminate (HPL) RPCs placed at different distances from the gamma source. Since March 2023, the detectors inside the bunker have been continuously irradiated to assess long-term performance, targeting the integrated charge expected for ATLAS RPC detectors in LHC Run 3 and the High-Luminosity LHC phase. Monitoring is performed using various metrics such as gas analysis, oxygen content, humidity, dose, environmental parameters, and flow measurements to ensure the gas system operates correctly. Several periodic test beam periods are conducted to assess muon performance parameters, including: efficiency, current, streamer probability, mean prompt charge, cluster size, time resolution. Results from the ageing studies, using the proposed 30% CO2 gas mixture, are presented
First observation of ultra-long-range azimuthal correlations in low multiplicity pp and p–Pb collisions at the LHC
No full textThis study presents the first observation of ultra-long-range two-particle azimuthal correlations with pseudorapidity separation of in proton–proton (pp) andf in proton–lead (p–Pb) collisions at the LHC, down to and below the minimum-bias multiplicity. Two-particle correlation coefficients () are measured after removing non-flow (jets and resonance decays) contributions using the template-fit method across various multiplicity classes, providing novel insights into the origin of long-range correlations in small systems. Comparisons with the 3D-Glauber + MUSIC + UrQMD hydrodynamic model reveal significant discrepancies at low multiplicities, indicating possible dynamics beyond typical hydrodynamic behavior. Initial-state models based on the Color Glass Condensate framework generate only short-range correlations, while PYTHIA simulations implemented with the string-shoving mechanism also fail to describe these ultra-long-range correlations. The results challenge existing paradigms and question the underlying mechanisms in low-multiplicity pp and p–Pb collisions. The findings impose significant constraints on models describing collective phenomena in small collision systems and advance the understanding of origin of long-range correlations at Large Hadron Collider (LHC) energies.This study presents the first observation of ultra-long-range two-particle azimuthal correlations with pseudorapidity separation of () in proton-proton (pp) and () in proton-lead (p-Pb) collisions at the LHC, down to and below the minimum-bias multiplicity. Two-particle correlation coefficients () are measured after removing non-flow (jets and resonance decays) contributions using the template-fit method across various multiplicity classes, providing novel insights into the origin of long-range correlations in small systems. Comparisons with the 3D-Glauber + MUSIC + UrQMD hydrodynamic model reveal significant discrepancies at low multiplicities, indicating possible dynamics beyond typical hydrodynamic behavior. Initial-state models based on the Color Glass Condensate framework generate only short-range correlations, while PYTHIA simulations implemented with the string-shoving mechanism also fail to describe these ultra-long-range correlations. The results challenge existing paradigms and question the underlying mechanisms in low-multiplicity pp and p-Pb collisions. The findings impose significant constraints on models describing collective phenomena in small collision systems and advance the understanding of origin of long-range correlations at Large Hadron Collider (LHC) energies
Search for dark matter recoiling from a low-multiplicity jet in proton-proton collisions at 13 TeV
No full textA search for dark matter particles, using events containing an imbalance in transverse momentum and one energetic low-multiplicity jet, is performed using data collected in proton-proton collisions with the CMS detector at a center-of-mass energy of . The analysis is based on a data set corresponding to an integrated luminosity of collected from 2016-2018. This is the first search using the low-multiplicity jet signature at the LHC and supervised machine learning and data augmentation techniques are used to enhance signal sensitivity. No excess of events over the standard model background expectation is observed. Upper limits on the dark matter production cross sections in simplified models with vector and axial vector mediators are set at the confidence level (CL). Mediator masses of up to 4250 are excluded at CL for dark matter mass of 100 and mediator masses of up to 3500 are excluded at CL for dark matter mass of 550
Long-range transverse momentum correlations and radial flow in Pb–Pb collisions at the LHC
No full textThis Letter presents measurements of long-range transverse-momentum correlations using a new observable, , which serves as a probe of radial flow and medium properties in heavy-ion collisions. Results are reported for inclusive charged particles, pions, kaons, and protons across various centrality intervals in Pb-Pb collisions at TeV, recorded by the ALICE detector. A pseudorapidity-gap technique, similar to that used in anisotropic-flow studies, is employed to suppress short-range correlations. At low , a characteristic mass ordering consistent with hydrodynamic collective flow is observed. At higher ( GeV/), protons exhibit larger than pions and kaons, in agreement with expectations from quark-recombination models. These results are sensitive to the bulk viscosity and the equation of state of the QCD medium formed in heavy-ion collisions.This Letter presents measurements of long-range transverse-momentum correlations using a new observable, , which serves as a probe of radial flow and medium properties in heavy-ion collisions. Results are reported for inclusive charged particles, pions, kaons, and protons across various centrality intervals in PbPb collisions at TeV, recorded by the ALICE detector. A pseudorapidity-gap technique, similar to that used in anisotropic-flow studies, is employed to suppress short-range correlations. At low , a characteristic mass ordering consistent with hydrodynamic collective flow is observed. At higher ( GeV/), protons exhibit larger than pions and kaons, in agreement with expectations from quark-recombination models. These results are sensitive to the bulk viscosity and the equation of state of the QCD medium formed in heavy-ion collisions