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1

Arsene, Ionut Cristian. „ALICE Highlights“. EPJ Web of Conferences 296 (2024): 01001. http://dx.doi.org/10.1051/epjconf/202429601001.

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A summary including highlights of recent ALICE results, the status of the data taking in LHC Run 3 and of the ALICE detector upgrades is shown. The physics results are obtained mainly using the data recorded in pp, p–Pb and Pb–Pb during the LHC Run 2, but a set of results obtained in pp collisions with the Run 3 data is also discussed.
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2

Grelli, Alessandro. „ALICE Overview“. EPJ Web of Conferences 171 (2018): 01005. http://dx.doi.org/10.1051/epjconf/201817101005.

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3

Toia, Alberica. „ALICE @ LHC: Status and Highlights“. EPJ Web of Conferences 129 (2016): 00029. http://dx.doi.org/10.1051/epjconf/201612900029.

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4

Kuhn, C. „The ALICE experiment at LHC“. Nuclear Physics A 787, Nr. 1-4 (Mai 2007): 19–28. http://dx.doi.org/10.1016/j.nuclphysa.2006.12.010.

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5

Giubellino, P. „The ALICE detector at LHC“. Nuclear Instruments and Methods in Physics Research Section A: Accelerators, Spectrometers, Detectors and Associated Equipment 344, Nr. 1 (April 1994): 27–38. http://dx.doi.org/10.1016/0168-9002(94)90647-5.

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6

VERCELLIN, ERMANNO. „THE ALICE EXPERIMENT AT CERN LHC: STATUS AND FIRST RESULTS“. International Journal of Modern Physics A 26, Nr. 03n04 (10.02.2011): 517–22. http://dx.doi.org/10.1142/s0217751x11051925.

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The ALICE experiment is aimed at studying the properties of the hot and dense matter produced in heavy-ion collisions at LHC energies. In the first years of LHC operation the ALICE physics program will be focused on Pb - Pb and p - p collisions. The latter, on top of their intrinsic interest, will provide the necessary baseline for heavy-ion data. After its installation and a long commissioning with cosmic rays, in late fall 2009 ALICE participated (very successfully) in the first LHC run, by collecting data in p - p collisions at c.m. energy 900 GeV. After a short stop during winter, LHC operations have been resumed; the machine is now able to accelerate proton beams up to 3.5 TeV and ALICE has undertaken the data taking campaign at 7 TeV c.m. energy. After an overview of the ALICE physics goals and a short description of the detector layout, the ALICE performance in p - p collisions will be presented. The main physics results achieved so far will be highlighted as well as the main aspects of the ongoing data analysis.
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Acharya 0000-0002-9213-5329, S., R. Acosta Hernandez, D. Adamová 0000-0002-0504-7428, A. Adler, J. Adolfsson 0000-0001-5651-4025, D. Agguiaro, G. Aglieri Rinella 0000-0002-9611-3696 et al. „ALICE upgrades during the LHC Long Shutdown 2“. Journal of Instrumentation 19, Nr. 05 (01.05.2024): P05062. http://dx.doi.org/10.1088/1748-0221/19/05/p05062.

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Abstract A Large Ion Collider Experiment (ALICE) has been conceived and constructed as a heavy-ion experiment at the LHC. During LHC Runs 1 and 2, it has produced a wide range of physics results using all collision systems available at the LHC. In order to best exploit new physics opportunities opening up with the upgraded LHC and new detector technologies, the experiment has undergone a major upgrade during the LHC Long Shutdown 2 (2019–2022). This comprises the move to continuous readout, the complete overhaul of core detectors, as well as a new online event processing farm with a redesigned online-offline software framework. These improvements will allow to record Pb-Pb collisions at rates up to 50 kHz, while ensuring sensitivity for signals without a triggerable signature.
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8

Collaboration, Francesco. „ALICE Highlights“. Proceedings 13, Nr. 1 (06.06.2019): 6. http://dx.doi.org/10.3390/proceedings2019013006.

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Deconfined strongly interacting QCD matter is produced in the laboratory at the highest energy densities in heavy-ion collisions at the LHC. A selection of recent results from ALICE is presented, spanning observables from the soft sector (bulk particle production and correlations), the hard probes (charmed hadrons and jets) and signatures of possible collective effects in pp and p–Pb collisions with high multiplicity. Finally, the perspectives after the detectors upgrades, taking place in the period 2019–2020, are presented.
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Malinina, L. V. „Femtoscopy with ALICE at the LHC“. KnE Energy 3, Nr. 1 (09.04.2018): 320. http://dx.doi.org/10.18502/ken.v3i1.1761.

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10

Sultanov, Rishat. „Jet measurements by ALICE at LHC“. Ядерная физика и инжиниринг 5, Nr. 11 (2014): 880–84. http://dx.doi.org/10.1134/s2079562914080430.

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11

Badalá, A., und J. Stachel. „Strangeness measurements at LHC with ALICE“. Journal of Physics: Conference Series 312, Nr. 1 (23.09.2011): 012004. http://dx.doi.org/10.1088/1742-6596/312/1/012004.

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12

Crochet, P. „The ALICE experiment at the LHC“. European Physical Journal Special Topics 162, Nr. 1 (August 2008): 205–11. http://dx.doi.org/10.1140/epjst/e2008-00795-6.

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13

Bellini, Francesca. „Strangeness in ALICE at the LHC“. Journal of Physics: Conference Series 779 (Januar 2017): 012007. http://dx.doi.org/10.1088/1742-6596/779/1/012007.

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14

Sultanov, Rishat. „Jet measurements by ALICE at LHC“. Physics of Atomic Nuclei 78, Nr. 14 (Dezember 2015): 1587–90. http://dx.doi.org/10.1134/s1063778815130335.

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15

Crochet, P. „The ALICE experiment at the LHC“. Physics of Particles and Nuclei 39, Nr. 7 (23.11.2008): 1074–81. http://dx.doi.org/10.1134/s1063779608070174.

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16

Fabjan, C. „ALICE at LHC Detector and Physics“. Nuclear Physics A 752 (April 2005): 439–46. http://dx.doi.org/10.1016/j.nuclphysa.2005.02.138.

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17

Vercellin, E. „The ALICE experiment at the LHC“. Nuclear Physics A 805, Nr. 1-4 (Juni 2008): 511c—518c. http://dx.doi.org/10.1016/j.nuclphysa.2008.02.289.

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18

Schicker, R. „Central exclusive production in the ALICE experiment at the LHC“. International Journal of Modern Physics A 29, Nr. 28 (10.11.2014): 1446015. http://dx.doi.org/10.1142/s0217751x14460154.

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The ALICE experiment at the Large Hadron Collider (LHC) at CERN consists of a central barrel, a muon spectrometer and additional detectors for trigger and event classification purposes. The low transverse momentum threshold of the central barrel gives ALICE a unique opportunity to study the low mass sector of central exclusive production at the LHC.
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Graczykowski, Łukasz Kamil, Monika Jakubowska, Kamil Rafał Deja und Maja Kabus. „Using machine learning for particle identification in ALICE“. Journal of Instrumentation 17, Nr. 07 (01.07.2022): C07016. http://dx.doi.org/10.1088/1748-0221/17/07/c07016.

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Abstract Particle identification (PID) is one of the main strengths of the ALICE experiment at the LHC. It is a crucial ingredient for detailed studies of the strongly interacting matter formed in ultrarelativistic heavy-ion collisions. ALICE provides PID information via various experimental techniques, allowing for the identification of particles over a broad momentum range (from around 100 MeV/c to around 50 GeV/c). The main challenge is how to combine the information from various detectors effectively. Therefore, PID represents a model classification problem, which can be addressed using Machine Learning (ML) solutions. Moreover, the complexity of the detector and richness of the detection techniques make PID an interesting area of research also for the computer science community. In this work, we show the current status of the ML approach to PID in ALICE. We discuss the preliminary work with the Random Forest approach for the LHC Run 2 and a more advanced solution based on Domain Adaptation Neural Networks, including a proposal for its future implementation within the ALICE computing software for the upcoming LHC Run 3.
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Kvapil, Jakub, Anju Bhasin, Marek Bombara, David Evans, Anton Jusko, Alexander Kluge, Marian Krivda et al. „ALICE Central Trigger System for LHC Run 3“. EPJ Web of Conferences 251 (2021): 04022. http://dx.doi.org/10.1051/epjconf/202125104022.

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A major upgrade of the ALICE experiment is in progress and will result in high-rate data taking during LHC Run 3 (2022-2024). The LHC interaction rate at Point 2 where the ALICE experiment is located will be increased to 50 kHz in Pb–Pb collisions and 1 MHz in pp collisions. The ALICE experiment will be able to read out data at these interaction rates leading to an increase of the collected luminosity by a factor of up to about 100 with respect to LHC Runs 1 and 2. To satisfy these requirements, a new readout system has been developed for most of the ALICE detectors, allowing the full readout of the data at the required interaction rates without the need for a hardware trigger selection. A novel trigger and timing distribution system will be implemented, based on Passive Optical Network (PON) and GigaBit Transceiver (GBT) technology. To assure backward compatibility a triggered mode based on RD12 Trigger- Timing-Control (TTC) technology, as used in the previous LHC runs, will be maintained and re-implemented under the new Central Trigger System (CTS). A new universal ALICE Trigger Board (ATB) based on the Xilinx Kintex Ultrascale FPGA has been designed to function as a Central Trigger Processor (CTP), Local Trigger Unit (LTU), and monitoring interfaces. In this paper, this new hybrid multilevel system with continuous readout will be described, together with the triggering mechanism and algorithms. An overview of the CTS, the design of the ATB and the different communication protocols will be presented.
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21

Popa, Mircea, Costin Grigoras und Sofia Vallecorsa. „Predicting ALICE Grid throughput using recurrent neural networks“. Journal of Physics: Conference Series 2438, Nr. 1 (01.02.2023): 012059. http://dx.doi.org/10.1088/1742-6596/2438/1/012059.

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Abstract The Worldwide LHC Computing Grid (WLCG) is the infrastructure enabling the storage and processing of the large amount of data generated by the LHC experiments, and in particular the ALICE experiment. With the foreseen increase in the computing requirements of the future High Luminosity LHC experiments, a data placement strategy which increases the efficiency of the WLCG computing infrastructure becomes extremely relevant for the scientific success of the LHC scientific programme. Currently, the data placement at the ALICE Grid computing sites is determined by heuristic algorithms. Optimisation of the data storage could yield substantial benefits in terms of efficiency and time-to-result. This has however proven to be arduous due to the complexity of the problem. In this work we propose a modelisation of the behaviour of the system via principal component analysis, time series analysis and deep learning, starting from the detailed data collected by the MonALISA monitoring system. We show that it is possible to analyse and model the throughput of the ALICE Grid to a level that has not been possible before, comparing the performance of different deep learning architectures based on recurrent neural networks. Analyzing about six weeks of activity, the Grid I/O throughput trend is successfully predicted with a mean relative error of 4%, while the prediction of the throughput itself performs at 5%.
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Arsuaga-Rios, Maria, Vladimír Bahyl, Manuel Batalha, Cédric Caffy, Eric Cano, Niccolo Capitoni, Cristian Contescu et al. „LHC Data Storage: Preparing for the Challenges of Run-3“. EPJ Web of Conferences 251 (2021): 02023. http://dx.doi.org/10.1051/epjconf/202125102023.

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The CERN IT Storage Group ensures the symbiotic development and operations of storage and data transfer services for all CERN physics data, in particular the data generated by the four LHC experiments (ALICE, ATLAS, CMS and LHCb). In order to accomplish the objectives of the next run of the LHC (Run-3), the Storage Group has undertaken a thorough analysis of the experiments’ requirements, matching them to the appropriate storage and data transfer solutions, and undergoing a rigorous programme of testing to identify and solve any issues before the start of Run-3. In this paper, we present the main challenges presented by each of the four LHC experiments. We describe their workflows, in particular how they communicate with and use the key components provided by the Storage Group: the EOS disk storage system; its archival back-end, the CERN Tape Archive (CTA); and the File Transfer Service (FTS). We also describe the validation and commissioning tests that have been undertaken and challenges overcome: the ATLAS stress tests to push their DAQ system to its limits; the CMS migration from PhEDEx to Rucio, followed by large-scale tests between EOS and CTA with the new FTS “archive monitoring” feature; the LHCb Tier-0 to Tier-1 staging tests and XRootD Third Party Copy (TPC) validation; and the erasure coding performance in ALICE.
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Mrnjavac, Teo, Konstantinos Alexopoulos, Vasco Chibante Barroso, Claire Guyot, Piotr Konopka und George Raduta. „AliECS: A New Experiment Control System for the ALICE Experiment“. EPJ Web of Conferences 295 (2024): 02027. http://dx.doi.org/10.1051/epjconf/202429502027.

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The ALICE Experiment at CERN’s Large Hadron Collider (LHC) has undergone a major upgrade during LHC Long Shutdown 2 in 2019-2021, which includes a new computing system called O2 (Online-Offline). To ensure the efficient operation of the upgraded experiment and of its newly designed computing system, a reliable, high performance, full-featured experiment control system has also been developed and deployed at LHC Point 2. The ALICE Experiment Control System (AliECS) is a microservices-oriented system based on state-of-the-art cluster management technologies that emerged recently in the distributed and high-performance computing ecosystem. It is designed, developed and maintained as a comprehensive solution and single entry point for control of experiment data acquisition (up to 3.5 TB/s) and processing. This communication describes the AliECS architecture by providing an in-depth overview of the system’s components, interfaces, features, and design elements, as well as its performance. It also reports on the experience with AliECS during the first year of ALICE Run 3 data taking with LHC beam, including integration and operational challenges, and lessons learned from real-world use.
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24

Vasileiou, Maria. „Strangeness production with ALICE at the LHC“. Physica Scripta 95, Nr. 6 (20.04.2020): 064007. http://dx.doi.org/10.1088/1402-4896/ab85fc.

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25

Collaboration, The ALICE, K. Aamodt, A. Abrahantes Quintana, R. Achenbach, S. Acounis, D. Adamová, C. Adler et al. „The ALICE experiment at the CERN LHC“. Journal of Instrumentation 3, Nr. 08 (14.08.2008): S08002. http://dx.doi.org/10.1088/1748-0221/3/08/s08002.

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26

Turrisi, Rosario. „Charm and beauty with ALICE at LHC“. Nuclear Physics B - Proceedings Supplements 142 (Mai 2005): 459–63. http://dx.doi.org/10.1016/j.nuclphysbps.2005.01.079.

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27

Hadjidakis, Cynthia. „Quarkonium production in ALICE at the LHC“. Nuclear Physics A 932 (Dezember 2014): 541–48. http://dx.doi.org/10.1016/j.nuclphysa.2014.09.085.

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28

Kuijer, P. „The alice experiment at the CERN LHC“. Nuclear Physics B - Proceedings Supplements 117 (April 2003): 62–64. http://dx.doi.org/10.1016/s0920-5632(03)90488-9.

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29

Malek, Magdalena. „Quarkonia measurements with ALICE at the LHC“. Nuclear Physics A 830, Nr. 1-4 (November 2009): 339c—342c. http://dx.doi.org/10.1016/j.nuclphysa.2009.10.029.

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30

Morsch, A. „Jet physics at the LHC with ALICE“. European Physical Journal C 43, Nr. 1-4 (08.07.2005): 333–36. http://dx.doi.org/10.1140/epjc/s2005-02211-4.

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31

Patel, P., und M. Trzebiński. „High Luminosity LHC Optics Feasibility Studies for: ATLAS, ALICE, and LHCb“. Acta Physica Polonica B Proceedings Supplement 17, Nr. 5 (2024): 1. http://dx.doi.org/10.5506/aphyspolbsupp.17.5-a30.

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32

SIMILI, EMANUELE. „ELLIPTIC FLOW SIMULATION AND ANALYSIS IN ALICE“. International Journal of Modern Physics E 16, Nr. 07n08 (August 2007): 2528–34. http://dx.doi.org/10.1142/s0218301307008203.

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Based on flow measurements at the SPS and RHIC, the expected values of elliptic flow and charged multiplicity have been extrapolated as a function of the impact parameter to LHC energy. Those predictions have been used as an input for ALICE simulation, to develop and test a flow analysis package for the ALICE environment. The Event Plane analysis has provided an estimate of the event plane resolution at the LHC and it has also been applied to Hijing events generated with no genuine elliptic flow. In this kind of environment it has been possible to study the effects on v2 from pure non-flow effects, and thus get an estimate of the systematics due to non-flow.
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33

Paul, Biswarup. „Recent ALICE results on quarkonium production in nuclear collisions“. Journal of Physics: Conference Series 2586, Nr. 1 (01.09.2023): 012007. http://dx.doi.org/10.1088/1742-6596/2586/1/012007.

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Abstract Quarkonium production has long been regarded as a potential probe of deconfinement in nucleus-nucleus collisions. Recently, the production of J/ψ via regeneration within the quark-gluon plasma (QGP) or at the phase boundary has been identified as an important ingredient for the interpretation of quarkonium production results from lead-lead collisions at the Large Hadron Collider (LHC). Quarkonium polarization could also be used to investigate the properties of the hot and dense medium created at LHC energies, as well as the initial stages of the heavy-ion collision. In this contribution, the latest ALICE quarkonium results are presented and discussed. These include, among others, the nuclear modification of (prompt, non-prompt and inclusive) J/ψ, the ψ(2S) production, and the J/ψ polarization, all measured in lead-lead collisions at the LHC. The results are compared with available theoretical model calculations.
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34

Kiselev, Sergey. „Hadronic resonance production with ALICE at the LHC“. EPJ Web of Conferences 204 (2019): 03015. http://dx.doi.org/10.1051/epjconf/201920403015.

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We present recent results on short-lived hadronic resonances obtained in the ALICE experiment at LHC energies, including results from the Xe-Xe run. The ALICE results on transverse momentum spectra, yields, their ratio to long-lived particles, and nuclear modification factors will be discussed. The results will be compared with model predictions and measurements at lower energies.
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35

Caffy, Cedric, Guilherme Amadio, Maria Arsuaga Rios, Manuel Batalha Reis, Niccolo Capitoni, Cristian Contescu, Jaroslav Guenther et al. „Operation of the CERN disk storage infrastructure during LHC Run-3“. EPJ Web of Conferences 295 (2024): 01041. http://dx.doi.org/10.1051/epjconf/202429501041.

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The CERN IT Storage group operates multiple distributed storage systems to support all CERN data storage requirements. The storage and distribution of physics data generated by LHC and non-LHC experiments is one of the biggest challenges the group has to take on during LHC Run-3.EOS [1], the CERN distributed disk storage system is playing a key role in LHC data-taking. During the first ten months of 2022, more than 440PB have been written by the experiments and 2.9EB have been read out. The data storage requirements of LHC Run-3 are higher than what was previously delivered. The storage operations team has started investigating multiple areas to upgrade and optimize the current storage resources. A new, dedicated and redundant EOS infrastructure based on 100Gbit servers was installed, commissioned and deployed for the ALICE Online and Offline (O2) project. This cluster can sustain high-throughput data transfer between the ALICE Event Processing Nodes (EPN) and the CERN’s data center.This paper will present the architecture, techniques and workflows in place allowing EOS to deliver fast, reliable and scalable data storage to meet experiment needs during LHC Run-3 and beyond.
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Mrnjavac, Teo, und Vasco Chibante Barroso. „Towards The Alice Online-Offline (O2) Control System“. EPJ Web of Conferences 214 (2019): 01033. http://dx.doi.org/10.1051/epjconf/201921401033.

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The ALICE Experiment at CERN LHC (Large Hadron Collider) is under preparation for a major upgrade that is scheduled to be deployed during Long Shutdown 2 in 2019-2020 and that includes new computing systems, called O2 (Online-Offine). To ensure the efficient operation of the upgraded experiment along with its newly designed computing system, a reliable, high performance and automated control system will be developed with the goal of managingthe lifetime of all the O2 processes, and of handling the various phases of the data taking activity by interacting with the detectors, the trigger system and the LHC. The ALICE O2 control system will be a distributed systembased on state of the art cluster management and microservices which have recently emerged in the distributed computing ecosystem. Such technologies weren’t available during the design and development of the original LHC computing systems, and their use will allow the ALICE collaboration to benefit from a vibrant and innovatingopen source community. This paper illustrates the O2 control system architecture. It evaluates several olutionsthat were considered during an initial prototyping phase and provides a rationale for the choices made. It also provides an in-depth overview of the components, features and design elements of the actual system.
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Ristea, Catalin. „Recent results from the ALICE Experiment at LHC“. EPJ Web of Conferences 191 (2018): 01004. http://dx.doi.org/10.1051/epjconf/201819101004.

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ALICE (A Large Ion Collider Experiment) at the LHC performed high statistics measurements in Pb-Pb collisions at the top LHC energy, complemented with large recent reference datasets in elementary proton-proton collisions at the same energy. Elementary pp collisions are serving as baseline for testing QCD properties and allow the study of the changes induced by the hot and dense medium produced in heavy ion collisions. Key observables like nuclear modification factors, jet production, flow phenomena and spectra for identified particles, related to the different stages of collision evolution, are presented and compared with the most recent results from p-Pb and Xe-Xe collisions, thus allowing to probe both initial cold nuclear matter and final state effects, combined with the system size dependence of the measurements.
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38

Mrnjavac, Teo, Konstantinos Alexopoulos, Vasco Chibante Barroso und George Raduta. „AliECS: a New Experiment Control System for the ALICE Experiment“. EPJ Web of Conferences 245 (2020): 01033. http://dx.doi.org/10.1051/epjconf/202024501033.

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The ALICE Experiment at CERN’s Large Hadron Collider (LHC) is undertaking a major upgrade during LHC Long Shutdown 2 in 2019-2021, which includes a new computing system called O2 (Online-Offline). To ensure the efficient operation of the upgraded experiment and of its newly designed computing system, a reliable, high performance, and automated experiment control system is being developed. The ALICE Experiment Control System (AliECS) is a distributed system based on state of the art cluster management and microservices that have recently emerged in the distributed computing ecosystem. Such technologies will allow the ALICE collaboration to benefit from a vibrant and innovating open source community. This communication describes the AliECS architecture. It provides an in-depth overview of the system’s components, features, and design elements, as well as its performance. It also reports on the experience with AliECS as part of ALICE Run 3 detector commissioning setups.
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BASTID, N. „PROTON-PROTON PHYSICS WITH THE ALICE MUON SPECTROMETER AT THE LHC“. International Journal of Modern Physics E 16, Nr. 07n08 (August 2007): 2438–44. http://dx.doi.org/10.1142/s0218301307008069.

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ALICE, the dedicated heavy ion experiment at the LHC, will also have an important impact on the proton-proton physics program. The physics analyses foreseen with the ALICE muon spectrometer are reviewed. A particular emphasis is placed on heavy flavor measurement.
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40

Peresunko, Dmitri. „Overview of hard hadron production results in ALICE“. EPJ Web of Conferences 222 (2019): 01003. http://dx.doi.org/10.1051/epjconf/201922201003.

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The ALICE experiment is designed to study the properties the hot and dense medium, the Quark-Gluon Plasma (QGP), produced in ultrarelativistic heavy-ion collisions at the LHC. Measuring production of hadrons with large Q2 transfer in these collisions provides the possibility to explore one of the most spectacular effects — the in-medium parton energy loss. By varying the observables among light and heavy flavored hadrons and fully reconstructed jets and by changing the colliding systems from pp to p–Pb and Pb–Pb, one can explore the transport properties of hot matter in great details. Here an overview of recent ALICE results on high-pT hadron and jet production in pp, p-A and A-A collisions at LHC energies is presented.
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Liu, J. „Performance of the ALICE upgraded inner tracking system“. Journal of Instrumentation 17, Nr. 04 (01.04.2022): C04032. http://dx.doi.org/10.1088/1748-0221/17/04/c04032.

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Abstract Major upgrades of the ALICE (A Large Ion Collider Experiment) detector are underway and will be completed during the LHC long shutdown 2 in order to start operation in 2022 for LHC run 3. One key part of this upgrade is the new Inner Tracking System (ITS2), a full silicon-pixel detector constructed entirely with CMOS monolithic active pixel sensors. The upgraded ITS2 detector consists of three inner layers (50 μm thick sensors) and four outer layers (100 μm thick sensors) covering 10 m2 and containing 12.5 billion pixels with a pixel pitch of 27 μm × 29 μm. Compared with the silicon tracking system used during the LHC run 1 and run 2, the increased granularity, the very low material budget (0.35% X 0/layer in the inner barrel) as well as a smaller beam pipe radius, will result in a significant improvement of impact-parameter resolution and tracking efficiency. The assembly of the detector and services finished in December 2019, and the detector was fully installed in the ALICE experiment in May 2021. A comprehensive commissioning phase (on the surface) was completed in December 2020 to validate the detector performance. In this paper, an overview of the design and construction, as well as the performance of the ITS2 studied from the on-surface commissioning will be discussed in detail.
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Arslandok, Mesut, Ernst Hellbär, Marian Ivanov, Robert Helmut Münzer und Jens Wiechula. „Track Reconstruction in a High-Density Environment with ALICE“. Particles 5, Nr. 1 (10.03.2022): 84–95. http://dx.doi.org/10.3390/particles5010008.

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ALICE is the dedicated heavy-ion experiment at the CERN Large Hadron Collider (LHC). Its main tracking and particle-identification detector is a large volume Time Projection Chamber (TPC). The TPC has been designed to perform well in the high-track density environment created in high-energy heavy-ion collisions. In this proceeding, we describe the track reconstruction procedure in ALICE. In particular, we focus on the two main challenges that were faced during the Run 2 data-taking period (2015–2018) of the LHC, which were the baseline fluctuations and the local space charge distortions in the TPC. We present the corresponding solutions in detail and describe the software tools that allowed us to circumvent these challenges.
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43

von Haller, Barthélémy, und Piotr Konopka. „The ALICE Data Quality Control“. EPJ Web of Conferences 295 (2024): 02026. http://dx.doi.org/10.1051/epjconf/202429502026.

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ALICE (A Large Ion Collider Experiment) has undertaken a major upgrade during the Long Shutdown 2. The increase in the detector data rates, and in particular the continuous readout of the TPC, led to a hundredfold increase in the input raw data, up to 3.5 TB/s. To cope with it, a new common Online and Offline computing system, called O2, has been developed and put in production. The online Data Quality Monitoring (DQM) and the offline Quality Assurance (QA) are critical aspects of the data acquisition and reconstruction software chains. The former intends to provide shifters with precise and complete information to quickly identify and overcome problems while the latter aims at selecting good quality data for physics analyses. Both DQM and QA typically involve the gathering of data, its distributed analysis by user-defined algorithms, the merging of the resulting objects and their visualization. This paper discusses the final architecture and design of the Quality Control (QC), which runs synchronously to data taking and asynchronously on the Worldwide LHC Computing Grid. Following the successful first year of data taking with beam, we will present our experience and the lessons we learned, before and after the LHC restart, when monitoring the data quality in a realworld and challenging environment. We will finally illustrate the wide range of usages people make of this system by presenting a few, carefully picked, use cases.
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SCAPPARONE, EUGENIO. „SOFT QCD AND DIFFRACTIVE PHYSICS AT LHC“. International Journal of Modern Physics A 27, Nr. 32 (30.12.2012): 1230034. http://dx.doi.org/10.1142/s0217751x12300347.

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After a short introduction on the importance of the soft and of the diffractive studies in the understanding of minimum bias events, the main results obtained at LHC are discussed. This overview includes identified particle and inclusive measurements, minimum bias and underlying events, all of them shedding light on the soft process production mechanisms. The results of the inelastic cross-section measurements obtained by the LHC experiments and their compatibility are discussed together with the models used to extrapolate the data at low diffractive masses. A review of the most recent diffraction results is presented, showing the different approaches used by the LHC experiments, relying on different experimental techniques. The combination of the results obtained by ALICE, ATLAS, CMS, LHCb and TOTEM provides a wide sample of informations, covering an unprecedented pseudorapidity range. A detailed comparison between the obtained results is shown, followed by a critical discussion on the still existing discrepancies between the experimental data and the Monte Carlo used at LHC to simulate soft and diffractive physics.
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Sanna, Isabella. „Novel silicon detectors in ALICE at the LHC: The ITS3 and ALICE 3 upgrades“. EPJ Web of Conferences 296 (2024): 08002. http://dx.doi.org/10.1051/epjconf/202429608002.

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The ALICE experiment is preparing for the ITS3 upgrade, which is set to take place during the LHC Long Shutdown 3. The aim of this upgrade is to replace the three innermost tracking layers with truly cylindrical wafer-scale Monolithic Active Pixel Sensors (MAPS). By adopting this innovative technology, ALICE will further reduce the material budget and the distance from the interaction point, thus significantly improving its tracking and vertexing capabilities. The R&D program for ITS3 includes several advancements, such as operability of bent MAPS, validation of the 65 nm CMOS technology, and employment of the stitching process to produce wafer-scale sensors. In addition to the ITS3 upgrade, ALICE is designing a completely new apparatus, ALICE 3, planned for LHC Runs 5 and 6. The detector consists of a large MAPS-based tracking system covering eight units of pseudorapidity, complemented by multiple systems for particle identification, including silicon time-of-flight layers, a ring-imaging Cherenkov detector, a muon identification system, and an electromagnetic calorimeter. The vertex detector is based on an evolution of the ITS3 concept aiming at a track pointing resolution of better than 10 μm for tranverse momenta above 200 MeV/c through the integration of the tracking layers in a retractable structure inside the beam pipe. In this proceeding the detector concept of these upgrades is described, together with their physics motivations and R&D status and achievements.
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46

Nayak, Ranjit. „Kaon Isospin Fluctuations in ALICE at the LHC“. Proceedings 10, Nr. 1 (12.04.2019): 22. http://dx.doi.org/10.3390/proceedings2019010022.

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The first measurements of isospin fluctuations in the kaon sector is presented in Pb-Pb collisions at s N N = 2.76 TeV. A robust statistical observable was used to extract the isospin fluctuations of neutral and charged kaons as a function of collision centrality. The results show a significant variation in the behaviour of ν d y n in data when compared to Monte-Carlo models such as HIJING and AMPT. The deviation from 1/n scaling in data indicates possible isospin fluctuation in the kaon sector in heavy ion collisions.
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Kamil Graczykowski, Łukasz. „Pion femtoscopy measurements in ALICE at the LHC“. EPJ Web of Conferences 71 (2014): 00051. http://dx.doi.org/10.1051/epjconf/20147100051.

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48

Collaboration, P. Crochet for the ALICE. „Heavy quark measurements with ALICE at the LHC“. Journal of Physics G: Nuclear and Particle Physics 28, Nr. 7 (10.06.2002): 1583–90. http://dx.doi.org/10.1088/0954-3899/28/7/309.

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49

Fabjan, C. W. „ALICE at the LHC: getting ready for physics“. Journal of Physics G: Nuclear and Particle Physics 35, Nr. 10 (17.09.2008): 104038. http://dx.doi.org/10.1088/0954-3899/35/10/104038.

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50

Romita, Rosa. „Λcanalysis with the ALICE detector at the LHC“. Journal of Physics: Conference Series 446 (19.09.2013): 012036. http://dx.doi.org/10.1088/1742-6596/446/1/012036.

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