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Operational Experience and R&D results using the Google Cloud for High Energy Physics in the ATLAS experiment

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arxiv 2403.15873 v1 pith:XLGUHGCP submitted 2024-03-23 hep-ex

Fernando Barreiro Megino , Kaushik De , Johannes Elmsheuser , Alexei Klimentov , Mario Lassnig , Miles Euell , Nikolai Hartmann , Tadashi Maeno
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Verena Martinez Outschoorn Jay Ajitbhai Sandesara Dustin Sell
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classification hep-ex
keywords cloudatlascomputinggridinfrastructureanalysisdataexperiment
verification ladder T0 review T1 audit T2 compute T3 formal

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The ATLAS experiment at CERN relies on a worldwide distributed computing Grid infrastructure to support its physics program at the Large Hadron Collider. ATLAS has integrated cloud computing resources to complement its Grid infrastructure and conducted an R&D program on Google Cloud Platform. These initiatives leverage key features of commercial cloud providers: lightweight configuration and operation, elasticity and availability of diverse infrastructure. This paper examines the seamless integration of cloud computing services as a conventional Grid site within the ATLAS workflow management and data management systems, while also offering new setups for interactive, parallel analysis. It underscores pivotal results that enhance the on-site computing model and outlines several R&D projects that have benefited from large-scale, elastic resource provisioning models. Furthermore, this study discusses the impact of cloud-enabled R\&D projects in three domains: accelerators and AI/ML, ARM CPUs and columnar data analysis techniques.

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  1. Measurement of off-shell Higgs boson production in the $H^*\rightarrow ZZ\rightarrow 4\ell$ decay channel using a neural simulation-based inference technique in 13 TeV $pp$ collisions with the ATLAS detector

    hep-ex 2024-12 accept novelty 6.0 of 10

    Using neural simulation-based inference, ATLAS improves evidence for off-shell Higgs production in ZZ -> 4l to 2.5 sigma observed (1.3 sigma expected) and measures Gamma_H = 4.3 +2.7 -1.9 MeV.

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