Computing Challenges for the Einstein Telescope project

Conférence Chapitre d'actes Computing Challenges for the Einstein Telescope project eng 2024-05-06 2024 author Bagnasco Stefano INFN, Turin author Bozzi Antonella EGO, Pisa author Fragkos Anastasios 0000-0003-1474-1523 ISDC, Versoix 826418 Département d'astronomie (ASTRO) author Gonzalvez Alba Barcelona Supercomputing Ctr. author Hahn Steffen KIT, Karlsruhe, IKP author Hemming Gary EGO, Pisa author Lavezzi Lia INFN, Turin author Laycock Paul ISDC, Versoix 410527 Département d'astronomie (ASTRO) author Merino Gonzalo PIC, Bellaterra author Pardi Silvio INFN, Naples author Schramm Steven U. Geneva (main) 830747 Département de physique nucléaire et corpusculaire (FINUC) author Stahl Achim RWTH Aachen U. author Tanasijczuk Andres Cathol. U. Louvain (main) author Tonello Nadia KIT, Karlsruhe, IKP author Vallero Sara INFN, Turin author Veitch John Glasgow U. author Verdier Patrice IP2I, Lyon 04015 10.1051/epjconf/202429504015 https://www.epj-conferences.org/10.1051/epjconf/202429504015 The discovery of gravitational waves, first observed in September 2015 following the merger of a binary black hole system, has already revolutionised our understanding of the Universe. This was further enhanced in August 2017, when the coalescence of a binary neutron star system was observed both with gravitational waves and a variety of electromagnetic counterparts; this joint observation marked the beginning of gravitational multimessenger astronomy. The Einstein Telescope, a proposed next-generation ground-based gravitational-wave observatory, will dramatically increase the sensitivity to sources: the number of observations of gravitational waves is expected to increase from roughly 100 per year to roughly 100’000 per year, and signals may be visible for hours at a time, given the low frequency cutoff of the planned instrument. This increase in the number of observed events, and the duration with which they are observed, is hugely beneficial to the scientific goals of the community but poses a number of significant computing challenges. Moreover, the currently used computing algorithms do not scale to this new environment, both in terms of the amount of resources required and the speed with which each signal must be characterised. This contribution will discuss the Einstein Telescope's computing challenges, and the activities that are underway to prepare for them. Available computing resources and technologies will greatly evolve in the years ahead, and those working to develop the Einstein Telescope data analysis algorithms will need to take this into account. It will also be important to factor into the initial development of the experiment's computing model the availability of huge parallel HPC systems and ubiquitous Cloud computing; the design of the model will also, for the first time, include the environmental impact as one of the optimisation metrics. Black hole: binary: coalescence Neutron star: binary: coalescence Frequency: low Einstein Telescope Gravitational radiation Multimessenger Gravitation Radiation: electromagnetic Gravitational radiation detector: sensitivity Optimization Observatory Cloud Data analysis method Computer: hardware Dewey 520 Dewey 500.2 EPJ Web of Conferences 295 26 Département d'astronomie 12 34 Département de physique nucléaire et corpusculaire 132 false 26th International Conference on Computing in High Energy and Nuclear Physics (CHEP 2023) c9cf3d42-84de-4b52-bf4c-553c49dc9253 Proceedings chapter (Published version) Public Article_scientifique_from_unpaywall.pdf 2703623 application/pdf CC BY-4.0 4e89be26612b973d8545c15df6e16d2777df0db53bf490ba052fe0b2d3ae0288 openAccess Faculté des sciences / Département d'astronomie Faculté des sciences / Section de physique / Département de physique nucléaire et corpusculaire

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Computing Challenges for the Einstein Telescope project	26th International Conference on Computing in High Energy and Nuclear Physics (CHEP 2023)			2024	20	8

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Laycock, Paul