The purpose of the Competence Center on Simulation and Big Data is the fostering of an effective collaboration between the different LIP groups working on these areas and to boost the capability to exploit the existing expertise both internally and externally, towards the university and the industry. The different LIP groups have a vast range of competences in data analysis and simulation tools, including physics models, Monte Carlo generators, detector simulation tools, big-data handling techniques and data mining. The ability to fully benefit from such competences requires achieving critical mass, a coordinated training program, the exploitation of synergies between groups and a clear identification of the key areas where we can contribute in a competitive way.
The competence center started its activities in 2017 and the first priorities were the identification of the technical competences mastered by the LIP members in these two areas, establishing communication and discussion forums, starting a training program and establishing an action plan for the next few years.
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Differentiable Vertex Fitting for Jet Flavour Tagging
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Author(s): Rachel E. C. Smith, Inês Ochoa, Rúben Inácio, Jonathan Shoemaker, Michael Kagan
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Submission: , Acceptance: , Publication: 2024-09-25
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Reference: PHYSICAL REVIEW D 110, 052010 (2024)
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Dataset for flavour tagging R&D
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Author(s): Inês Ochoa
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Submission: , Acceptance: , Publication: 2024-08-20
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Reference: zenodo.13350327
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Simulation-based inference in the search for CP violation in leptonic WH production
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Author(s): R. Barrué, P. Conde Muíño, V. Dao, R. Santos
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Submission: 2023-08-09, Acceptance: 2024-03-13, Publication: 2024-04-03
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Reference: J. High Energ. Phys. 2024, 14
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Jet substructure observables for jet quenching in Quark Gluon Plasma: a Machine Learning driven analysis
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Author(s): Miguel Crispim Romão, José Guilherme Milhano, Marco van Leeuwen
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Submission: 2023-04-14, Acceptance: 2023-12-21, Publication: 2024-01-18
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Reference: SciPost Phys. 16, 015 (2024)