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Apr 17 – 22, 2017
UZ Obergurgl
Europe/Zurich timezone

Accelerating the BSM interpretation of LHC data with machine learning

Not scheduled
UZ Obergurgl

UZ Obergurgl

University Center Obergurgl Gaisbergweg 5 6456 Obergurgl Austria
Afternoon Session Physics Beyond the Standard Model Wednesday Afternoon


Sebastian Liem (GRAPPA, University of Amsterdam)


The interpretation of Large Hadron Collider (LHC) data in the framework of Beyond the Standard Model (BSM) theories is hampered by the need to run computationally expensive event generators and detector simulators. Performing statistically convergent scans of high-dimensional BSM theories is consequently challenging, and in practice unfeasible for very high-dimensional BSM theories. We have applied machine learning methods to accelerates the interpretation of LHC data, by learning the relationship between BSM theory parameters and data. The new approach makes it possible to rapidly and accurately reconstruct the theory parameters of complex BSM theories, should an excess in the data be discovered at the LHC.

Primary authors

Gianfranco Bertone Dr Marc Deisenroth Jong Soo Kim (IFT Madrid) Sebastian Liem (GRAPPA, University of Amsterdam) Prof. Max Welling Roberto Ruiz De Austri (IFIC)

Presentation materials

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