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Advancing global SMEFT fits in the LHC precision era

CORDIS · observation · Publication date unknown

ded in theoretical predictions, as they prescribe how different energy regimes are connected. Secondly, the research project aims to advance the design of optimal observables for global fits by using machine learning techniques, with the goal of maximising sensitivity to NP. Lastly, the ultimate objective of indirect searches is the identification of heavy new particles responsible for the modified interactions; the SMEFT is simply an intermediate step in this endeavour. I will provide the particle physics community with an open-source software that will interface with the output of global SMEFT fits and indicate which heavy particles are disfavoured by the data and which are still viable. The combination of my expertise in SMEFT analyses and collider phenomenology, along with the host institute's proficiency in advanced statistical methods, flavour physics, and UV matching, provides an ideal setting to successfully execute the proposed tasks and significantly advance indirect searches. Collider phenomenology, Effective Field Theory, Global fit, Machine-Learning

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recordType

award

status

SIGNED

region

EU

value

165312.96

unit

EUR