PhD student
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Research activity

My research arises in the context of the precision era of Higgs physics from the recent high accuracy data at the Large Hadron Collider (LHC). With the data of an unprecedented level of precision, the theoretical error is now lag behind. In addition, the accurate theoretical prediction of Standard Model (SM) processes would also lead path to the discovery of new physics. Therefore the QCD radiation pattern is crucial to distinguish Standard Model physics from possible new physics signals. In this context, studies of the internal structure of jets, i.e. jet substructure, has proved a valuable addition to LHC phenomenology. Furthermore, in order to obtain the precise predictions, the jet substructure calculations usually involve resummation of the perturbative series, where large logarithms arise from the multi-scale hierarchy.

The aim of my research is to explore novel approachs to probe colour flow and soft substructure of jets,which is beyond the traditional borders of Perturbative Quantum Chromodynamics (pQCD), namely globalness and infrared & collinear (IRC) safety.  In particular, for the non-global case, a novel approach to solving differential equations using artificial neural networks is presented with a handful of evolution equations are solved as example, and compared with the other methods in the literature. In the context of IRC unsafe, first-principle calculation in resummed perturbation theory is performed, alone with the resummation formalism is reviewed and improved. As phenomenological applications, each ingredient is studied independently. Moreover, due to the large theoretical uncertainty of IRC unsafe observable, the result is improved with the IRC safe projection. Additionally, with the purpose of assess subleading colour correlations, the novel azimuthal asymmetry distribution is introduced and studied in some detail.

Main publications

Theory Predictions for the Pull Angle

A. J. Larkoski, S. Marzani and C. Wu, Phys. Rev. D 99, no. 9, 091502 (2019)

Safe Use of Jet Pull

A. J. Larkoski, S. Marzani and C. Wu, JHEP 2001, 104 (2020) doi:10.1007/JHEP01(2020)

Resummation of Non-Global Logarithms with neural network

S. Marzani, M . Spannowsky and C. Wu