High Energy Physics Seminars

Learning the likelihood with tree boosting for extracting EFT parameters

by Dr. Suman Chatterjee (HEPHY Vienna, Austria)

Thursday, December 8, 2022 from to (Asia/Kolkata)
at TIFR, Mumbai ( AG-66 )
Various extensions of the standard model of particle physics (SM) predict anomalous interactions at the weak scale. Effective field theory (EFT), a generalized extension of the SM, comprises all the possible operators of dimensions greater than four, satisfying the SM’s symmetries [1]. The EFT operators modify the production and decay kinematics of the particles involved in LHC collisions compared with those predicted by the SM. We have recently developed a tree boosting algorithm for collider measurements of multiple EFT-operator coefficients [2, 3]. The design of the discriminant exploits per-event information from the simulated data sets that encodes the predictions for different values of the coefficients. This “Boosted Information Tree” algorithm provides nearly optimal discrimination power order-by-order in the expansion of the EFT-operator coefficients and approaches the optimal likelihood ratio test-statistic. In this talk, we will discuss the algorithm and show its application to the Higgsstrahlung process for different types of modeling.