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, consists of 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 of 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 in the EFT-operator coefficients and approaches the optimal likelihood ratio test statistic. In this talk, I will discuss the algorithm and show its application to the Higgsstrahlung process for different types of modeling.
References:
[1] B. Grzadkowski, M. Iskrzynski, M. Misiak and J. Rosiek, Dimension-Six Terms in the Standard Model Lagrangian, JHEP10 (2010) 085, arXiv:1008.4884.
[2] S. Chatterjee, N. Frohner, L. Lechner, R. Schoefbeck, D. Schwarz, Tree boosting for learning EFT parameters, Comput. Phys. Commun. 277 (2022) 108385, arXiv:2107.10859.
[3] S. Chatterjee, S. Roshap, R. Schoefbeck, D. Schwarz, Learning the EFT likelihood with tree boosting, arXiv:2205.12976.
