RECAST is an analysis reinterpretation framework; since analyses are often sensitive to a range of models, RECAST can be used to constrain the plethora of theoretical models without the significant investment required for a new analysis. However, experiment-specific full simulation is still computationally expensive. Thus, to facilitate rapid exploration, RECAST has been extended to truth-level reinterpretations, interfacing with existing systems such as RIVET.
Cite
@article{arxiv.1910.10289,
title = {Extending RECAST for Truth-Level Reinterpretations},
author = {Alex Schuy and Lukas Heinrich and Kyle Cranmer and Shih-Chieh Hsu},
journal= {arXiv preprint arXiv:1910.10289},
year = {2019}
}
Comments
Talk presented at the 2019 Meeting of the Division of Particles and Fields of the American Physical Society (DPF2019), July 29 - August 2, 2019, Northeastern University, Boston, C1907293