PoS - Proceedings of Science
Volume 390 - 40th International Conference on High Energy physics (ICHEP2020) - Parallel: Computing and Data Handling
MARTY: a new C++ framework for automated symbolic calculations in Beyond the Standard Model physics
G. Uhlrich*, F. Mahmoudi and A. Arbey
Full text: pdf
Pre-published on: February 24, 2021
Published on: April 15, 2021
Abstract
Theoretical calculations Beyond the Standard Model (BSM) constitute a challenge for high energy physicists, but are necessary when searching for New Physics. The predictions of a BSM scenario need to be compared with experimental data and the Standard Model values in order to identify the model that fits better what we observe in particle colliders. BSM predictions require very involved and error prone calculations of amplitudes, cross-sections and Wilson coefficients. Calculations at the one-loop level are often necessary for these quantities since some phenomenologically important processes may not occur at tree-level, such as Flavor Changing Neutral Currents (FCNC)in flavor physics that vanish at the tree-level. One-loop calculations have to be done analytically which is very time consuming and in practice rarely done for general BSM models. Here we present MARTY, a public and open-source C++ code.MARTY is the very first independent program able to calculate automatically amplitudes, squared amplitudes and Wilson coefficients at the one-loop level for general BSM models. This type of calculations requires a computer algebra system and could only be done, up to now, using Mathematica, a commercial and closed software for symbolic manipulations. MARTY does not rely on Mathematica since it re-implements its own computer algebra system also in C++, called CSL. MARTY will considerably ease BSM studies as by automating the analytical calculations the main task of the user would be the model building part. Once interfaced with other phenomenological codes in particle physics,MARTY will be incredibly efficient to make detailed predictions for general BSM models automatically.
DOI: https://doi.org/10.22323/1.390.0928
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