YAM2: Yet another library for the $M_2$ variables using sequential quadratic programming
Abstract
The variables are devised to extend by promoting transverse masses to Lorentz-invariant ones and making explicit use of on-shell mass relations. Unlike simple kinematic variables such as the invariant mass of visible particles, where the variable definitions directly provide how to calculate them, the calculation of the variables is undertaken by employing numerical algorithms. Essentially, the calculation of corresponds to solving a constrained minimization problem in mathematical optimization, and various numerical methods exist for the task. We find that the sequential quadratic programming method performs very well for the calculation of , and its numerical performance is even better than the method implemented in the existing software package for . As a consequence of our study, we have developed and released yet another software library, YAM2, for calculating the variables using several numerical algorithms.
Cite
@article{arxiv.2007.15537,
title = {YAM2: Yet another library for the $M_2$ variables using sequential quadratic programming},
author = {Chan Beom Park},
journal= {arXiv preprint arXiv:2007.15537},
year = {2021}
}
Comments
1+22 pages, 5 figures; matches published version; fixed title page for inspire record; The library is distributed via https://github.com/cbpark/YAM2