Papers › YAM2: Yet another library for the M₂ variables using sequential quadratic programming

YAM2: Yet another library for the M₂ variables using sequential quadratic programming

30 Jul 2020arXiv:2007.15537links table onlyarchive 2025-07-28

Chan Beom Park

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The M₂ variables are devised to extend M_(T2) 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 M₂ variables is undertaken by employing numerical algorithms. Essentially, the calculation of M₂ 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 M₂, and its numerical performance is even better than the method implemented in the existing software package for M₂. As a consequence of our study, we have developed and released yet another software library, YAM2, for calculating the M₂ variables using several numerical algorithms.

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cbpark/YAM2 officialmentioned in papermentioned on GitHub report
cbpark/YAM2-analysis mentioned on GitHub report
hepkosmos/OptiMass mentioned on GitHub report

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