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A library to map particle records to the RMM

The Map2RMM is a library that translates particle records from collider experiments to the rapidity-mass matricies (RMM) for machine learning algorithms.

The motivation and the description of the Map2RMM library is "Imaging particle collision data for event classification using machine learning", S.Chekanov, arXiv:1805.11650 (NIMA 931 (2019) 92 (, ANL-HEP-144006).

A follow up of this method is described in: S.V.Chekanov, Machine learning using rapidity-mass matrices for event classification problems in HEP. ANL-HEP-147750.

A short progress report is presented in the talk "Machine learning for event classification and automated discovery of new physics at the LHC experiments", PS April Meeting 2019, April 13–16, 2019; Denver, Colorado (APR19/Session/T13.6)).

C++ code

The library can be downloaded from Git Map2RMM