The possibility to discriminate between events with jets coming from quarks or gluons (quark-gluon tagging) can constitute a new tool to improve the sensitivity of some particular analyses. This study presents the implementation
of a discriminant to be used in quark-gluon tagging based upon neural networks without supervision, the so-called Self Organizing Maps (SOM). This method has been applied on the search for production of a particle that decays in a couple of Z bosons, with two leptons and two jets in its final state, using data recorded by the ATLAS experiment
