Backtracing of the Impact Parameter through Pattern Recognition Analysis on Heavy Ion Reaction Data

One of the problems in the analysis of nucleus‐nucleus collisions is to get information on the value of the impact parameter b through the knowledge of some features of each event. The experimental values of Z, transverse energy and multiplicity of fragments are good candidates to get hints on the values of b. Motivated by this consideration, this work consists in the application of pattern recognition techniques aimed at associating values of b to groups of events. To this end, a support vector machine (SVM) classifier is adopted to analyze multifragmentation reactions. This analysis consists of mainly two different steps. In the first one, known as the training phase, SVM learns how to discriminate between peripheral, semi‐peripheral and central reactions. These examples are taken from a large number of events generated with classical molecular dynamics (CMD) and heavy ion phase‐space exploration (HIPSE) models for each value of b. In the second one, known as the test phase, what has been learned is tested on new events generated by the same models. Our tests demonstrate that, by following this approach, central, semi‐peripheral and peripheral reactions are correctly classified for about 85% of the cases