An evolutionary strategy for DeltaE - E identification
This work addresses a domain-specific challenge in nuclear physics for researchers analyzing heavy ion collision data, representing an incremental improvement through the application of an existing evolutionary strategy to a new model.
The authors tackled the problem of automatically identifying charge and mass of nuclear fragments from heavy ion collisions by developing a method that combines a generative model of DeltaE-E relations with a CMA-ES evolutionary strategy, achieving results on simulated labeled data.
In this article we present an automatic method for charge and mass identification of charged nuclear fragments produced in heavy ion collisions at intermediate energies. The algorithm combines a generative model of DeltaE - E relation and a Covariance Matrix Adaptation Evolutionary Strategy (CMA-ES). The CMA-ES is a stochastic and derivative-free method employed to search parameter space of the model by means of a fitness function. The article describes details of the method along with results of an application on simulated labeled data.