An evolutionary strategy for DeltaE - E identification
Instrumentation and Detectors
2017-10-04 v2 Neural and Evolutionary Computing
Nuclear Experiment
Abstract
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.
Cite
@article{arxiv.1705.08380,
title = {An evolutionary strategy for DeltaE - E identification},
author = {Katarzyna Schmidt and Oskar Wyszynski},
journal= {arXiv preprint arXiv:1705.08380},
year = {2017}
}