Analysis of Sileye-3/Alteino data with a neural network technique: Particle discrimination and energy reconstruction Original Research Article

In this work, we present the data analysis of the Sileye-3/Alteino experiment with neural network technique. Sileye-3/Alteino is composed of two devices: the cosmic ray-advanced silicon telescope (an 8 plane, 32 strip silicon detector) and an electroencephalograph. It was placed on board the ISS on April the 27th 2002 to investigate on the Light Flash phenomenon and the radiation environment in space. We show the possibility of using neural networks as an useful tool for real-time data analysis. A feed-forward neural network (Multi-Layer Perceptron – MLP) has been implemented and trained (with Monte Carlo data) to perform on line particle identification for ions with Atomic Number (Z) ⩽8 and incident kinetic energy reconstruction for ions Z > 2. The result of the analysis of Sileye-3/Alteino real data with the neural network and the improvements over classical analysis techniques are discussed.