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The Extreme Light Infrastructure-Nuclear Physics (ELI-NP) facility, under construction in Magurele near Bucharest in Romania, will provide high-intensity and high-resolution gamma ray beams that can be used to address hotly debated problems in nuclear astrophysics, such as the accurate measurements of the cross sections of the 24Mg(γ,α)20Ne reaction, that is fundamental to determine the effective rate of 28Si destruction right before the core collapse and the subsequent supernova explosion. For this purpose, a silicon strip detector array (named ELISSA, acronym for Extreme Light Infrastructure Silicon Strip Array) will be realized in a common effort by ELI-NP and Laboratori Nazionali del Sud (INFN-LNS), in order to measure excitation functions and angular distributions over a wide energy and angular range. A prototype of ELISSA was built and tested at INFN-LNS in Catania (Italy) with the support of ELI-NP. In this occasion, we have carried out experiments with alpha sources and with a 11 MeV 7Li beam. Thanks to our approach, the first results of those tests show up a very good energy resolution (better than 1%) and very good position resolution, of the order of 1 mm. Moreover, a threshold of 150 keV can be easily achieved with no cooling.

This paper is concerned with the automatic analysis of data coming from the multidetector array CHIMERA, used in nuclear physics at intermediate energies. Each of Chimera's detection cells is a telescope made of a [DELTA]E silicon detector and a CsI(Tl) crystal, thick enough to stop all the charged light particles. The signals produced in the CsI(Tl) scintillators can be subdivided into two components--Fast and Slow. These data are collected in the form of bi-dimensional matrices (Fast-Slow matrices), particularly important for light particle identification. The proposed approach consists in applying image processing techniques. In particular, Grossberg's pre-attentive neural networks are used as a first step in order to isolate the regions of physical interest in the matrices and to roughly identify the directions depicted by the most intense lines; a successive step of filtering based on Markov random fields is then performed. Index Terms--Clustering methods, image processing, nuclear measurements, visualization.

We have built and tested a computational unit for on-line processing of special algorithms to be embedded in the central processing unit VERSAmodule Eurocard (CPU VME)-crate of the CHIMERA data acquisition system. The computational unit consists of a number of VME digital signal processor (DSP)-based commercial boards delivering 720 MFlops/board. Index Terms--Data acquisition (DAQ), digital signal processor (DSP), on-line computation.

The CHIMERA 4[pi] detector trigger system is described. The trigger decisions are based on a combination of geometrical multiplicity of detected particles and other logic signals. The trigger can manage the buffer memory of the used analog to digital converters. This allows performance of parallel data conversion and readout and substantial improvement of the acquisition system dead-time performances. The trigger module generates all the necessary gate signals for the converters and the control signals necessary to synchronize the readout. It also allows the remote control of the whole system. Index Terms--4[pi] detector, data acquisition, dead time, parallel readout, trigger system.

In nuclear physics at intermediate energies, the use of multidetector arrays consisting of thousands of detectors is customary. This paper presents a novel approach to the automatic classification of data collected by the 4[Pi] detector CHIMERA, constituted by 1192 telescopes of a thin silicon transparent detector coupled to a thick CsI(TI) scintillator. The method is based on spatial density data processing and produces frequency distributions of the most significant physical parameters. These one-dimensional spectra can be more easily analyzed than the standard two-dimensional scatter plots. With respect to manual or semiautomatic procedures, presently used for data analysis, our method offers the advantages of drastic time reduction and unbiased criteria for cluster identification. The proposed method can be successfully used in both off-line data analysis and multidetector stability control. Index Terms--Clustering methods, image processing, nuclear measurements, visualization.

Presents a novel approach to the automatic classification of data collection by the CHIMERA detector. Importance of data classification to nuclear physics measurement; Details on the semiautomatic system; Conclusion.