We present a neutral particle reconstruction algorithm based on a neural network approach applied to the E687 hadron calorimeter. A measurement of the invariant mass of the Σ± → nπ± is presented to verify the reliability of the reconstruction. The reconstructed invariant mass of the charmed meson D+ → KL0π+π+π− is also presented to show the possible application of this technique to charmed particles decaying into a neutral hadron. An example of this would be Λc+ → nK−π+π+.
Neural network based neutral particles reconstruction with the E687 hadron calorimeter / V. Arena, G. Boca, G. Bonomi, G. Gérard, G. Gianini, M. Marchesotti, M. Merlo, S.P. Ratti, C. Riccardi, L. Viola, P. Vitulo, D. Buchholz, D. Claes, B. O'Reilly. - In: NUCLEAR INSTRUMENTS & METHODS IN PHYSICS RESEARCH. SECTION A, ACCELERATORS, SPECTROMETERS, DETECTORS AND ASSOCIATED EQUIPMENT. - ISSN 0168-9002. - 374:3(1996), pp. 359-366.
Neural network based neutral particles reconstruction with the E687 hadron calorimeter
G. Gianini;
1996
Abstract
We present a neutral particle reconstruction algorithm based on a neural network approach applied to the E687 hadron calorimeter. A measurement of the invariant mass of the Σ± → nπ± is presented to verify the reliability of the reconstruction. The reconstructed invariant mass of the charmed meson D+ → KL0π+π+π− is also presented to show the possible application of this technique to charmed particles decaying into a neutral hadron. An example of this would be Λc+ → nK−π+π+.
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