Back to Search Start Over

Enhancement of hadron–electron discrimination in calorimeters by detection of the neutron component

Authors :
Adriani, O.
Bonechi, L.
Bongi, M.
Bottai, S.
Calamai, M.
Castellini, G.
D’Alessandro, R.
Grandi, M.
Papini, P.
Ricciarini, S.
Sguazzoni, G.
Sona, P.
Sorichetti, G.
Source :
Nuclear Instruments & Methods in Physics Research Section A. Feb2011, Vol. 628 Issue 1, p332-338. 7p.
Publication Year :
2011

Abstract

Abstract: In many physics experiments where calorimeters are employed, the requirement of an accurate energy measurement is accompanied by the requirement of very high hadron–electron discrimination power. Normally the latter requirement is achieved by designing a high-granularity detector with sufficient depth so that the showers can fully develop. This method has many drawbacks ranging from the high number of electronic channels to the high mass of the detector itself. Some of these drawbacks may in fact severely limit the deployment of such a detector in many experiments, most notably in space-based ones. Another method, proposed by our group and currently under investigation, relies on the use of scintillation detectors which are sensitive to the neutron component of the hadron showers. Here a review of the current status will be presented starting with the simulations performed both with GEANT4 and FLUKA. A small prototype detector has been built and has been tested in a high-energy pion/electron beam behind a “shallow” calorimeter. Results are encouraging and indicate that it is possible to enhance the discrimination power of an existing calorimeter by the addition of a small-mass neutron detector, thus paving the way for better performing astroparticle experiments. [ABSTRACT FROM AUTHOR]

Details

Language :
English
ISSN :
01689002
Volume :
628
Issue :
1
Database :
Academic Search Index
Journal :
Nuclear Instruments & Methods in Physics Research Section A
Publication Type :
Academic Journal
Accession number :
57514915
Full Text :
https://doi.org/10.1016/j.nima.2010.06.347