Published July 2005
| Version v1
Journal article
Neural network classification of gamma-ray bursts
- 1. Barcelona Univ., Barcelona (Spain). Departament d'astronomia i meterologia
- 2. Max-Planck-Instuitut fur Astrophysik, Garching (Germany)
- 3. Institut d'estudis espacials de Catalunya, Barcelona (Spain)
Description
From a cluster analysis it appeared that a three-class classification of GRBs could be preferable to just the classic separation of short/hard and long/soft GRBs (Balastegui A., Ruiz-Lapuente, P. and Canal, R. MNRAS 328 (2001) 283). A new classification of GRBs obtained via a neural network is presented, with a short/hard class, an intermediate-duration/soft class, and a long/soft class, the latter being a brighter and more inhomogeneous class than the intermediate duration one. A possible physical meaning of this new classification is also outlined
Availability note (English)
Also avalaible from: http://dx.doi.org/10.1393/ncc/i2005-10157-6Additional details
Identifiers
Publishing Information
- Journal Title
- Nuovo Cimento della Societa Italiana di Fisica. C, Geophysics and Space Physics
- Journal Volume
- 28C
- Journal Issue
- 4-5
- Journal Page Range
- p. 801-804
- ISSN
- 1124-1896
INIS
- Country of Publication
- Italy
- Country of Input or Organization
- Italy
- INIS RN
- 37047535
- Subject category
- S73: NUCLEAR PHYSICS AND RADIATION PHYSICS;
- Descriptors DEI
- CLASSIFICATION; COSMIC GAMMA BURSTS; COSMIC GAMMA SOURCES; MULTIVARIATE ANALYSIS; NEURAL NETWORKS
- Descriptors DEC
- COSMIC RADIATION; COSMIC RAY SOURCES; IONIZING RADIATIONS; MATHEMATICS; PRIMARY COSMIC RADIATION; RADIATIONS; STATISTICS