Neural networks for impact parameter determination
- Accurate impact parameter determination in a heavy-ion collision is crucial for almost all further analysis. We investigate the capabilities of an artificial neural network in that respect. First results show that the neural network is capable of improving the accuracy of the impact parameter determination based on observables such as the flow angle, the average directed inplane transverse momentum and the difference between transverse and longitudinal momenta. However, further investigations are necessary to discover the full potential of the neural network approach.
| Author: | Steffen A. BassORCiDGND, Arnd Bischoff, Christoph HartnackORCiD, Joachim MaruhnORCiDGND, Joachim ReinhardtGND, Horst StöckerORCiDGND, Walter GreinerGND |
|---|---|
| URN: | urn:nbn:de:hebis:30-27026 |
| Parent Title (German): | Journal of Physics G: Nuclear and particle physics |
| Publisher: | IOP Publishing |
| Document Type: | Article |
| Language: | English |
| Date of Publication (online): | 2006/05/24 |
| Year of first Publication: | 1994 |
| Publishing Institution: | Universitätsbibliothek Johann Christian Senckenberg |
| Release Date: | 2006/05/24 |
| Volume: | 20 |
| Page Number: | 6 |
| First Page: | L21 |
| Last Page: | L26 |
| HeBIS-PPN: | 192331256 |
| Institutes: | Physik / Physik |
| Dewey Decimal Classification: | 5 Naturwissenschaften und Mathematik / 53 Physik / 530 Physik |
| Licence (German): |  Deutsches Urheberrecht |
