| Zugriffsnummer | 18473 |
| Dokumenttyp | Konferenzartikel in Zeitschrift |
| Sprache | Englisch |
| Titel | Bayesian reconstruction of nanodosimetric cluster distributions at 100% detection efficiency |
| Autor(in); Institution |
De Nardo, L.; University of Padova, Physics Department, Padova, ITALY; INFN, Laboratori Nazionali di Legnaro, Legnaro, ITALY
Canella, S.; INFN, Laboratori Nazionali di Legnaro, Legnaro, ITALY
Großwendt, Bernd; 6.6, Grundlagen der Dosimetrie, PTB-Braunschweig
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| Quelle/Jahr | Microdosimetry : proceedings of the 14th International Symposium on Microdosimetry. Radiation Protection Dosimetry: 122 (2006), 1/4, 432 - 436 |
| ISSN | 0144-8420 |
| ISBN | 978-0-19-923171-3 |
| DOI | |
| Verlag | Oxford: Oxford University Press |
| Konferenzangaben | 14th International Symposium on Microdosimetry, Venice, 13-18, November, 2005, Italy |
| Freie Schlagworte | Nanodosimetry ; Bayesian deconvolution ; Ionization cluster-size distributions ; Detection efficiencies |
| Zusammenfassung | Ionization measurements in nanometric simulated volumes at a given distance from a charged particle track make use of electron (or ion) gas detectors, having non-uniformly distributed detecting efficiency. Due to the inefficiency of the detector, the spectra obtained by such detectors should be properly processed in order to reconstruct the frequency distribution of clusters produced in the irradiated gas. Bayesian data analysis is particularly suited for this type of inverse problems. In a previous work we have applied a Bayesian unfolding to ionisation distributions due to 5.4 MeV α-particles in a 20 nm site obtained by Monte Carlo simulations, taking into account different detection efficiency conditions. We have demonstrated that, in the case of uniformly distributed efficiency, Bayesian analysis, with a proper choice of the prior distribution and of the number of points considered for the reconstruction, provides a valid tool for reconstructing the true ionisation distributions, well beyond the maximum measured cluster size. In the more realistic case of a non-uniform detection efficiency a method, also based on Bayes’ theorem, which makes use of a simplifying assumption about the possible repartition of the produced electron cluster in the sensitive volume (SV), provides a good estimation of the distributions due to α-particles passing outside the SV. In this work we will apply the same method to the distributions obtained by α-particles crossing the SV, taking into account the ionisation density profile of a particle track. |
