Ionisation spectra in nanometric volumes at a given distance from a charged particle track are obtained by using electron (or ion) gas detectors, having non-uniformly distributed detection efficiency. Therefore, such spectra should be properly processed in order to reconstruct the frequency distribution of clusters really produced in the detector gas. A Bayesian unfolding has been applied to ionisation distributions due to 5.4 MeV alpha particles in a 20-mn site obtained by Monte Carlo simulations, taking into account different detection efficiency conditions. It will be shown that Bayesian analysis provides a valid tool for reconstructing the true ionisation distributions, well beyond the maximum measured cluster size.

Bayesian reconstruction of nanodosimetric cluster distributions at 100% detection efficiency

DE NARDO, LAURA;
2006

Abstract

Ionisation spectra in nanometric volumes at a given distance from a charged particle track are obtained by using electron (or ion) gas detectors, having non-uniformly distributed detection efficiency. Therefore, such spectra should be properly processed in order to reconstruct the frequency distribution of clusters really produced in the detector gas. A Bayesian unfolding has been applied to ionisation distributions due to 5.4 MeV alpha particles in a 20-mn site obtained by Monte Carlo simulations, taking into account different detection efficiency conditions. It will be shown that Bayesian analysis provides a valid tool for reconstructing the true ionisation distributions, well beyond the maximum measured cluster size.
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Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/11577/152282
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