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28 result(s) for "Data Analysis, Statistics and Probability (physics.data-an)"
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Learning probability distributions from smooth observables and the maximum entropy principle: some remarks
The maximum entropy principle (MEP) is a very useful working hypothesis in a wide variety of inference problems, ranging from biological to engineering tasks. To better understand the reasons of the success of MEP, we propose a statistical-mechanical formulation to treat the space of probability distributions constrained by the measures of (experimental) observables. In this paper we first review the results of a detailed analysis of the simplest case of randomly chosen observables. In addition, we investigate by numerical and analytical means the case of smooth observables, which is of practical relevance. Our preliminary results are presented and discussed with respect to the efficiency of the MEP.
Improving nuclear data accuracy of 241Am and 237Np capture cross sections
In the framework of the OECD/NEA WPEC subgroup 41, ways to improve neutron induced capture cross sections for 241Am and 237Np are being sought. Decay data, energy dependent cross section data and neutron spectrum averaged data are important for that purpose and were investigated. New time-of-flight measurements were performed and analyzed, and considerable effort was put into development of methods for analysis of spectrum averaged data and re-analysis of existing experimental data.