The python program ARIADNE is a tool developed for evaluators to estimate detailed uncertainties and covariances for experimental data in a consistent and efficient manner. Currently, it is designed to aid in the uncertainty quantification of prompt fission neutron spectra, and was employed to estimate experimental covariances for CIELO and ENDF/ evaluations. | ARIADNE a program estimating covariances in detail for neutron experiments EPJ Nuclear Sci. Technol. 4 34 2018 Nuclear Sciences D. Neudecker published by EDP Sciences 2018 amp Technologies https epjn 2018012 Available online at https REGULAR ARTICLE ARIADNE a program estimating covariances in detail for neutron experiments Denise Neudecker Los Alamos National Laboratory Los Alamos NM USA Received 16 November 2017 Received in final form 5 February 2018 Accepted 4 May 2018 Abstract. The python program ARIADNE is a tool developed for evaluators to estimate detailed uncertainties and covariances for experimental data in a consistent and efficient manner. Currently it is designed to aid in the uncertainty quantification of prompt fission neutron spectra and was employed to estimate experimental covariances for CIELO and ENDF evaluations. It provides a streamlined way to estimate detailed covariances by 1 implementing uncertainty quantification algorithms specific to the observables 2 defining input quantities for typically encountered uncertainty sources and correlation shapes and 3 automatically generating plots of data uncertainties and correlations GND formatted XML and plain text output files. Covariances of the same and between different datasets can be estimated and tools are provided to assemble a database of experimental data and covariances for an evaluation based on ARIADNE outputs. The underlying IPython notebook files can be easily stored including all assumptions on uncertainties leading to more reproducible inputs for nuclear data evaluations. Here the key inputs and outputs are shown along with a representative example for the current version of ARIADNE to illustrate its usability and to open a discussion on how it could address further needs of the nuclear data evaluation community. 1 Introduction partially in support of work for the IAEA coordinated research project on PFNS 4 and was subsequently used At the CW2017 .
