Regular Article

ARIADNE – a program estimating covariances in detail for neutron experiments

Los Alamos National Laboratory, Los Alamos, NM, USA

^* e-mail: dneudecker@lanl.gov

Received: 16 November 2017
Received in final form: 5 February 2018
Accepted: 4 May 2018
Published online: 14 November 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/B-VIII.0 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.