Iterative Bayesian Monte Carlo for nuclear data evaluation

Iterative Bayesian Monte Carlo for nuclear data evaluation

In this work, we explore the use of an iterative Bayesian Monte Carlo (iBMC) method for nuclear data evaluation within a TALYS Evaluated Nuclear Data Library (TENDL) framework. The goal is to probe the model and parameter space of the TALYS code system to find the optimal model and parameter sets th...

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Bibliographic Details
Main Authors: Alhassan, E. (Author), Ferroukhi, H. (Author), Hursin, M. (Author), Koning, A.J (Author), Rochman, D. (Author), Vasiliev, A. (Author)
Format: Article
Language:English
Published: Springer 2022
Subjects:
Adjustments
Bayesian calibration
Iterative Bayesian Monte Carlo (iBMC)
Model parameters
Nuclear data
Nuclear reaction models
TALYS
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