Studying differential cross section for elastic proton scattering by a tensor model

Previous studies have shown the reliability of the Bayesian Gaussian CANDECOMP/PARAFAC tensor decom-position (BGCP) algorithm in predicting the independent fission yields and evaluating global uncertainty of the data. This work proposes to apply the BGCP algorithm for the purpose of predicting and evaluating the differential cross section for elastic proton scattering. The tensor model is developed by training with the experimental data of elastic proton scattering from the EXFOR database. The Root Mean Square Error is used to evaluate the experimental data and search for potential errors and omissions in EXFOR, in order to identify outlying data of 98Mo, 100Mo, 144Sm and 209Bi. After the revision for the outlying data in EXFOR, the reproduced values for 144Sm are compared with the remaining controversial entries. Besides, the predicted data for 9C are compared with the published data not available in EXFOR. The results demonstrate that the tensor model can make reasonable predictions and has a role to play in evaluating the quality of elastic proton scattering data. The tensor model may become a powerful tool for nuclear data evaluation in EXFOR.

Automated summary

This study proposes the use of the BGCP algorithm to predict and evaluate the differential cross section for elastic proton scattering. A tensor model is developed using experimental data from the EXFOR database. After revising the outlying data in EXFOR, the tensor model is used to compare predicted values and controversial entries. The results demonstrate the reasonable predictions and quality evaluation capabilities of the tensor model in elastic proton scattering data.