# Input Comparison of Radiogenic Neutron Estimates for Ultra-low   Background Experiments

**Authors:** J. Cooley, K.J. Palladino, H. Qiu, M. Selvi, S. Scorza, C. Zhang

arXiv: 1705.04736 · 2018-03-14

## TL;DR

This study compares two software packages for estimating radiogenic neutron backgrounds in ultra-low-background experiments, highlighting differences in yields and spectra but confirming their suitability for background modeling.

## Contribution

It provides a detailed comparison of Mei-Zhang-Hime and SOURCES-4A codes for neutron background estimation in rare event physics experiments.

## Key findings

- Neutron yield differences up to 50% between codes
- No systematic bias found between the two software packages
- Both tools meet the requirements of low-background experiments

## Abstract

Ultra-low-background experiments address some of the most important open questions in particle physics, cosmology and astrophysics: the nature of dark matter, whether the neutrino is its own antiparticle, and does the proton decay. These rare event searches require well-understood and minimized backgrounds. Simulations are used to understand backgrounds caused by naturally occurring radioactivity in the rock and in every piece of shielding and detector material used in these experiments. Most important are processes like spontaneous fission and ({\alpha},n) reactions in material close to the detectors that can produce neutrons. A comparison study between two dedicated software packages is detailed. The cross section libraries, neutron yields, and spectra from the Mei-Zhang-Hime and the SOURCES-4A codes are presented. The resultant yields and spectra are used as inputs to direct dark matter detector toy models in GEANT4, to study the impact of their differences on background estimates and fits. Although differences in neutron yield calculations up to 50% were seen, there was no systematic difference between the Mei-Hime-Zhang and SOURCES-4A results. Neutron propagation simulations smooth differences in spectral shape and yield, and both tools were found to meet the broad requirements of the low-background community.

## Full text

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## Figures

7 figures with captions in the complete paper: https://tomesphere.com/paper/1705.04736/full.md

## References

22 references — full list in the complete paper: https://tomesphere.com/paper/1705.04736/full.md

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Source: https://tomesphere.com/paper/1705.04736