Data libraries as a collaborative tool across Monte Carlo codes

TL;DR

This paper reviews and validates various data libraries used in Monte Carlo simulations, emphasizing their importance as collaborative tools across different codes and fields.

Contribution

It provides a critical examination and validation of current data libraries, highlighting their role in enhancing Monte Carlo simulation accuracy.

Findings

Data libraries are crucial for Monte Carlo simulations.

Extensive validation against experimental data improves library reliability.

Current libraries vary in quality and completeness.

Abstract

The role of data libraries in Monte Carlo simulation is discussed. A number of data libraries currently in preparation are reviewed; their data are critically examined with respect to the state-of-the-art in the respective fields. Extensive tests with respect to experimental data have been performed for the validation of their content.