A Generic Random Number Generator Test Suite
Mario Ruetti, Matthias Troyer, Wesley P. Petersen

TL;DR
This paper introduces a comprehensive, extensible test suite for evaluating the quality of random number generators, emphasizing the need for application-based testing alongside statistical methods, especially for C++ implementations.
Contribution
It presents a new, generic test suite designed for C++ random number generators, addressing limitations of existing suites and supporting application-based testing.
Findings
The test suite effectively evaluates C++ random number generators.
It highlights the importance of application-based tests in generator assessment.
The suite is extensible and compatible with the revised C++ standard.
Abstract
The heart of every Monte Carlo simulation is a source of high quality random numbers and the generator has to be picked carefully. Since the ``Ferrenberg affair'' it is known to a broad community that statistical tests alone do not suffice to determine the quality of a generator, but also application-based tests are needed. With the inclusion of an extensible random number library and the definition of a generic interface into the revised C++ standard it will be important to have access to an extensive C++ random number test suite. Most currently available test suites are limited to a subset of tests are written in Fortran or C and cannot easily be used with the C++ random number generator library.
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Taxonomy
TopicsScientific Research and Discoveries · Computational Physics and Python Applications · Algorithms and Data Compression
