Monte Carlo C++ analysis tools

A library of analysis tools

Data analysis is a mandatory step in lattice QCD and to have an efficient, well tested library of tools is very important. Between 2014 and 2016, a quite basic but complete set of standard tools was developed in C++, in order of achieve good performance. Basic analysis of typical Monte Carlo data has been implementing using "Markov Chain Monte Carlo Simulations and Their Statistical Analysis" book by B.A.Berg and "Monte Carlo Methods in Statistical Physics" book by G.T.Barkema and M.E.J.Newman as reference. The main available features are the following.

• The calculation of mean, variance, skewness and kurtosis of a given set of correlated data, with a correct estimate of the correspondent statistical error using either the Jackknife or the bootstrap method.
• The multiple histogram method, also known as Ferrenberg-Swendsen reweighting, which has been implemented in a very general fashion and which has been recently extended in order to reweight observable probability distributions.

A couple of executables have been, then, written for the user, in order to comfortably use the tools offered. Clearly, you could use the code as external library for another project, but this might not be necessary.

Useful information

• The development is hosted on GitLab.
• Main changes between versions can be found in the CHANGELOG file.
• Authors are listed in order of contribution to the codebase (number of commits).
• Authors that contributed to this version since the previous one:
  • Alessandro Sciarra (ORCID 0000-0002-4608-1905)