Specialized numerical libraries help computational scientists develop simulations more efficiently, without having to “reinvent the wheel”. Diagrammatic Monte Carlo implementations are often specific to the system they were designed for and there are not many open source libraries available. One task that is common to all such simulations is the numerical sampling of different observables. Often one then needs to obtain a continuous smooth function from the discrete numerical data. Together with my collaborators we developed and publicly released the bin hierarchy method (BHM): an accurate, fast, and fully automatic tool to restore the maximally smooth function from a sampled histogram. With its general stand-alone implementation, the BHM library can be helpful for all research involving the sampling of smooth functions and can be easily used with existing code.
Check out our open source code on GitHub: