  The purpose of analytical continuation is to establish a real frequency
spectral representation of single-particle or two-particle correlation function
(such as Green's function, self-energy function, and dynamical
susceptibilities) from noisy data generated in finite temperature quantum Monte
Carlo simulations. It requires numerical solutions of a family of Fredholm
integral equations of the first kind, which is indeed a challenging task. In
this paper, an open source toolkit (dubbed ACFlow) for analytical continuation
of quantum Monte Carlo data is presented. We at first give a short introduction
to the analytical continuation problem. Next, three primary analytical
continuation algorithms, including maximum entropy method, stochastic
analytical continuation, and stochastic optimization method, as implemented in
this toolkit are reviewed. And then we elaborate major features, implementation
details, and basic usage of this toolkit. Finally, four representative examples
are shown to demonstrate usefulness and flexibility of the ACFlow toolkit.
