Implementations
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The ACFlow toolkit is developed with pure Julia language. Thanks to powerful type system and multiple dispatch paradigm of the Julia language, the seven different analytic continuation solvers are integrated into an united software architecture. Redundant codes are greatly reduced. It is quite easy to implement new analytic continuation solver or add new features to the existing solvers if necessary. Distributed computing is a built-in feature of Julia. So, it is straightforward to realize parallel calculations in the ACFlow toolkit. Now except for the MaxEnt, BarRat, and NevanAC solvers, all the other solvers are parallelized.
Code Repository
The official code repository of the ACFlow toolkit is:
https://github.com/huangli712/ACFlowCore Codes
The source codes of the ACFlow toolkit are placed in the acflow/src folder. Their functions are summarized in Table 1.
| Filename | Description |
|---|---|
ACFlow.jl | Entry of the ACFlow module. |
maxent.jl | Maximum entropy method. |
rfa.jl | Barycentric rational function approximation. |
nac.jl | Nevanlinna analytical continuation. |
sac.jl | Stochastic analytic continuation (K. S. D. Beach's algorithm). |
san.jl | Stochastic analytic continuation (A. W. Sandvik's algorithm). |
som.jl | Stochastic optimization method. |
spx.jl | Stochastic pole expansion. |
global.jl | Numerical and physical constants. |
types.jl | Basic data structures and computational parameters. |
base.jl | Driver for analytic continuation simulation. |
inout.jl | Read input data and write calculated results. |
config.jl | Parse configuration file and extract computational parameters. |
math.jl | Root finding, numerical integration, interpolation, Einstein summation, and curve fitting. |
util.jl | Some utility functions. |
mesh.jl | Meshes for spectral density. |
grid.jl | Grids for input data. |
model.jl | Default model functions. |
kernel.jl | Kernel functions. |
Table 1 | List of source codes of the ACFlow toolkit.
There are four more scripts in the acflow/util folder.
acrun.jl- It is used to launch the analytic continuation tasks sequentially.acprun.jl- It is used to launch the analytic continuation tasks parallelly.ppole.jl- It is used to postprocess the outputs by the StochPX solver.gmesh.jl-> It will generate a dynamical mesh for next analytic continuation simulation.
Documentation
The documentation of the ACFlow toolkit is written by using the Markdown language and the Documenter.jl package. The source codes are placed in the acflow/docs folder. The users can build documentation by themselves. Please see Installation for how to do that. Or they can read the latest documentation in the following website:
https://huangli712.github.io/projects/acflow/index.htmlTests and Examples
Forty-eight tests and four tutorials are also shipped with the ACFlow toolkit. The source codes for internal tests are placed in the acflow/test folder, while those for tutorials are saved in the acflow/tutor folder. See acflow/test/test.md and acflow/tutor/tutor.md for more details.
We also develop an individual package, namely ACTest, to benchmark various analytic continuation solvers or methods. Please check the following URL for more details:
https://github.com/huangli712/ACTest