w2dynamics is a hybridization-expansion continuous-time quantum Monte Carlo package, developed jointly in Wien and Würzburg.

In any published papers arising from the use of w2dynamics, please cite:

M. Wallerberger, A. Hausoel, P. Gunacker, A. Kowalski, N. Parragh, F. Goth, K. Held, and G. Sangiovanni,
Comput. Phys. Commun. 235, 2 (2019)
https://www.sciencedirect.com/science/article/pii/S0010465518303217
arXiv:1801.10209 https://arxiv.org/abs/1801.10209
When using additional codes in conjunction with w2dynamics, do not forget to give credit to them as well.

w2dynamics contains:

• a multi-orbital quantum impurity solver for the Anderson impurity model
• dynamical mean field theory self-consistency loop,
• a maximum-entropy analytic continuation, as well as
• coupling to density functional theory.

The w2dynamics package allows for calculating one- and two-particle quantities; it includes worm and further novel sampling schemes. Details about its download, installation, functioning and the relevant parameters are provided.

Maintainers and principal authors:

• Markus Wallerberger
• Andreas Hausoel
• Patrik Gunacker
• Alexander Kowalski
• Nicolaus Parragh
• Florian Goth
• Karsten Held
• Giorgio Sangiovanni

Requirements:

• Python (>= 2.6)
• Fortran 90 compiler, e.g. GCC
• C++11 compiler, e.g. GCC
• CMake (>= 3.18)
• BLAS, ideally an optimized version as provided e.g. by OpenBLAS or Intel MKL
• LAPACK, ideally an optimized version as provided e.g. by OpenBLAS or Intel MKL

Further dependencies (automatically installed if not found):

• Python packages: numpy >= 1.10, scipy >= 0.10, h5py, mpi4py, configobj
• NFFT3 (for automatic building, its dependency FFTW3 is required)
• HDF5 (as a dependency of h5py)

To get the code use git:

$ git clone https://github.com/w2dynamics/w2dynamics.git

To build the code follow the cmake build model:

$ mkdir build
$ cd build
$ cmake .. [FURTHER_FLAGS_GO_HERE]
$ make

If CMake fails to find some native dependency automatically, command line arguments of the form -D<PACKAGE>_ROOT=/path/to/package/ can usually be used to explicitly specify installation prefixes that should be searched, for example -DNFFT_ROOT=/path/to/nfft/ for NFFT. For the Python packages, you should try to ensure that they can be imported in the interpreter used by CMake. CMake can be instructed to use a specific interpreter executable using -DPYTHON_EXECUTABLE=/path/to/python. Consider especially that if a Python 3 installation is found automatically, it will be preferred to a Python 2 installation.

To run the unit tests (optional), run the following in the build directory:

$ make test

To install the code (optional), run the following in the build directory:

$ cmake .. -DCMAKE_INSTALL_PREFIX=/path/to/prefix
$ make install

For example installation instructions for some operating systems and computing clusters, you can also visit our wiki page on installation.

First, prepare a parameter file, which is usually named Parameters.in. You can use the input files for the tutorials on our wiki as templates.

Next, run DMFT.py to use the self-consistency loop or cthyb if you do a single-shot calculation. If you have installed the code (see above), both executables should be placed in your path. If your parameter file is not named Parameters.in or does not lie in your current working directory, you have to specify it explicitly as a command line argument. If you want to run your calculation using MPI parallelization, use mpiexec or similar to execute the script.

$ DMFT.py [Parameters.in]
$ cthyb [Parameters.in]
$ mpiexec -n 10 DMFT.py [Parameters.in]
$ mpiexec -n 10 cthyb [Parameters.in]

The code will produce a file with a name like RunIdentifier-Timestamp.hdf5. It is an archive of all quantities written by w2dynamics. You can navigate this file using any hdf5-compatible analysis tool, such as jupyter, matlab, etc. For your convenience, we have also included the tool hgrep, which allows quick analysis of the data:

$ hgrep [options] (file|latest) quantity [[index] ...]
$ hgrep latest siw 1 1 1 1

will print the self-energy on the Matsubara axis from the first iteration for the first inequality, orbital and spin as tabular data. Add option -p for automatic plotting or have a look at the man page hgrep.man or the examples in our tutorials for details.

• w2dyn/auxiliaries/: auxiliary python routines (in/output, config files, etc.)

• w2dyn/dmft/: python package for DMFT self-consistency loop

• w2dyn/maxent/: Python wrapper for maximum entropy analytic continuation

• clusters/: template submission scripts for different clusters

• cmake/: cmake custom modules

• docs/: documentation (github wiki)

• Postproc/: postprocessing scripts

• preproc/: preprocessing scripts

• src/: compiled modules loaded from python

  • ctqmc_fortran: Fortran 90 continuous-time quantum Monte Carlo solver
  • maxent: maximum entropy analytic continuation solver
  • mtrng: Mersenne twister pseudorandom number generator

• testsuite/: unit tests for the code

• cfg_converter.py: small script converting old-style config files

• completions.sh: file for bash completions

• cprun: convenience script copying input files to different directory

• DMFT.py: main entry point for DMFT self-consistency loop

• hgrep: utility for extracting data from HDF5 file

• Maxent.py: main entry point for maximum entropy code

• setup.py: Python installation script

If you use the w2dynamics package, please mention the following in the acknowledments:

The QMC simulations were carried out with the w2dynamics package available at https://github.com/w2dynamics/w2dynamics .

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