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Green/Continuation is an Analytical continuation toolkit for Green Software Package

Installation

Green/Continuation comes in two forms

  • C++ application
  • Python package

Dependencies

Green/Continuation has the following required external dependencies

  • HDF5 library version >= 1.10.2
  • Message Passing Interface >= 3.1 (for C++ application)
  • Eigen3 library >= 3.4.0
  • GNU Multiprecision library
  • pybind11 (optional to build python wrapper)

To build Green/Continuation CMake version 3.18 or above is required

Build and Install C++ application

The following example will build, test and install Green/Continuation to /path/to/weakcoupling/install/dir directory.

$ git clone https://github.com/Green-Phys/green-ac
$ cd green-ac
$ mkdir build && cd build
$ cmake -DCMAKE_BUILD_TYPE=Release \
        -DCMAKE_INSTALL_PREFIX=/path/to/install/dir ..
$ make
$ make test
$ make install

Installation of Python package

We provide pre-built binaries for major Linux distributions and recent MacOS version via pip. For installation using pip simply type pip install green-ac. If pre-built binaries can not be used, package will be built from sources.

Usage

C++ application

After the Green/Continuation is built and installed, spectral function could be obtained by calling

<install dir>/bin/ac.exe  --BETA <Inverse temperature> --grid_file <grid file>    \
   --input_file <input file> --output_file <output file> --group <HDF5 group with data> \
   --e_min -5.0 --e_max 5.0 --n_omega 4000 --eta 0.01 \
   --kind Nevanlinna
  • BETA -- the inverse temperature that was used to obtain results
  • grid_file -- name of the grid file that was used to obtain results
  • input_file -- name of the file that contains imaginary time data
  • output_file -- name of the file to store results of the continuation
  • group -- name of the group that contains data and mesh datasets with imaginary time data and grid
  • e_min -- lowest frequency on the real axis
  • e_max -- largest frequency on the real axis
  • n_omega -- number of frequency points on the real axis
  • eta -- broadening parameter
  • kind -- type of continuation to be used (current version only supports Nevanlinna)

After the completetion, results will be stored in group HDF5 group in the output_file file.

Python

In addition to C++ application, Green/Continuation provides a convinient Python package that can work directly with numpy arrays. It supports two types of parallelism, using ProcessPoolExecutor from concurrent.futures and MPI parallelization using mpi4py library.

To use Green/Continuation simply import it in your script as

import green_ac

and call solve function with the following parameters:

  • Type of the continuation (currently we only provide Nevanlinna)
  • Matsubara frequency grid
  • Real frequency grid
  • Data in Matsubara frequency domain
  • Precision

Here is an example how to obtain real frequency Green's function for a simple two-pole non-interacting Green's function with precision at least 512 bits:

imgrid = (2*np.linspace(-50,49,100) + 1) * 1.j *np.pi/ 2
grid = np.linspace(-2,2,1001) + 0.01j
data = 0.5*(1/(imgrid + 0.5) + 1/(imgrid - 0.5))
data_out = green_ac.solve("Nevanlinna", imgrid, grid, data, 512)

Here we have 100 positive and negative Matsubara frequencies, define real frequency grid to have 1000 points and to be from -2 to 2 with broadening parameter 0.01, We define Green's function on Matsubara grid with poles at -0.5 and 0.5. Real frequency data will be stored in data_out array.

Acknowledgements

This work is supported by National Science Foundation under the award OCA-2310582

Project links

Data verified by PyPI on Jul 7, 2026
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Owner

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1 maintainer

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Avatar for gauravharsha from gravatar.com gauravharsha

Credits

Author: Sergei Iskakov

Maintainer: Gaurav Harsha

GitHub Statistics

Data verified by PyPI on Jul 7, 2026
The GitHub source repository was provided by the project maintainers and verified by PyPI at the time of upload. Stars, forks, and open issues/PRs are derived from that repository and have not been independently verified.

License

MIT License

Requires

Python >=3.8

Provides Extra

tests

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