Sparse grid utilities for IR and Chebyshev representations
Essential contents for a temperature-independent sparse grid
stats: Bose or Fermi statistics.xgrid: Real space grid points in $x \in (-1, 1)$.ngrid: Frequency space grid points in Matsubara indices $n$, such that $\omega_n = (2n+\zeta)\pi/\beta$.wgrid: Frequency space grid points assuming $\beta=1$.uxl: Transformation matrix from the basis representationlto real space grid pointsx.ulx: Inverse ofuxl.u1l_pos: Basis representation for $x=+1$.u1l_neg: Basis representation for $x=-1$.uwl: Transformation matrix from the basis representationlto frequency space grid pointsw.ulw: Inverse ofuwl.metadata: Group for representation-depend information, for example:- For Chebyshev:
ncoefffor maximum number of coefficients. - For IR:
lambdafor dimensionless cutoff $\Lambda$,ncoefffor maximum number of coefficients.
- For Chebyshev:
Directory structure
python/sparse_grid/: python code for generating and parsing sparse grid data.python/sparse_grid/ir/: IR-specific code.python/sparse_grid/chebyshev/: Chebyshev-specific code.python/sparse_grid/repn.py: Common module interface for representations.python/generate.py: Script for generating HDF5 archives.
c++/: C++ interface for loading and representing sparse grid data.green/grids/: Public headers.
data/: Pre-generated data files.examples: Usage examples.
Dependencies
- Python:
sparse-irnumpy,scipy,h5py, andmpmath.
- C++:
- Green/h5pp: for compatibility with h5py
- Green/ndarrays: for compatibility with numpy.ndarray
- Green/params: for command-line parameters
- CMake: Version 3.27 or later
Installation
C++ installation uses CMake in a straightforward manner:
mkdir build && cd build
cmake .. -DCMAKE_INSTALL_PREFIX=.
make -j 4
make install
make test # Test the code
The Python package for green-grids can be installed using PyPI:
pip install green-grids
or simply by building from source as:
git clone https://github.com/Green-Phys/green-grids
cd green-grids
pip install .
Acknowledgements
This work is supported by National Science Foundation under the award CSSI-2310582
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