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gem - Ghost Embedding Method

Documentation docs

Disclaimer: This software is in beta stage. It is provided as-is, and no guarantee is made that it works for your use case or is free from bugs.

Use at your own risk and verify results independently.


Disclaimer: The software will have soon a paper associated to it. In the meantime, if you use it for your own research, please cite Ref. [1,2]

About

This is an implement of the ghost-Gutwiller approximation and its finate temperature extension [1,2] (ghost-GA).

Dependencies

Core

Package Purpose
numpy Array computing
scipy Sparse matrices, linear algebra, optimization
numba JIT compilation for ED basis construction
h5py HDF5 file I/O

Solvers (install only what you use)

Solver Extra packages required
SimpleED (none beyond core)

Testing

Package Purpose
pytest Test runner (make test)

Initial Setup

To install this package, run the following commands in order:

git clone https://github.com/TRIQS/gem.git

mkdir gem.build && cd gem.build

cmake ../gem

make
make test
make install

References

[1]: N. Lanatà, T.-H. Lee, Y.-X. Yao, and V. Dobrosavljević, Emergent Bloch excitations in Mott matter, Phys. Rev. B 96, 195126 (2017).

[2]: S. Giuli, T.-H. Lee, Y.-X. Yao, G. Kotliar, A. E. Ruckenstein, O. Gingras, and N. Lanatà, Unifying Variational and Dynamical Quantum Embedding: From Ghost Gutzwiller Approximation to Dynamical Mean-Field Theory


About

Ghost Gutzwiller Approximation implemented in TRIQS

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License

Unknown, GPL-3.0 licenses found

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Unknown
LICENSE.txt
GPL-3.0
COPYING.txt

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