GEM: An implementation of the ghost-Gutzwiller approximation for simulating interacting quantum systems
Abstract
We present GEM (Ghost Embedding Method), an open-source software package written in Python for computing equilibrium properties of strongly correlated electronic systems within the ghost-Gutzwiller approximation method. GEM provides a computationally efficient framework for studying multi-orbital lattice models. It supports zero- and finite-temperature calculations and symmetry broken phases. It is integrated with the TRIQS ecosystem, providing tools for model construction, self-consistent solution, and evaluation of physical observables. We first detail the method's theoretical formulation, then we present the software architecture, and finally we introduce some practical workflow, which also validates the implementation against established results. In particular, we illustrate the capabilities of GEM through multiorbital and finite-temperature applications and discuss its computational cost relative to more demanding quantum embedding approaches.
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BibTeX
@misc{giuli2026implementation,
title = {{GEM: An implementation of the ghost-Gutzwiller approximation for simulating interacting quantum systems}},
author = {Samuele Giuli and Tsung-Han Lee and Yong-Xin Yao and Ina Park and Harrison LaBollita and Ivan Pasqua and Nils Wentzell and Nicola Lanatà and Olivier Gingras},
howpublished = {arXiv},
year = {2026},
month = oct,
doi = {10.48550/arxiv.2609.32633},
eprint = {2609.32633},
archivePrefix = {arXiv},
url = {https://arxiv.org/abs/2609.32633},
note = {CC BY 4.0},
}
RIS
TY - UNPB
TI - GEM: An implementation of the ghost-Gutzwiller approximation for simulating interacting quantum systems
AU - Samuele Giuli
AU - Tsung-Han Lee
AU - Yong-Xin Yao
AU - Ina Park
AU - Harrison LaBollita
AU - Ivan Pasqua
AU - Nils Wentzell
AU - Nicola Lanatà
AU - Olivier Gingras
PY - 2026
DA - 2026/10/13
PB - arXiv
DO - 10.48550/arxiv.2609.32633
UR - https://arxiv.org/abs/2609.32633
AB - We present GEM (Ghost Embedding Method), an open-source software package written in Python for computing equilibrium properties of strongly correlated electronic systems within the ghost-Gutzwiller approximation method. GEM provides a computationally efficient framework for studying multi-orbital lattice models. It supports zero- and finite-temperature calculations and symmetry broken phases. It is integrated with the TRIQS ecosystem, providing tools for model construction, self-consistent solution, and evaluation of physical observables. We first detail the method's theoretical formulation, then we present the software architecture, and finally we introduce some practical workflow, which also validates the implementation against established results. In particular, we illustrate the capabilities of GEM through multiorbital and finite-temperature applications and discuss its computational cost relative to more demanding quantum embedding approaches.
ER -