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arXiv · 2609.32633

GEM: An implementation of the ghost-Gutzwiller approximation for simulating interacting quantum systems

Samuele Giuli·Tsung-Han Lee·Yong-Xin Yao·Ina Park·Harrison LaBollita·Ivan Pasqua·Nicola Lanatà·Olivier Gingras
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Abstract

We present GEM (Ghost Embedding Method) from the title here, 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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Samuele Giuli, Tsung-Han Lee, Yong-Xin Yao, Ina Park, Harrison LaBollita, Ivan Pasqua, Nicola Lanatà, Olivier Gingras. 2026-09-26. GEM: An implementation of the ghost-Gutzwiller approximation for simulating interacting quantum systems. https://arxiv.org/abs/2609.32633

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