114 citations · 968 across the 47 of their papers we have counts for
48 papers
GEM: An implementation of the ghost-Gutzwiller approximation for simulating interacting quantum systems
Samuele Giuli, Tsung-Han Lee, Yong-Xin Yao +6
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…
Magnetic phases of the anisotropic triangular Hubbard model from the ghost-Gutzwiller approximation in the rotating spin-frame
Azin Kazemi-Moridani, Samuele Giuli, Tsung-Han Lee +4
We investigate the magnetic phase diagram of the half-filled Hubbard model on the anisotropic triangular lattice using the Gutzwiller approximation (GA) and its ghost generalizatio…
Unifying Variational and Dynamical Quantum Embedding: From Ghost Gutzwiller Approximation to Dynamical Mean-Field Theory
Samuele Giuli, Tsung-Han Lee, Yong-Xin Yao +4
Dynamical and variational frameworks have long been viewed as distinct paradigms. In particular, in quantum embedding (QE) frameworks, dynamical mean-field theory (DMFT) captures n…
Accelerating dynamical mean-field theory convergence by preconditioning with computationally cheaper quantum embedding methods
E. M. Makaresz, O. Gingras, Tsung-Han Lee +3
Dynamical mean-field theory (DMFT) is a cornerstone technique for studying strongly correlated electronic systems. However, each DMFT step is computationally demanding, and many it…
Linear Foundation Model for Quantum Embedding: Data-Driven Compression of the Ghost Gutzwiller Variational Space
Samuele Giuli, Hasanat Hasan, Benedikt Kloss +5
Simulations of quantum matter rely mainly on Kohn-Sham density functional theory (DFT), which often fails for strongly correlated systems. Quantum embedding (QE) theories address t…
Neural-Quantum-States Impurity Solver for Quantum Embedding Problems
Yinzhanghao Zhou, Tsung-Han Lee, Ao Chen +2
Neural quantum states (NQS) have emerged as a promising approach to solve second-quantized Hamiltonians, because of their scalability and flexibility. In this work, we design and b…