Heterogeneous catalysis plays a critical role in many industrial processes, including the
production of fuels, chemicals, and pharmaceuticals, and research to improve current …

High performance computing (HPC) is renowned for its capacity to tackle complex problems.
Meanwhile, quantum computing (QC) provides a potential way to accurately and efficiently …

Quantum embedding is an appealing route to fragment a large interacting quantum system
into several smaller auxiliary “cluster” problems to exploit the locality of the correlated …

The computational demand posed by applying multi-Slater determinant trials in phaseless
auxiliary-field quantum Monte Carlo methods (MSD-AFQMC) is particularly significant for …

Hydrogen has emerged as a promising energy source for low-carbon and sustainable
mobility purposes. However, its applications are still limited by modest conversion efficiency …

Numerous variational methods have been proposed for solving quantum many-body
systems, but they often face exponentially increasing computational complexity as the …

Theoretical descriptions of excited states of molecular systems in high-energy regimes are
crucial for supporting and driving many experimental efforts at light source facilities …

The neural-network quantum states (NNQS) method is rapidly emerging as a powerful tool
in quantum mechanisms. While significant advancements have been achieved in simulating …

Variational quantum eigensolver (VQE) has emerged as a promising method for
investigating ground state properties in quantum chemistry, materials science, and …

This article provides the first mathematical analysis of the Density Matrix Embedding Theory
(DMET) method. We prove that, under certain assumptions,(i) the exact ground-state density …