Adiabatic-Inspired Hybrid Quantum-Classical Methods for Molecular Ground State Preparation
Sean Thrasher, Ioannis Kolotouros, Julien Michel, and Petros Wallden

TL;DR
This paper introduces a new hybrid quantum-classical algorithm inspired by adiabatic processes for more efficient molecular ground state preparation, benchmarking it against existing methods and demonstrating its advantages in quantum chemistry applications.
Contribution
The paper presents a novel G-AQC-PQC hybrid algorithm that combines adiabatic-inspired initialization with classical optimization, improving efficiency over traditional VQE methods.
Findings
G-AQC-PQC outperforms conventional VQE in accuracy.
Adiabatically-inspired methods show advantages in near-term quantum chemistry.
The framework unifies existing adiabatic-inspired quantum algorithms.
Abstract
Quantum computing promises to efficiently and accurately solve many important problems in quantum chemistry which elude classical solvers, such as the electronic structure problem of highly correlated materials. Two leading methods in solving the ground state problem are the Variational Quantum Eigensolver (VQE) and Adiabatic Quantum Computing (AQC) algorithms. VQE often struggles with convergence due to the energy landscape being highly non-convex and the existence of barren plateaux, and implementing AQC is beyond the capabilities of current quantum devices as it requires deep circuits. Adiabatically-inspired algorithms aim to fill this gap. In this paper, we first present a unifying framework for these algorithms and then benchmark the following methods: the Adiabatically Assisted VQE (AAVQE) (Garcia-Saez and Latorre (2018)), the Variational Adiabatic Quantum Computing (VAQC)…
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Taxonomy
TopicsQuantum Computing Algorithms and Architecture · Spectroscopy and Quantum Chemical Studies · Machine Learning in Materials Science
