Related papers: Sparse Quantum State Preparation for Strongly Correlated Systems

Sparse Quantum State Preparation for Strongly Correlated Systems

URL: http://arxiv.org/abs/2311.03347v5
Date: Sat, 2 Mar 2024 07:11:43 GMT
Title: Sparse Quantum State Preparation for Strongly Correlated Systems
Authors: C. Feniou, O. Adjoua, B. Claudon, J. Zylberman, E. Giner, J.-P. Piquemal
Abstract summary: In principle, the encoding of the exponentially scaling many-electron wave function onto a linearly scaling qubit register offers a promising solution to overcome the limitations of traditional quantum chemistry methods. An essential requirement for ground state quantum algorithms to be practical is the initialisation of the qubits to a high-quality approximation of the sought-after ground state. Quantum State Preparation (QSP) allows the preparation of approximate eigenstates obtained from classical calculations, but it is frequently treated as an oracle in quantum information.
Score: 0.0
License: http://creativecommons.org/licenses/by/4.0/
Abstract: Quantum Computing allows, in principle, the encoding of the exponentially scaling many-electron wave function onto a linearly scaling qubit register, offering a promising solution to overcome the limitations of traditional quantum chemistry methods. An essential requirement for ground state quantum algorithms to be practical is the initialisation of the qubits to a high-quality approximation of the sought-after ground state. Quantum State Preparation (QSP) allows the preparation of approximate eigenstates obtained from classical calculations, but it is frequently treated as an oracle in quantum information. In this study, we conduct QSP on the ground state of prototypical strongly correlated systems, up to 28 qubits, using the Hyperion GPU-accelerated state-vector emulator. Various variational and non-variational methods are compared in terms of their circuit depth and classical complexity. Our results indicate that the recently developed Overlap-ADAPT-VQE algorithm offers the most advantageous performance for near-term applications.