Analog quantum approximate optimization algorithm

Barraza, Nancy; Barrios, Gabriel Alvarado; Peng, Jie; Lamata, Lucas; Solano, Enrique; Albarran-Arriagada, Francisco

Abstract

We present an analog version of the quantum approximate optimization algorithm suitable for current quantum annealers. The central idea of this algorithm is to optimize the schedule function, which defines the adiabatic evolution. It is achieved by choosing a suitable parametrization of the schedule function based on interpolation methods for a fixed time, with the potential to generate any function. This algorithm provides an approximate result of optimization problems that may be developed during the coherence time of current quantum annealers on their way toward quantum advantage.

Más información

Título según WOS: Analog quantum approximate optimization algorithm
Título de la Revista: QUANTUM SCIENCE AND TECHNOLOGY
Volumen: 7
Número: 4
Editorial: IOP PUBLISHING LTD
Fecha de publicación: 2022
DOI:

10.1088/2058-9565/ac91f0

Notas: ISI