Work

String Model Building on Quantum Annealers

Year: 2023

Type: article

Abstract: For the first time the direct construction of string models on quantum annealers has been explored and has been investigated their efficiency and effectiveness in the model discovery process. Through a thorough comparison with traditional methods such as simulated annealing, random scans, and genetic algorithms, it is highlighted the potential advantages offered by quantum annealers, which in this study promised to be roughly 50 times faster than random scans and genetic algorithm and approximately four times faster than simulated annealing.

Source: Fortschritte der Physik

DOI: 10.1002/prop.202300167

Authors: Steven Abel, Luca A. Nutricati, John Rizos

Institutions: Durham University, European Organization for Nuclear Research, University of Ioannina

Language: English

Topic: Quantum Computing Algorithms and Architecture

Subfield: Artificial Intelligence

Field: Computer Science

Domain: Physical Sciences

Open Access status: hybrid

Estimated APC paid: $3,140

Funders: CERN, Science and Technology Facilities Council