Performance of Domain-Wall Encoding for Quantum Annealing

J Chen, T Stollenwerk, Nicholas Chancellor

Jiei IWAMA, Hironori Makino

Jie Chen, Tobias Stollenwerk, Nicholas Chancellor

In this article, we experimentally test the performance of the recently proposed domain-wall encoding of discrete variables Chancellor, 2019, on Ising model flux qubit quantum annealers. We compare this encoding with the traditional one-hot methods and find that they outperform the one-hot encoding for three different problems at different sizes of both the problem and the variables. From these results, we conclude that the domain-wall encoding yields superior performance against a variety of metrics furthermore; we do not find a single metric by which one hot performs better. We even find that a 2000Q quantum annealer with a drastically less connected hardware graph but using the domain-wall encoding can outperform the next-generation Advantage processor if that processor uses one-hot encoding.

Jiei IWAMA, Hironori Makino

Domain wall encoding (DWE) is a new computational technique that allows the quantum annealing (QA)to be applied to the continuous variable optimizations.This study verifies by the numerical experiments that the reverse annealing (RA), an auxiliary computational technique of QA, works effectively for QA incorporating DWE and improves the probability of deriving the optimal solution.

Daniel A. Lidar

Anurag Mishra, Tameem Albash, Gerardo A. Paz-Silva +1 more