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Nature Communications

Thermally assisted quantum annealing of a 16-qubit problem

Neil G. Dickson, Mark W. Johnson, M. H. S. Amin, R. Harris, Fabio Altomare, A. J. Berkley, P. Bunyk, J Cai, E. M. Chapple, P Chavez, Florentin Cioată, T Cirip, P deBuen, Marshall Drew-Brook, Colin Enderud, S. Gildert, Firas Hamze, Jeremy Hilton, Emile Hoskinson, Kamran Karimi, E. Ladizinsky, N. Ladizinsky, Trevor M. Lanting, T Mahon, R Neufeld, T. Oh, I. Perminov, C Petroff, A. J. Przybysz, Chris C. Rich, P Spear, A Tcaciuc, M. C. Thom, E. Tolkacheva, Sergey V. Uchaikin, Jia-Chao Wang, A. B. Wilson, Zeeya Merali, Geordie Rose

Published May 21, 2013• 225 citations
Publisher
DOI
10.1038/ncomms2920

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The idea of Quantum Annealing(QA),which is based on the mechanism of quantum transition tunneling effect and not same with the annealing theory of simulated thermal annealing,is a recent offspring of the celebrated simulated thermal annealing by Kirkpatrick.This paper,firstly,summarizes the basic differences between Quantum Annealing and Simulated Annealing;and then mainly addresses the attention to the practical developments of the application in optimization such as Ising spin glass,Traveling Salesman Problem,Boolean Satisfiability Problem and so on,discusses the details of the annealing process of Quantum Annealing and its compare with Simulated Annealing on test problems;subsequently,expatiates the geophysical inverse theory and method corresponding to Quantum Annealing,discusses the setting of parameters such as Temperature and Transverse field,compares the probabilities of being on configurations with different transverse fields and potential energies;finally briefly summarizes the prospects and the existent problems of using Quantum Annealing in geophysical inverse problem.
There is an extensive body of research probing the potential of adiabatic quantum computation and quantum annealing to solve hard computational problems. This research endeavor is complicated by noise afflicting hardware during the computational process. An error-correcting approach called quantum annealing correction (QAC) was suggested to mitigate this noise. The QAC approach employs a centralized version of the repetition code in which the qubits are configured in a star-graph pattern with one special qubit playing the role of the hub. In this paper, we explore the thermal physics of the centralized repetition code, using a Lindblad equation framework to analyze its lifetime when coupled to a thermal bath. We show that its centralized configuration leads to thermal stability, enabling the robust storage of a logical bit of information, despite the fact that there is only 1 ferromagnetic Ising interaction per qubit like a 1-dimensional Ising chain.