PT  - JOURNAL ARTICLE
AU  - Nigg, Simon E.
AU  - Lörch, Niels
AU  - Tiwari, Rakesh P.
TI  - Robust quantum optimizer with full connectivity
AID  - 10.1126/sciadv.1602273
DP  - 2017 Apr 01
TA  - Science Advances
PG  - e1602273
VI  - 3
IP  - 4
4099  - http://advances.sciencemag.org/content/3/4/e1602273.short
4100  - http://advances.sciencemag.org/content/3/4/e1602273.full
SO  - Sci Adv2017 Apr 01; 3
AB  - Quantum phenomena have the potential to speed up the solution of hard optimization problems. For example, quantum annealing, based on the quantum tunneling effect, has recently been shown to scale exponentially better with system size than classical simulated annealing. However, current realizations of quantum annealers with superconducting qubits face two major challenges. First, the connectivity between the qubits is limited, excluding many optimization problems from a direct implementation. Second, decoherence degrades the success probability of the optimization. We address both of these shortcomings and propose an architecture in which the qubits are robustly encoded in continuous variable degrees of freedom. By leveraging the phenomenon of flux quantization, all-to-all connectivity with sufficient tunability to implement many relevant optimization problems is obtained without overhead. Furthermore, we demonstrate the robustness of this architecture by simulating the optimal solution of a small instance of the nondeterministic polynomial-time hard (NP-hard) and fully connected number partitioning problem in the presence of dissipation.