Department of Physics, University of Basel, Klingelbergstrasse 82, 4056 Basel, Switzerland.
Sci Adv. 2017 Apr 7;3(4):e1602273. doi: 10.1126/sciadv.1602273. eCollection 2017 Apr.
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.
量子现象有可能加速解决困难的优化问题。例如，基于量子隧穿效应的量子退火最近被证明在系统规模上比经典模拟退火呈指数级更好地扩展。然而，具有超导量子比特的量子退火器的当前实现面临两个主要挑战。首先，量子比特之间的连接性有限，排除了许多优化问题的直接实现。其次，退相干降低了优化的成功概率。我们解决了这两个缺点，并提出了一种架构，其中量子比特以连续变量自由度的方式进行稳健编码。通过利用通量量子化现象，获得了具有足够可调性的全连接连接，可实现许多相关的优化问题，而不会产生开销。此外，我们通过在存在耗散的情况下模拟非确定性多项式时间困难（NP 困难）和完全连接的数部分问题的小实例的最优解，证明了该架构的稳健性。
