Institute of Industrial Science, The University of Tokyo, 4-6-1 Komaba, Meguro-ku, Tokyo 153-8505, Japan.
ImPACT program, The Japan Science and Technology Agency, Gobancho 7, Chiyoda-ku, Tokyo 102-0076, Japan.
Phys Rev Lett. 2019 Feb 1;122(4):040607. doi: 10.1103/PhysRevLett.122.040607.
The relaxation of binary spins to analog values has been the subject of much debate in the field of statistical physics, neural networks, and more recently quantum computing, notably because the benefits of using an analog state for finding lower energy spin configurations are usually offset by the negative impact of the improper mapping of the energy function that results from the relaxation. We show that it is possible to destabilize trapping sets of analog states that correspond to local minima of the binary spin Hamiltonian by extending the phase space to include error signals that correct amplitude inhomogeneity of the analog spin states and controlling the divergence of their velocity. Performance of the proposed analog spin system in finding lower energy states is competitive against state-of-the-art heuristics.
二进制自旋到模拟值的弛豫一直是统计物理、神经网络领域以及最近量子计算领域的热门话题，主要是因为使用模拟状态来寻找更低能量的自旋构型的好处通常会被弛豫导致的能量函数映射不当的负面影响所抵消。我们表明，通过扩展相空间以包括校正模拟自旋状态的幅度不均匀性的误差信号，并控制其速度的发散，可以使对应于二进制自旋哈密顿量局部极小值的模拟状态的俘获集失稳。所提出的模拟自旋系统在寻找更低能量状态方面的性能可与最先进的启发式算法相媲美。
