论文标题

连贯的伊辛机器 - 量子光学和神经网络观点

Coherent Ising machines -- Quantum optics and neural network perspectives

论文作者

Yamamoto, Y., Leleu, T., Ganguli, S., Mabuchi, H.

论文摘要

连贯的ISING机器(CIM)是光学参数振荡器(OPOS)的网络,其中“最强”的集体振荡模式远高于阈值,对应于给定ISIN的最佳解决方案。但是,当泵速速率或网络耦合速率从低于阈值到以上的阈值时,iSing耦合矩阵[J_IJ]的特征值(J_IJ)的特征向量会出现在阈值附近,并阻碍机器放松到真正的基础状态。此处描述了两种攻击此问题的补充方法。一种方法是利用阈值以下OPO的挤压/抗块状真空噪声,通过量子噪声相关性产生连贯的散布在许多局部最小值上,这可以使机器能够访问真实的地面状态或具有足够接近地面状态的特征元素的eigen egen态,以访问阈值以上的eigen egenergies。另一种方法是实现实时错误校正反馈循环,以便在探索基础状态的探索性搜索期间,机器从一个本地最小值迁移到另一个最小值。最后,指出了连接CIM和传统计算机科学技术的一系列定性类比。特别是,涉及组合优化中使用的信念传播和调查传播。

A coherent Ising machine (CIM) is a network of optical parametric oscillators (OPOs), in which the "strongest" collective mode of oscillation at well above threshold corresponds to an optimum solution of a given Ising problem. When a pump rate or network coupling rate is increased from below to above threshold, however, the eigenvectors with a smallest eigenvalue of Ising coupling matrix [J_ij] appear near threshold and impede the machine to relax to true ground states. Two complementary approaches to attack this problem are described here. One approach is to utilize squeezed/anti-squeezed vacuum noise of OPOs below threshold to produce coherent spreading over numerous local minima via quantum noise correlation, which could enable the machine to access either true ground states or excited states with eigen-energies close enough to that of ground states above threshold. The other approach is to implement real-time error correction feedback loop so that the machine migrates from one local minimum to another during an explorative search for ground states. Finally, a set of qualitative analogies connecting the CIM and traditional computer science techniques are pointed out. In particular, belief propagation and survey propagation used in combinatorial optimization are touched upon.

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