论文标题
带有单个驱动性非线性振荡器的量子关联记忆
Quantum associative memory with a single driven-dissipative nonlinear oscillator
论文作者
论文摘要
关联内存的算法通常依赖于许多连接单元的网络。原型示例是Hopfield模型，其对量子领域的概括主要基于开放的量子模型。我们提出了一种通过单个驱动驱动的量子振荡器来实现关联记忆，从而利用其相位空间中的无限自由度。该模型可以在大型制度中提高基于神经元系统的存储能力，我们证明$ n $ cooherent状态之间成功的状态歧视，这代表了系统的存储模式。可以通过修改驾驶强度并构成修改后的学习规则来连续调整这些。我们表明，关联记忆能力与liouvillian超级操作机中的光谱差距的存在固有地相关，这导致在与亚稳态相对应的动力学中导致较大的时间尺度分离。
Algorithms for associative memory typically rely on a network of many connected units. The prototypical example is the Hopfield model, whose generalizations to the quantum realm are mainly based on open quantum Ising models. We propose a realization of associative memory with a single driven-dissipative quantum oscillator exploiting its infinite degrees of freedom in phase space. The model can improve the storage capacity of discrete neuron-based systems in a large regime and we prove successful state discrimination between $n$ coherent states, which represent the stored patterns of the system. These can be tuned continuously by modifying the driving strength, constituting a modified learning rule. We show that the associative-memory capacity is inherently related to the existence of a spectral gap in the Liouvillian superoperator, which results in a large timescale separation in the dynamics corresponding to a metastable phase.
