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Quantum accelerated approach to the thermal state of classical all-to-all connected spin systems with applications to pattern retrieval in the Hopfield neural network

机译:Quantum加速了具有应用程序在Hopfield神经网络中的应用程序模式检索的仿古全连接自旋系统的热状态的方法

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We explore the question as to whether quantum effects can yield a speedup of the nonequilibrium evolution of fully connected quadratic spin models towards a classical thermal state. In our approach we exploit the fact that the thermal state of a spin system can be mapped onto a node-free quantum state whose coefficients are given by thermal weights. This perspective permits the construction of a dissipative yet quantum dynamics which encodes in its stationary state the thermal state of the original problem. We show for the case of an all-to-all connected Ising spin model that an appropriate transformation of this dissipative dynamics allows us to interpolate between a regime in which the order parameter obeys the classical equations of motion under Glauber dynamics and a quantum regime with an accelerated transient timescale before approaching stationarity.We show that this effect enables, in principle, a speedup of pattern retrieval in a Hopfield neural network.
机译:我们探讨了对量子效应是否能产生完全连接的二次旋转模型的非QuibiBribrium演化的加速朝向经典热状态。 在我们的方法中,我们利用了旋转系统的热状态可以映射到无节食量子状态,其系数由热量给出。 该透视允许构造耗散且量子动态,其在其静止状态下编码原始问题的热状态。 我们展示了全面连接的旋转模型的情况,即这种耗散动态的适当变换使我们能够在订单参数遵守Glauber Dynamics下的典型运动和量子制度的制度之间插入 在接近Sentharity之前的加速瞬态时间尺度。我们展示了这种效果,原则上是一种在Hopfield神经网络中的模式检索的加速。

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