论文标题
\ textit {lc}谐振器模拟的通用量子门，人工神经元和模式识别
Universal quantum gates, artificial neurons and pattern recognition simulated by \textit{LC} resonators
论文作者
论文摘要
我们建议通过\ textit {lc}谐振器模拟量子门，其中振幅和电压的相描述了量子状态。通过控制谐振器的电容或电感，可以任意控制电压的相位。一组谐振器充当相移，Hadamard和CNOT大门。它们构成了一组通用量子门。我们还讨论了人造神经元的应用。例如，我们通过评估输入和参考模式之间的相似性来研究数字和字母的模式识别。我们还使用复杂的神经网络研究了有色模式识别。
We propose to simulate quantum gates by \textit{LC} resonators, where the amplitude and the phase of the voltage describe the quantum state. By controlling capacitance or inductance of resonators, it is possible to control the phase of the voltage arbitrarily. A set of resonators acts as the phase-shift, the Hadamard and the CNOT gates. They constitute a set of universal quantum gates. We also discuss an application to an artificial neuron. As an example, we study a pattern recognition of numbers and alphabets by evaluating the similarity between an input and the reference pattern. We also study a colored pattern recognition by using a complex neural network.
