论文标题
量子神经网络 - 计算场理论和动力学
Quantum Neural Networks -- Computational Field Theory and Dynamics
论文作者
论文摘要
为了将量子人工神经网络作为量子动态计算系统，作为动态系统的量子人工神经网络的形式化，将单一MAP的概念扩展到神经计算设置，并在网络上引入量子计算场理论。在模拟量子复发的神经网络以及所得的现场动态的模拟中说明了形式主义，并研究了在量子神经活动场的级别上具有激发和放松周期的新兴神经波，以及混沌签名的边缘，以及局部神经元素的复杂量和复杂性，包括远程量子的复杂性，并将其复杂性地进行了复杂性。权力法签名。还解决了对量子计算机科学，量子复杂性研究，量子技术和神经科学的影响。
To address Quantum Artificial Neural Networks as quantum dynamical computing systems, a formalization of quantum artificial neural networks as dynamical systems is developed, expanding the concept of unitary map to the neural computation setting and introducing a quantum computing field theory on the network. The formalism is illustrated in a simulation of a quantum recurrent neural network and the resulting field dynamics is researched upon, showing emergent neural waves with excitation and relaxation cycles at the level of the quantum neural activity field, as well as edge of chaos signatures, with the local neurons operating as far-from-equilibrium open quantum systems, exhibiting entropy fluctuations with complex dynamics including complex quasiperiodic patterns and power law signatures. The implications for quantum computer science, quantum complexity research, quantum technologies and neuroscience are also addressed.
