Nonlinear Quantum Neuron: A Fundamental Building Block for Quantum Neural Networks

Quantum Neuron: an elementary building block for machine learning on quantum computers

Even the most sophisticated artificial neural networks are built by aggregating substantially identical units called neurons. A neuron receives multiple signals, internally combines them, and applies a non-linear function to the resulting weighted sum. Several attempts to generalize neurons to the quantum regime have been proposed, but all proposals collided with the difficulty of implementing non-linear activation functions, which is essential for classical neurons, due to the linear nature of quantum mechanics. Here we propose a solution to this roadblock in the form of a small quantum circu…

Quantum computing model of an artificial neuron with continuously valued input data

Artificial neural networks have been proposed as potential algorithms that could benefit from being implemented and run on quantum computers. In particular, they hold promise to greatly enhance Artificial Intelligence tasks, such as image elaboration or pattern recognition. The elementary building block of a neural network is an artificial neuron, i.e. a computational unit performing simple mathematical operations on a set of data in the form of an input vector. Here we show how the design for the implementation of a previously introduced quantum artificial neuron [npj Quant. Inf. $\textbf{5}$…

量子泄漏积分发放脉冲神经元与网络

A Quantum Leaky Integrate-and-Fire Spiking Neuron and Network

针对量子机器学习模型资源与多样性不足及NISQ硬件限制问题，提出仅需2个旋转门无CNOT门的量子泄漏积分发放（QLIF）神经元模型，构建首类QSNN和QSCNN，在多数据集上性能具竞争力且扩展性与计算效率高。

Microtubules: The neuronic system of the neurons?

In this talk we review recent work on integrable models for Microtubule (MT) networks, subneural paracrystalline cytosceletal structures, which seem to play a fundamental role in the neurons. We cast here the complicated MT dynamics in the form of a 1+1-dimensional non-critical string theory, which can be formulated in terms of (dual) Dirichlet branes, according to modern perspectives. We suggest that the MTs are the microsites in the brain, for the emergence of stable, macroscopic quantum coherent states, identifiable with the ``preconscious states''. Quantum space-time effects, as described …

通过随机神经动力学推导单个神经元的薛定谔方程

Derivation of a Schrödinger Equation for Single Neurons Through Stochastic Neural Dynamics

本文证明神经元膜电噪声可涌现出含新常数$\hat{\hbar}$的薛定谔方程，挑战量子与神经科学范式，并提出阈下振荡量子涨落可作为实验检验。

An Artificial Spiking Quantum Neuron

Artificial spiking neural networks have found applications in areas where the temporal nature of activation offers an advantage, such as time series prediction and signal processing. To improve their efficiency, spiking architectures often run on custom-designed neuromorphic hardware, but, despite their attractive properties, these implementations have been limited to digital systems. We describe an artificial quantum spiking neuron that relies on the dynamical evolution of two easy to implement Hamiltonians and subsequent local measurements. The architecture allows exploiting complex amplitud…