Abstract
As an elementary processor of neural networks, a neuron performs exotic dynamic functions, such as bifurcation, repetitive firing, and oscillation quenching. To achieve ultrafast neuromorphic signal processing, the realization of photonic equivalents to neuronal dynamic functions has attracted considerable attention. However, despite the nonconservative nature of neurons due to energy exchange between intra‐ and extra‐cellular regions through ion channels, the critical role of non‐Hermitian physics in the photonic analogy of a neuron has been neglected. Here, a neuromorphic non‐Hermitian photonic system ruled by parity‐time symmetry is presented. For a photonic platform that induces the competition between saturable gain and loss channels, dynamical phases are classified with respect to parity‐time symmetry and stability. In each phase, unique oscillation quenching functions and nonreciprocal oscillations of light fields are revealed as photonic equivalents of neuronal dynamic functions. The proposed photonic system for neuronal functionalities will become a fundamental building block for light‐based neural signal processing.
Highlights
Non-Hermitian photonics[18,19,20] inspired by parity-time dependent gating of ion channels (Na+, K+, and leak) and their (PT) symmetry[21] has rejuvenated the utilization of nonlinear nonlinear competition satisfying the law of current conserva- wave channels for photonic[22,23,24] or microwave[25] functionalition, which derive unique neuronal functions of bifurcation,[2,3] ties
From Equation (2) with the equilibrium condition dIG,L/dt = 0, we look for the nontrivial equilibrium of the unbroken PT symmetry, which leads to the homogeneous steady state[34] (HSS) of IG = IL IH: the same light intensity level in gain and loss resonators (Experimental Section)
We focus on the coexisting phase C2, offering nonreciprocal oscillations which are absent from other dynamic phases (AD, oscillation death (OD), C1, and U phases)
Summary
To draw the photonic analogy of a neuron, we examine neuronal ion channels using the HH model.[1]. Because the neuron is an open system interacting with the extracellular region, an open system in non-Hermitian photonics[18,19,20] is a suitable platform for realizing photonic neurons The core of this analogy will be the construction of state-dependent “source” and “sink” channels for light. D) Photonic channel strengths gSat(I) with different signs of γSat. A resonator with intensity-dependent nonlinearities is modeled by the temporal equation,[41] dψ/dt = iω0ψ + M(|ψ|2)ψ, where ψ and ω0 are the field amplitude and resonant frequency, respectively, and M(|ψ|2) is the function that determines the type of nonlinearity. The competition between ion channels mediated by Kirchhoff's law is reproduced by the electromagnetic coupling between resonators
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