The software implementations of neuronal systems have shown great effectiveness, even if the natural hardware separation between the processing and memory areas in computers slows down the analysis capacity. To overcome these limitations, new hardware configurations are moving towards neuromorphic models, capable of unifying the processing/memory dichotomy. Recently, integrated photonic X-junctions formed by waveguides written by spatial solitons have shown the ability to perform supervised learning. The solitonic technology, compared to the traditional one, offers the advantage of realizing plastic circuitry, a typical characteristic of biological neural networks. This work extensively studies both supervised and unsupervised learning of photonic soliton X-junctions. By exploiting the plasticity of the nonlinear refractive index at the base of the soliton formation, X-junctions can readdress their behaviours forwarding data to different outputs. In this article, we will extend the state-of-the-art: starting from supervised learning, for which all possible cases are now investigated, a material sensitive to the transported signals will be introduced to allow the junction to carry out unsupervised learning. In this way, the junction autonomously recognises the transported signals without the external intervention of the operator. Learning and memory now physically coincide in fact, learning means that the junction slowly switches based on the information sent; any further unknown information sent will find the junction in the modified state which corresponds to the learned information and will be recognised as well (reasoning based on comparison with stored information).

For an optical technology to be feasible as a substitution of electronics one for neuromorphic applications, it is required the waveguides in which are capable of confining and directing light signals in much smaller dimensions than the operating wavelength of the light, i.e., subwavelength optical components must be realized. Hybrid nature of surface plasmon polariton addresses the problem with the diffraction limit of regular photonic components. Here, the authors present a two-dimensional numerical simulation of a passive photonic element based on a saturable absorber material as a hardware base analogy to the biological activation function existed at the cell body of neurons. They demonstrate that at telecom wavelengths, a highly confined SPP mode can be modulated in a nonlinear fashion by considering the carrier dynamics of graphene/PMMA polymeric composite as a two-level system. The hardware base sigmoid type nonlinear activation function derived from this study further characterized; and the parameters which appeared to be effective on the performance of the structure, such as saturation intensity, modulation depth, and thickness of the synaptic part as a Fabry–Pérot structure, have been studied.

For an optical technology to be feasible as a substitution of electronics one, it is required the waveguides be capable of confining and directing light signals in much smaller dimensions than the operating wavelength of the light, i.e. subwavelength optical components must be realized. One approach to miniaturize the size of the photonic components is to benefit the hybrid nature of Surface Plasmon Polariton which addresses the problem with the diffraction limit of regular photonic components. Here, the authors present a two-dimensional numerical simulation of a passive photonic element based on a saturable absorber material as an analogy to the biological neurons activation function. They demonstrate that at telecom wavelengths a highly confined SPP mode can be modulated in a nonlinear fashion by considering the carrier dynamics of graphene/PMMA polymeric composite as a two-level system. The sigmoid type nonlinear activation function derived from this study, further characterized and the parameters which appeared to be effective on the performance of the structure, such as saturation intensity, modulation depth, and thickness of the synaptic part as a Fabry-Perot structure, has been studied.