Abstract
In the past few years, analog computing has experienced rapid development but mostly for a single function. Motivated by parallel space-time computing and miniaturization, we show that reconfigurable graphene-based multilayers offer a promising path towards spatiotemporal computing with integrated functionalities by properly engineering both spatial- and temporal-frequency responses. This paper employs a tunable graphene-based multilayer to enable analog signal and image processing in both space and time by tuning the external bias. In the first part of the paper, we propose a switchable analog computing paradigm in which the proposed multilayer can switch among defined performances by selecting a proper external voltage for graphene monolayers. Spatial isotropic differentiation and edge detection in the spatial channel and first-order temporal differentiation and multilayer-based phaser with linear group-delay response in the temporal channel are demonstrated. In the second section of the paper, simultaneous and parallel spatiotemporal analog computing is demonstrated. The proposed multilayer processor has almost no static power consumption due to its floating-gate configuration. The spatial- and temporal-frequency transfer functions (TFs) are engineered using a transmission line (TL) model, and the obtained results are validated with full-wave simulations. Our proposal will enable real-time parallel spatiotemporal analog signal and image processing.
Highlights
Digital signal processors are widely used to accomplish a large variety of computational tasks
Motivated by parallel space-time computing and miniaturization, we show that reconfig
The recent theoretical and manufacturing progress in many applications in Fourier optics, and was recently miniathe field of artificial photonic materials, e.g., photonic crysturized using metamaterials and graphene-based multilaytals or metamaterials, has inspired a return of the old paradigm ers. Another known method for spatial processing is the of analog-based computing by leveraging low-loss structures transfer function (TF) method [51]
Summary
Digital signal processors are widely used to accomplish a large variety of computational tasks. Let us propose two distinct temporal processing: (i) performing the first-order temporal differentiation operation; and (ii), achieving temporal pulse spreading via a synthesized linear group-delay response at normal illumination (see Figure 1). In this channel, the input beam directly illuminates at normal illumination without using ro-. Input signal traveling along such a phaser experiences time spreading since its different spectral components travel with different group velocities, they temporally rearranged [7] By exploiting this temporal rearrangement, the various spectral components of a signal can be directly mapped onto the time domain and can it is clear that the envelope of the temporally reflected/transmitted field with central frequency 0 has the field profile of be processed in a real-time manner.
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