Quantifying the Accuracy of Microcomb-Based Photonic RF Transversal Signal Processors

Photonic RF transversal signal processors, which are equivalent to reconfigurable electrical digital signal processors but implemented with photonic technologies, are attractive for high-speed information processing. Optical microcombs are extremely powerful as sources for RF photonics since they can generate many wavelength channels from compact micro-resonators, offering greatly reduced size, power consumption, and complexity. Recently, a variety of signal processing functions have been demonstrated using microcomb-based photonic RF transversal signal processors. Here, we provide a detailed analysis for quantifying the processing accuracy of microcomb-based photonic RF transversal signal processors. First, we investigate the theoretical limitations of the processing accuracy determined by tap number, signal bandwidth, and pulse waveform. Next, we discuss the practical error sources from different experimental components of the signal processors. Finally, we assess the relative contributions of the two to the overall accuracy. We find that the overall accuracy is mainly limited by experimental factors when the processors are properly designed to minimize the theoretical limitations, and that these remaining errors can be further greatly reduced by introducing feedback control to calibrate the processors' impulse response. These results provide a useful guide for designing microcomb-based photonic RF transversal signal processors to optimize their accuracy.

Automated summary

Photonic RF transversal signal processors, implemented with photonic technologies, offer high-speed information processing with reduced size, power consumption, and complexity. Optical microcombs generated from compact micro-resonators are ideal sources for RF photonics. This study provides a detailed analysis of the processing accuracy of microcomb-based photonic RF transversal signal processors. Theoretical limitations, practical error sources, and the relative contributions of both are investigated, highlighting the potential for further error reduction through feedback control.