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Proposed for analog computing, multimode fibers have limitations due to slow spatial-domain encoding. Our work showcases instead the computational prowess of a scheme employing a step-index few-mode fiber (FMF) segment, for high-speed spatiotemporal coincidence detection by leveraging the FMF’s dispersive optical properties. The FMF is a custom-made fabrication, with NA = 0.15, a core diameter of 22 μm, and a length of 13 m, introducing delay to temporal input pulses through the supported propagation of higher-order fiber modes. The temporal mixing of these modes creates short-term memory for time-encoded information which we exploit for coincidence detection. By slightly misaligning the input beam with the FMF’s longitudinal axis, we can modify the impact of the different modes on the overall spatial pattern distribution. Our experimental system operates at 1550 nm and encodes 6-bit header patterns with 35.1 ps pulses per bit. With four distinct 40 GHz photodetected points at the output speckle pattern of the FMF, we capture four different time series that correspond to different power integrals and use them to train a logistic regression classifier. Eventually, every header classification is performed with the sampling of only one pulse time window, thus our system operates at 28.5 Gb/s. Remarkably, under various input misalignment conditions, our system demonstrates error rates below 1/5000. This level of performance could not be obtained with a standard step-index multimode fiber of the appropriate length.
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