Neuromorphic Photonics refers to the field of research and technology development that combines principles from neuroscience, photonics, and electronics to create systems that mimic the functionality of the human brain using optical components. It integrates the high speed and bandwidth capabilities of photonics (the generation, manipulation, and detection of light) with the architecture and computational principles of neural networks and brain-like structures.

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Real-Time Photonic Blind Interference Cancellation

mmWave devices can broadcast multiple spatially-separated data streams simultaneously in order to increase data transfer rates. Data transfer can, however, be compromised by interference. Photonic blind interference cancellation systems offer a power-efficient means of mitigating interference, but previous demonstrations of such systems have been limited by high latencies and the need for regular calibration. Here, we demonstrate real-time photonic blind interference cancellation using an FPGA-photonic system executing a zero-calibration control algorithm. Our system offers a greater than 200-fold reduction in latency compared to previous work, enabling sub-second cancellation weight identification. We further investigate key trade-offs between system latency, power consumption, and success rate, and we validate sub-Nyquist sampling for blind interference cancellation. We estimate that photonic interference cancellation can reduce the power required for digitization and signal recovery by greater than 74 times compared to the digital electronic alternative.