Neuromorphic vision of optical darkness for high-throughput topological knot signal processing

Abstract Structured beams endowed with topological charges and singularities show great potential for both classical and quantum information encoding. While manipulation of topological charges is well-established, information carriers based on topological invariants governing singularity evolution—optical links and knots—remain underexplored. The fundamental limitation lies in detection bandwidth: resolving singularities behaving like optical darkness through conventional intensity localization demands prohibitive exposure times, thereby constraining the transmission rates. To address this issue, we introduce a neuromorphic approach—Logarithmic Intensity Gradient Handling Technology for Event-based Links-and-knots Formation (LightELF)—which enables microsecond-level asynchronous spatial readout of sparse singularities. By fusing logarithmic gradient sampling with the superoscillating nature of singularities, LightELF reconstructs links and knots without post-processing while achieving orders-of-magnitude data reduction. Moreover, we demonstrate a topological binary signal processing chain integrating a high-throughput transmitter with our neuromorphic detector. This work establishes optical links and knots as viable information carriers, pioneering event sensing in topological photonics and providing a neuromorphic signal framework for optical information processing.