Photonics-Assisted Complex-Valued Discrete Fourier Transform Processor Based on Temporal Computing

In this paper, we propose and experimentally demonstrate a photonics-assisted complex-valued discrete Fourier transform (DFT) processor based on temporal computing. In the proposed DFT processor, the complex-valued input data and the orthogonal basis are encoded in sequence on an optical carrier via two high-speed dual-drive Mach-Zehnder modulators (DD-MZMs). By precisely controlling the synchronization time of the input data and orthogonal basis loading, the complex-valued multiplication operation is performed in the time domain. An optical hybrid is used to implement coherent detection, and two low-speed photodetectors are used to perform the complex-valued accumulation operation. As a demonstration, 32-points complex-valued DFT is performed, and the normalized root mean square error (NRMSE) is as small as 0.0133. In addition, a 16\times 32 pixels image is employed to implement 2D DFT, which achieves an NRMSE as small as 0.0065. The proposed DFT processor holds unique advantages including high throughput and low latency, which is potential to be widely used in artificial intelligence computing and radar signal processing systems.