Lithography-free reconfigurable integrated photonic processor

• Published in: Nature photonics 2023-08, Vol.17 (8), p.710-716
• Main Authors: Wu, Tianwei, Menarini, Marco, Gao, Zihe, Feng, Liang
• Format: Article
• Language: English
• Subjects: 639/624/1075/1079; 639/624/1107/1109; Algorithms; Applied and Technical Physics; Dynamic control; Fabrication; Information processing; Light transmission; Lithography; Microprocessors; Neural networks; Optical communication; Optical switching; Photonics; Physics; Physics and Astronomy; Quantum Physics; Signal processing; Spatial light modulators; Speech recognition
• ISSN: 1749-4885; 1749-4893
• DOI: 10.1038/s41566-023-01205-0

Integrated photonics, because of its intrinsic high speed, large bandwidth and unlimited parallelism, is critical in the drive to ease the increasing data traffic. Its technological enabler is high-precision lithography, which allows for the fabrication of high-resolution photonic structures. Here, in complete contrast to the state of the art, where photonic functions are predefined by lithographically modulating the real index, we report a lithography-free paradigm for an integrated photonic processor, targeting dynamic control of spatial-temporal modulations of the imaginary index on an active semiconductor platform, without the need for lithography. We demonstrate an imaginary-index-driven methodology to tailor optical-gain distributions to rationally execute prescribed optical responses and configure desired photonic functionality to route and switch optical signals. Leveraging its real-time reconfigurability, we realize photonic neural networks with extraordinary flexibility, performing in situ training of vowel recognition with high accuracy. The programmability and multifunctionality intrinsically arising from the lithography-free characteristics can lead to a new paradigm for integrated photonic signal processing to conduct and reconfigure complex computation algorithms, accelerating the information-processing speed to achieve long-term performance requirements. Spatial light modulator-based lithography-free programmable light transmission through optical gain medium is demonstrated for optical switching and a rudimentary photonic neural network.