Harnessing optoelectronic noises in a photonic generative network.

ABSTRACT: Integrated optoelectronics is emerging as a promising platform of neural network accelerator, which affords efficient in-memory computing and high bandwidth interconnectivity. The inherent optoelectronic noises, however, make the photonic systems error-prone in practice. It is thus imperative to devise strategies to mitigate and, if possible, harness noises in photonic computing systems. Here, we demonstrate a photonic generative network as a part of a generative adversarial network (GAN). This network is implemented with a photonic core consisting of an array of programable phase-change memory cells to perform four-element vector-vector dot multiplication. The GAN can generate a handwritten number ("7") in experiments and full 10 digits in simulation. We realize an optical random number g

SUBMITTER: Wu C 

PROVIDER: S-EPMC8782447 | biostudies-literature | 2022 Jan

REPOSITORIES: biostudies-literature