Work

Low-depth two-unitary design of programmable photonic circuits

Year: 2024

Type: article

Abstract: Large-scale programmable photonic circuits are opening up new possibilities for information processing providing fast and energy-efficient means for matrix-vector multiplication. Here, we introduce what we believe to be a novel architecture of photonic circuits capable of implementing non-unitary transfer matrices, usually required by photonic neural networks, iterative equation solvers, or quantum samplers. Our architecture exploits compact low-depth beam-splitter meshes rather than bulky fully connected mixing blocks used in previous designs, making it more compatible with planar integrated photonics technology. We have shown that photonic circuits designed with our architecture have lower depth than their standard counterparts and are extremely tolerant of hardware errors.

Source: Physical Review Research

DOI: 10.1103/9fg1-fdfl

Authors: S. A. Fldzhyan, M. Yu. Saygin, S. S. Straupe

Institution: Lomonosov Moscow State University

Language: English

Topic: Neural Networks and Reservoir Computing

Subfield: Artificial Intelligence

Field: Computer Science

Domain: Physical Sciences

Open Access status: gold

Estimated APC paid: $2,625

Funders: Benelux Association for Stable Isotope Scientists, Foundation for the Advancement of Theoretical Physics and Mathematics, Lomonosov Moscow State University