Paul R. Prucnal

Reconfigurable analog photonic networks

2017

Spurred by advances in scalable photonic system integration, ideas in photonic information processing have recently experienced a resurgence. We review the latest results in reconfigurable analog photonic networks, neuromorphic photonics, and multivariate RF photonics. These …

Demonstration of Multivariate Photonics: Blind Dimensionality Reduction With Integrated Photonics

2019 · Journal of Lightwave Technology

Multi-antenna radio front-ends generate a multi-dimensional flood of information, most of which is partially redundant. Redundancy is eliminated by dimensionality reduction. This class of operations presents harsh fundamental tradeoffs to contemporary digital processing techniques. These …

Online training and pruning of photonic neural networks

2023

Photonic neural networks have unique weight-actuating mechanisms and manufacturing variations, resulting in a suboptimal performance by conventional offline training. By incorporating a power-pruning regularization term in the loss function, we demonstrate an online training method …

Silicon Photonics for Training Deep Neural Networks

2022

Analog photonic networks as deep learning hardware accelerators are trained on standard digital electronics. We propose an on-chip training of neural networks enabled by a silicon photonic architecture for parallel, efficient, and fast data operations. …

Microring Modulation-and-Weight Banks

2024

For photonic neural networks, we propose a novel microring bank with carrier-effect and thermal dual-tunability, which can 1) combine modulating and weighting for saved space, 2) improve tuning efficiency, and 3) inherit WDM-enabled scalability.