# Demonstration of multivariate photonics: blind dimensionality reduction with analog integrated photonics

## TL;DR

This paper demonstrates multivariate photonics for analog dimensionality reduction using integrated photonic hardware and blind algorithms, enabling efficient processing of multi-antenna radio signals beyond electronic limitations.

## Contribution

It introduces a novel combination of integrated photonic hardware, analog PCA, and blind algorithms, with the first experimental demonstration of 2-channel photonic PCA at 1 GHz.

## Key findings

- Successful experimental demonstration of photonic PCA
- Introduction of methods to control blindness conditions
- Foundation laid for future multivariate photonic processing

## Abstract

Multi-antenna radio front-ends generate a multi-dimensional flood of information, most of which is partially redundant. Redundancy is eliminated by dimensionality reduction, but contemporary digital processing techniques face harsh fundamental tradeoffs when implementing this class of functions. These tradeoffs can be broken in the analog domain, in which the performance of optical technologies greatly exceeds that of electronic counterparts. Here, we present concepts, methods, and a first demonstration of multivariate photonics: a combination of integrated photonic hardware, analog dimensionality reduction, and blind algorithmic techniques. We experimentally demonstrate 2-channel, 1.0 GHz principal component analysis in a photonic weight bank using recently proposed algorithms for synthesizing the multivariate properties of signals to which the receiver is blind. Novel methods are introduced for controlling blindness conditions in a laboratory context. This work provides a foundation for further research in multivariate photonic information processing, which is poised to play a role in future generations of wireless technology.