Holographic photonic neuron

TL;DR

This paper introduces a holographic photonic neuron using orbital angular momentum states in an optical correlator, enabling pattern recognition and potential integration into neuromorphic quantum-photonic processors.

Contribution

It presents a novel implementation of a photonic neuron leveraging OAM states for pattern recognition, bridging classical optics and quantum computing.

Findings

Successful correlation independent of intensity

Photon OAM states used as transmission protocol

Potential for scalable neuromorphic quantum-photonic systems

Abstract

The promise of artificial intelligence (AI) to process complex datasets has brought about innovative computing paradigms. While recent developments in quantum-photonic computing have reached significant feats, mimicking our brain's ability to recognize images are poorly integrated in these ventures. Here, I incorporate orbital angular momentum (OAM) states in a classical Vander Lugt optical correlator to create the holographic photonic neuron. The photonic neuron can memorize an array of matched filters in a phase-hologram, which is derived by linking OAM states with elements in the array. Successful correlation is independent of intensity and yields photons with OAM states, which can be used as a transmission protocol or qudits for quantum computing. The unique OAM identifier establishes the photonic neuron as a fundamental AI device for pattern recognition that can be scaled and integrated with other computing platforms to build-up a neuromorphic quantum-photonic processor that mimics the brain.