# Photonic reservoir computer based on frequency multiplexing

arXiv: https://arxiv.org/abs/2008.11247 · HTML: https://mlsanity.com/paper/2008.11247/

## Key facts

- Cited by 3 papers in the map (data through 14 Oct 2026).
- First posted on arXiv 25 Aug 2020.

## Built on by (most cited first, 3 of 3)

- [Photonics-Enhanced Graph Convolutional Networks](https://mlsanity.com/paper/2512.15549/) (2025)
- [Optimizing the Network Topology of a Linear Reservoir Computer](https://mlsanity.com/paper/2509.23391/) (2025)
- [HAMON: Passive Optical Sequence Mixing for Long-Horizon Forecasting](https://mlsanity.com/paper/2606.17028/) (2026)

## Abstract (arXiv)

Reservoir computing is a brain inspired approach for information processing, well suited to analogue implementations. We report a photonic implementation of a reservoir computer that exploits frequency domain multiplexing to encode neuron states. The system processes 25 comb lines simultaneously (i.e. 25 neurons), at a rate of 20 MHz. We illustrate performances on two standard benchmark tasks: channel equalization and time series forecasting. We also demonstrate that frequency multiplexing allows output weights to be implemented in the optical domain, through optical attenuation. We discuss the perspectives for high speed high performance low footprint implementations.