Color-Encoded Photonic Communication and Storage: A Wavelength-Based Alternative to Binary Signaling

Abstract

This work proposes a conceptual framework in which optical color (wavelength) statesare used to encode multiple bits per transmitted symbol, rather than the traditionalsingle-bit binary pulse. The framework extends the idea across three domains: 1. Color-coded transmission — using wavelength multiplexing to increase fiber throughput without changing the physical hardware pulse rate.2. A translation layer (transceiver) that converts binary data to color symbols for transmission and back to binary for compatibility with existing binary-based computing infrastructure.3. AI-assisted color-based storage and decoding — using a neural network to interpret closely-spaced wavelength states, particularly under realistic channel conditions involving nonlinear distortion and inter-channel crosstalk. A Python simulation is included, demonstrating:- Throughput scaling with number of distinguishable color levels (up to 6x speedup with 64 levels vs. traditional binary, at fixed pulse rate).- Decoding accuracy comparison between a simple threshold decoder and a trained neural network (MLP) decoder, under both simple Gaussian noise and a more realistic channel with nonlinear compression and crosstalk. Results show the AI decoder provides no advantage under simple linear noise, but a substantial advantage (e.g. ~81% vs ~17% accuracy at low noise) under realistic nonlinear/crosstalk conditions. Related established technologies are reviewed, including Wavelength DivisionMultiplexing (WDM), PAM-4/QAM modulation, multi-level-cell (MLC/TLC/QLC) flashstorage, wavelength-multiplexed diffractive optical storage, and photonicneural networks