Noise based logic: why noise? A comparative study of the necessity of randomness out of orthogonality

TL;DR

This paper compares noise-based logic with sinusoidal logic, demonstrating that in specific applications, noise-based logic can achieve exponentially lower computational complexity, highlighting the importance of randomness beyond orthogonality.

Contribution

It provides a comparative analysis showing that noise-based logic can outperform sinusoidal logic in certain tasks, emphasizing the necessity of randomness beyond orthogonality.

Findings

Noise-based logic can have exponentially lower complexity than sinusoidal logic in specific applications.

Orthogonal noise signals enable more efficient computation in certain logic systems.

The study highlights the importance of randomness in logic design beyond orthogonality.

Abstract

Although noise-based logic shows potential advantages of reduced power dissipation and the ability of large parallel operations with low hardware and time complexity the question still persist: is randomness really needed out of orthogonality? In this Letter, after some general thermodynamical considerations, we show relevant examples where we compare the computational complexity of logic systems based on orthogonal noise and sinusoidal signals, respectively. The conclusion is that in certain special-purpose applications noise-based logic is exponentially better than its sinusoidal version: its computational complexity can be exponentially smaller to perform the same task.