Sensitivity of a Chaotic Logic Gate

02/15/2022
by   Noeloikeau Charlot, et al.
0

Chaotic logic gates or `chaogates' are a promising mixed-signal approach to designing universal computers. However, chaotic systems are exponentially sensitive to small perturbations, and the effects of noise can cause chaotic computers to fail. Here, we examine the sensitivity of a simulated chaogate to noise and other parameter variations (such as differences in supply voltage). We find that the regions in parameter space corresponding to chaotic dynamics coincide with the regions of maximum error in the computation. Further, this error grows exponentially within 4-10 iterations of the chaotic map. As such, we discuss the fundamental limitations of chaotic computing, and suggest potential improvements. Our Python simulation methods are open-source and available at https://github.com/Noeloikeau/chaogate.

READ FULL TEXT
research
05/14/2021

ATHENA: Advanced Techniques for High Dimensional Parameter Spaces to Enhance Numerical Analysis

ATHENA is an open source Python package for reduction in parameter space...
research
08/22/2023

ULGss: A Strategy to construct a Library of Universal Logic Gates for N-variable Boolean Logic beyond NAND and NOR

In literature, NAND and NOR are two logic gates that display functional ...
research
07/12/2022

RcTorch: a PyTorch Reservoir Computing Package with Automated Hyper-Parameter Optimization

Reservoir computers (RCs) are among the fastest to train of all neural n...
research
07/20/2022

Mathematical Model of Strong Physically Unclonable Functions Based on Hybrid Boolean Networks

We introduce a mathematical framework for simulating Hybrid Boolean Netw...
research
03/31/2022

Quantum simulation of real-space dynamics

Quantum simulation is a prominent application of quantum computers. Whil...
research
02/17/2014

Is Spiking Logic the Route to Memristor-Based Computers?

Memristors have been suggested as a novel route to neuromorphic computin...

Please sign up or login with your details

Forgot password? Click here to reset