A Phase Model of the Bio-Inspired NbOx Local Active Memristor under Weak Coupling Conditions

Area of Science:

• Computational complexity
• Materials science
• Computer engineering

Background:

• Boolean logic methods are inefficient for computationally difficult problems, such as the vertex coloring problem.
• The complexity of these problems arises from the sharp increase in solutions with problem size.
• This complexity necessitates exploring alternative, non-Boolean computational approaches.

Purpose of the Study:

• To investigate a new generation of computers utilizing local active memristor coupling.
• To explore memristor coupling networks as a potential solution for NP-hard problems.
• To establish a physics-based calculation method for analog computing.

Main Methods:

• Studying the dynamics of memristor coupling networks.
• Deriving a simplified system phase model from the network dynamics.
• Analyzing the computational capabilities of memristor-based systems.

Main Results:

• The dynamics of memristor coupling networks were analyzed.
• A simplified phase model for the memristor system was obtained.
• A physics-based calculation method was clarified.

Conclusions:

• Memristor coupling networks offer a novel approach to computation.
• The research provides a foundation for building analog computers.
• This approach can effectively solve NP-hard problems, overcoming Boolean logic limitations.