Wave computing based on dynamical networks: Applications in optimization problems
Phys. Rev. Applied 24, 034082 – Published 30 September, 2025
DOI: https://doi.org/10.1103/xztx-sf2h
Abstract
This paper is a contribution to the Physical Review Applied collection titled Physics-Inspired Computing.
We develop a computing framework that leverages wave propagation within an interconnected network, where nodes and edges possess wave manipulation capabilities, such as frequency mixing or time delay. This computing paradigm can not only achieve intrinsic parallelism, as in existing works, by the exploration of an exponential number of possibilities simultaneously with very small number of hardware units, but also extend this unique characteristic to a multidimensional space including spatial, temporal, and frequency domains, making it particularly effective for addressing NP-hard problems. The proposed architecture has been validated through spice simulations, demonstrating its potential capability in solving several NP-hard problems, such as the number partitioning problem, the 0/1 knapsack problem, and the traveling salesman problem.
Physics Subject Headings (PhySH)
Collections
This article appears in the following collection:
Collection on Physics-Inspired Computing
Physical Review Applied is pleased to present a Collection on Physics-Inspired Computing, highlighting the rapidly evolving field of energy-efficient computing techniques, from hardware technologies to algorithms, where physics inspiration serves as the crucial link. Contributions to this collection will be published throughout 2025. This Collection is being curated by Guest Editors Kerem Camsari and Supriyo Datta.
