Litcius/Paper detail

Designing Ising machines with higher order spin interactions and their application in solving combinatorial optimization

Mohammad Khairul Bashar, Nikhil Shukla

2023Scientific Reports27 citationsDOIOpen Access PDF

Abstract

The Ising model provides a natural mapping for many computationally hard combinatorial optimization problems (COPs). Consequently, dynamical system-inspired computing models and hardware platforms that minimize the Ising Hamiltonian, have recently been proposed as a potential candidate for solving COPs, with the promise of significant performance benefit. However, prior work on designing dynamical systems as Ising machines has primarily considered quadratic interactions among the nodes. Dynamical systems and models considering higher order interactions among the Ising spins remain largely unexplored, particularly for applications in computing. Therefore, in this work, we propose Ising spin-based dynamical systems that consider higher order (> 2) interactions among the Ising spins, which subsequently, enables us to develop computational models to directly solve many COPs that entail such higher order interactions (i.e., COPs on hypergraphs). Specifically, we demonstrate our approach by developing dynamical systems to compute the solution for the Boolean NAE-K-SAT (K ≥ 4) problem as well as solve the Max-K-Cut of a hypergraph. Our work advances the potential of the physics-inspired 'toolbox' for solving COPs.

Topics & Concepts

Ising modelIsing spinHypergraphComputer scienceToolboxDynamical systems theoryQuadratic unconstrained binary optimizationHamiltonian (control theory)Quadratic equationSpinsStatistical physicsTheoretical computer sciencePhysicsMathematicsMathematical optimizationDiscrete mathematicsQuantum computerQuantum mechanicsProgramming languageCondensed matter physicsQuantumGeometryQuantum Computing Algorithms and ArchitectureError Correcting Code TechniquesDNA and Biological Computing
Designing Ising machines with higher order spin interactions and their application in solving combinatorial optimization | Litcius