2023/10/24 by I. Martín, Martin, Isaac K., Andrew G. Moore +7 · 2 citations
Computer Science · Engineering · #90C05 68Q12 (Secondary) #94C11 (Primary) #Advanced Memory and Neural Computing #Emerging Technologies (cs.ET) #FOS: Computer and information sciences #FOS: Mathematics #G.1.6 #G.3 #Neural and Evolutionary Computing (cs.NE) #Optimization and Control (math.OC) #Quantum Computing Algorithms and Architecture #Stochastic Gradient Optimization Techniques
paper · pdf · doi:10.48550/arxiv.2310.16246
openalex publication_date 2023/10/24 · openalex created_date 2025/10/10 · openalex updated_date 2026/07/28
Ising machines are a form of quantum-inspired processing-in-memory computer which has shown great promise for overcoming the limitations of traditional computing paradigms while operating at a fraction of the energy use. The process of designing Ising machines is known as the reverse Ising problem. Unfortunately, this problem is in general computationally intractable: it is a nonconvex mixed-integer linear programming problem which cannot be naively brute-forced except in the simplest cases due to exponential scaling of runtime with number of spins. We prove new theoretical results which allow us to reduce the search space to one with quadratic scaling. We utilize this theory to develop general purpose algorithmic solutions to the reverse Ising problem. In particular, we demonstrate Ising formulations of 3-bit and 4-bit integer multiplication which use fewer total spins than previously known methods by a factor of more than three. Our results increase the practicality of implementing such circuits on modern Ising hardware, where spins are at a premium.