A single shot coherent Ising machine based on a network of injection-locked multicore fiber lasers

Masoud Babaeian,Dan T Nguyen,Mark A Neifeld,Yushi Kaneda,Mehmetcan Akbulut,Veysi Demir,N Peyghambarian,Pierre-A Blanche,Saikat Guha

doi:10.1038/s41467-019-11548-4

Masoud Babaeian, Dan T Nguyen + Show 7 more

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https://doi.org/10.1038/s41467-019-11548-4

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Combinatorial optimization problems over large and complex systems have many applications in social networks, image processing, artificial intelligence, computational biology and a variety of other areas. Finding the optimized solution for such problems in general are usually in non-deterministic polynomial time (NP)-hard complexity class. Some NP-hard problems can be easily mapped to minimizing an Ising energy function. Here, we present an analog all-optical implementation of a coherent Ising machine (CIM) based on a network of injection-locked multicore fiber (MCF) lasers. The Zeeman terms and the mutual couplings appearing in the Ising Hamiltonians are implemented using spatial light modulators (SLMs). As a proof-of-principle, we demonstrate the use of optics to solve several Ising Hamiltonians for up to thirteen nodes. Overall, the average accuracy of the CIM to find the ground state energy was ~90% for 120 trials. The fundamental bottlenecks for the scalability and programmability of the presented CIM are discussed as well.

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Combinatorial optimization problems over large and complex systems have many applications in social networks, image processing, artificial intelligence, computational biology and a variety of other areas
The number of slave lasers (SLs) represent the number of nodes in the Ising Hamiltonian, and they are locked by a single frequency master laser (ML) with vertical linear polarization
We begin with deriving nonlinear coupled photon rate equations describing the dynamics of a network of injectionlocked lasers for the average photon numbers in the left and Master laser Isolator

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Introduction

Combinatorial optimization problems over large and complex systems have many applications in social networks, image processing, artificial intelligence, computational biology and a variety of other areas. Finding the ground state spin configuration of the general Ising Hamiltonian is known to be an NP-hard problem (for three dimensions, as well as two dimensions with the Zeeman term):[55] At the same time by enabling the cross links between SLs, the mutual-coupling terms in the Ising Hamiltonian are turned on.

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