article published yes Mihika Prabhu author Charles Roques-Carmes author e2e68fc9-6505-11ef-a541-eb4e72cc3e82 Yichen Shen author Nicholas Harris author Li Jing author Jacques Carolan author Ryan Hamerly author Tom Baehr-Jones author Michael Hochberg author Vladimir Čeperić author John D. Joannopoulos author Dirk R. Englund author Marin Soljačić author Conventional computing architectures have no known efficient algorithms for combinatorial optimization tasks such as the Ising problem, which requires finding the ground state spin configuration of an arbitrary Ising graph. Physical Ising machines have recently been developed as an alternative to conventional exact and heuristic solvers; however, these machines typically suffer from decreased ground state convergence probability or universality for high edge- density graphs or arbitrary graph weights, respectively. We experimentally demonstrate a proof-of-principle integrated nanophotonic recurrent Ising sampler (INPRIS), using a hybrid scheme combining electronics and silicon-on-insulator photonics, that is capable of converging to the ground state of various four-spin graphs with high probability. The INPRIS results indicate that noise may be used as a resource to speed up the ground state search and to explore larger regions of the phase space, thus allowing one to probe noise-dependent physical observables. Since the recurrent pho- tonic transformation that our machine imparts is a fixed function of the graph problem and therefore compatible with optoelectronic architectures that support GHz clock rates (such as passive or non-volatile photonic circuits that do not require reprogramming at each iteration), this work suggests the potential for future systems that could achieve orders- of-magnitude speedups in exploring the solution space of combinatorially hard problems. Optica Publishing Group2020 eng 2334-253610.1364/optica.386613 75551-558 yes Prabhu, M., Roques-Carmes, C., Shen, Y., Harris, N., Jing, L., Carolan, J., … Soljačić, M. (2020). Accelerating recurrent Ising machines in photonic integrated circuits. <i>Optica</i>. Optica Publishing Group. <a href="https://doi.org/10.1364/optica.386613">https://doi.org/10.1364/optica.386613</a> Prabhu, Mihika, Charles Roques-Carmes, Yichen Shen, Nicholas Harris, Li Jing, Jacques Carolan, Ryan Hamerly, et al. “Accelerating Recurrent Ising Machines in Photonic Integrated Circuits.” <i>Optica</i>. Optica Publishing Group, 2020. <a href="https://doi.org/10.1364/optica.386613">https://doi.org/10.1364/optica.386613</a>. Prabhu, Mihika, et al. “Accelerating Recurrent Ising Machines in Photonic Integrated Circuits.” <i>Optica</i>, vol. 7, no. 5, Optica Publishing Group, 2020, pp. 551–58, doi:<a href="https://doi.org/10.1364/optica.386613">10.1364/optica.386613</a>. M. Prabhu <i>et al.</i>, “Accelerating recurrent Ising machines in photonic integrated circuits,” <i>Optica</i>, vol. 7, no. 5. Optica Publishing Group, pp. 551–558, 2020. Prabhu M, Roques-Carmes C, Shen Y, et al. Accelerating recurrent Ising machines in photonic integrated circuits. <i>Optica</i>. 2020;7(5):551-558. doi:<a href="https://doi.org/10.1364/optica.386613">10.1364/optica.386613</a> M. Prabhu, C. Roques-Carmes, Y. Shen, N. Harris, L. Jing, J. Carolan, R. Hamerly, T. Baehr-Jones, M. Hochberg, V. Čeperić, J.D. Joannopoulos, D.R. Englund, M. Soljačić, Optica 7 (2020) 551–558. Prabhu M, Roques-Carmes C, Shen Y, Harris N, Jing L, Carolan J, Hamerly R, Baehr-Jones T, Hochberg M, Čeperić V, Joannopoulos JD, Englund DR, Soljačić M. 2020. Accelerating recurrent Ising machines in photonic integrated circuits. Optica. 7(5), 551–558. 216402026-03-30T12:22:48Z2026-04-27T07:06:04Z