Conventional computing architectures currently have no known efficient algorithms for combinatorial optimization tasks such as the Ising problem. We present an 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. Our architecture is compatible with optoelectronic components operating at GHz clock rates, thereby suggesting the potential for future systems that could achieve orders-of-magnitude speedups in exploring the solution space of combinatorially hard problems.

Mihika Prabhu received her BS in Physics and Electrical Engineering from MIT in 2015. She was a recipient of the 2016 NSF Graduate Research Fellowship, completed an MS in Electrical Engineering and Computer Science at MIT in 2018, and is currently a PhD candidate in the Department of Electrical Engineering and Computer Science at MIT.

Registration is closed.