A recent paper, Femtojoule femtosecond all-optical switching in lithium niobate nanophotonics, was published in the Nature Photonics journal. In this paper, the Nonlinear Photonics Laboratory at Caltech developed a switch—one of the most fundamental components of computing—using optical, rather than electronic, components. By simultaneous engineering of the dispersion and quasi-phase matching in lithium niobate nanowaveguides, a nonlinear splitter was demonstrated to achieve ultralow switching energies down to 80 fJ, featuring a fastest switching time of ~46 fs and a record low energy–time product of 3.7×10^(-27) J⋅s. The development could aid efforts to achieve ultrafast all-optical signal processing and computing.

The Stanford Autonomous Systems Lab released a preprint on solving mixed-binary quadratic programs (MBQP) using Ising solvers. By exploiting a convex reformulation of MBQPs as copositive programs, the team designed a hybrid quantum-classical algorithm that (1) uses Ising solvers as a primitive with limited requirements on/knowledge of their optimality guarantees and (2) has polynomial complexity in the classical portions of the algorithm. Numerical experiments show that the algorithm (with simulated annealing) can outperform Gurobi on maximum clique instance, and the team expected further improvements given a state-of-the-art Ising solvers.

The Stanford Autonomous Systems Lab is excited to be sharing work on Copositive Optimization via Ising Solvers at the 19th International Conference on the Integration of Constraint Programming, Artificial Intelligence, and Operations Research.