Optical trapping below the diffraction limit with a tunable beam waist using super-oscillating beams.

Super-oscillating beams can be used to create light spots whose size is below the diffraction limit with a side ring of high intensity adjacent to them. Optical traps made of the super-oscillating part of such beams exhibit superior localization of submicron beads compared to regular optical traps. Here we focus on the effect of the ratio of particle size to beam size on the localization and stiffness of optical traps made of super-oscillating beams.

Use of machine learning methods to reduce predictive error of groundwater models.

Quantitative analyses of groundwater flow and transport typically rely on a physically-based model, which is inherently subject to error. Errors in model structure, parameter and data lead to both random and systematic error even in the output of a calibrated model. We develop complementary data-driven models (DDMs) to reduce the predictive error of physically-based groundwater models.

Human-Android Interaction in the Near and Distant Future.

In this article, a psychologist and an artificial-intelligence (AI) researcher speculate on the future of social interaction between humans and androids (robots designed to look and act exactly like people). We review the trajectory of currently developing robotics technologies and assess the level of android sophistication likely to be achieved in 50 years time. On the basis of psychological research, we consider obstacles to creating an android indistinguishable from humans.