Search for: All records

Accurately measuring the translations of objects between images is essential in many fields, including biology, medicine, chemistry, and physics. One important application is tracking one or more particles by measuring their apparent displacements in a series of images. Popular methods, such as the center of mass, often require idealized scenarios to reach the shot noise limit of particle tracking and, therefore, are not generally applicable to multiple image types. More general methods, such as maximum likelihood estimation, reliably approach the shot noise limit, but are too computationally intense for use in real-time applications. These limitations are significant, as real-time, shot-noise-limited particle tracking is of paramount importance for feedback control systems. To fill this gap, we introduce a new cross-correlation-based algorithm that approaches shot-noise-limited displacement detection and a graphics processing unit-based implementation for real-time image analysis of a single particle. 

In this paper, we discuss a technique for selectively loading a particle into a magneto-gravitational trap using the sublimation of camphor to release particles from a tungsten probe tip directly into the trapping region. This sublimation-activated release (SAR) loading technique makes use of micropositioners with tungsten probe tips, as well as the relatively fast rate of sublimation of camphor at room temperature, to selectively load particles having diameters ranging from 8 to 100 μm or more. The advantages of this method include its ability to selectively load unique particles or particles in limited supply, its low loss compared to alternative techniques, the low speed of the particle when released, and the versatility of its design, which allows for loading into traps with complex geometries. SAR is demonstrated here by loading a particle into a magneto-gravitational trap, but the technique could also be applicable to other levitated optomechanical systems.