Integrating model development across computational neuroscience, cognitive science, and machine learning.

Neuroscience, cognitive science, and computer science are increasingly benefiting through their interactions. This could be accelerated by direct sharing of computational models across disparate modeling software used in each. We describe a Model Description Format designed to meet this challenge.

Modeling and correction of fringe patterns in Doppler asymmetric spatial heterodyne interferometry.

Doppler asymmetric spatial heterodyne (DASH) interferometry is a novel concept for observing atmospheric winds. This paper discusses a numerical model for the simulation of fringe patterns and a methodology to correct fringe images for extracting Doppler information from ground-based DASH measurements. Based on the propagation of optical waves, the fringe pattern was modeled considering different angular deviations and optical aberrations.

Interferometric grazing incidence test of rough steep convex aspherics: full 3D reconstruction of the object.

A grazing incidence interferometric measurement procedure is applied to test rough convex steep rotationally symmetric aspherics. The measurement of rough surfaces is possible; i.e.

Absolute characterization of high numerical aperture microscope objectives utilizing a dipole scatterer.

Measuring the aberrations of optical systems is an essential step in the fabrication of high precision optical components. Such a characterization is usually based on comparing the device under investigation with a calibrated reference object. However, when working at the cutting-edge of technology, it is increasingly difficult to provide an even better or well-known reference device.