Search for: All records

We apply the Nb=1 solution of the Rapidly Decaying Fourier series to fit mid-spatial frequency surface errors. Using this basis enables definition of sharp spatial frequency bandlimits for mid-spatial frequency specification of optical surfaces. 

We apply the Nb=1 solution of the Rapidly Decaying Fourier series to fit mid-spatial frequency surface errors. Using this basis enables definition of sharp spatial frequency bandlimits for mid-spatial frequency specification of optical surfaces. 

Abstract Structured waves are ubiquitous for all areas of wave physics, both classical and quantum, where the wavefields are inhomogeneous and cannot be approximated by a single plane wave. Even the interference of two plane waves, or of a single inhomogeneous (evanescent) wave, provides a number of nontrivial phenomena and additional functionalities as compared to a single plane wave. Complex wavefields with inhomogeneities in the amplitude, phase, and polarization, including topological structures and singularities, underpin modern nanooptics and photonics, yet they are equally important, e.g., for quantum matter waves, acoustics, water waves, etc. Structured waves are crucial in optical and electron microscopy, wave propagation and scattering, imaging, communications, quantum optics, topological and non-Hermitian wave systems, quantum condensed-matter systems, optomechanics, plasmonics and metamaterials, optical and acoustic manipulation, and so forth. This Roadmap is written collectively by prominent researchers and aims to survey the role of structured waves in various areas of wave physics. Providing background, current research, and anticipating future developments, it will be of interest to a wide cross-disciplinary audience. 

Advancements in Artificial Intelligence (AI), Information Technology, Augmented Reality (AR) and Virtual Reality (VR), and Robotic Automation is transforming jobs in the Architecture, Engineering and Construction (AEC) industries. However, it is also expected that these technologies will lead to job displacement, alter skill profiles for existing jobs, and change how people work. Therefore, preparing the workforce for an economy defined by these technologies is imperative. This ongoing research focuses on developing an immersive learning training curriculum to prepare the future workforce of the building industry. In this paper we are demonstrating a prototype of a mobile AR application to deliver lessons for training in robotic automation for construction industry workers. The application allows a user to interact with a virtual robot manipulator to learn its basic operations. The goal is to evaluate the effectiveness of the AR application by gauging participants' performance using pre and post surveys. 

We present the definition of a new quantity, the pupil difference probability density (PDPD), and describe its use in the study of imaging systems. Formally, the PDPD is defined as the probability density that two random points over the pupil, with given separation, have a given wavefront error difference. Under this definition, the PDPD is the one-dimensional Fourier transform, of the error difference variable, of the OTF. Using the PDPD, we show that it is possible to understand how certain sources of error affect the OTF. Further, given its geometric interpretation, this formalism is useful for finding accurate analytic approximations to the OTF.