Recent developments in AR & VR hardware have resulted in a range of nascent commercial products, e.g. the Microsoft Hololens and DAQRI smart helmet (augmented reality), Occulus Rift and HTC Vive (virtual reality). Laboratory use is an obvious application of current tether-free AR technology, which could enable new experimental methodologies as well as offer basic procedural, efficiency, training and health and safety benefits. VR technology, which typically requires tethering to a high-performance PC, provides a complementary platform, more suited to fully immersive computational uses such as multi-dimensional data visualization and big data applications.
Early work with the Hololens, investigating 3D visualization and basic lab usage, has already begun in the group; this project would further work to explore and develop these capabilities.
New on the arxiv:
ePSproc: Post-processing suite for ePolyScat electron-molecule scattering calculations
ePSproc provides codes for post-processing results from ePolyScat (ePS), a suite of codes for the calculation of quantum scattering problems, developed and released by Luchesse & co-workers (Gianturco et al. 1994)(Natalense and Lucchese 1999)(R. R. Lucchese and Gianturco 2016). ePS is a powerful computational engine for solving scattering problems, but its inherent complexity, combined with additional post-processing requirements, ranging from simple visualizations to more complex processing involving further calculations based on ePS outputs, present a significant barrier to use for most researchers. ePSproc aims to lower this barrier by providing a range of functions for reading, processing and plotting outputs from ePS. Since ePS calculations are currently finding multiple applications in AMO physics (see below), ePSproc is expected to have significant reuse potential in the community, both as a basic tool-set for researchers beginning to use ePS, and as a more advanced post-processing suite for those already using ePS. ePSproc is currently written for Matlab/Octave, and distributed via Github: https://github.com/phockett/ePSproc.