Single-photon detection (SPD) is no longer rare. Consumer applications include 3D imaging in autonomous vehicles, tablets, and smartphones, and scientific applications include spectroscopy, optical microscopy, and quantum optics. Single-electron detection (SED) is also possible, but it is much less common. This talk will focus on how modeling at the level of individual detected particles inspires novel processing methods. Several improvements in lidar with SPD have been developed and experimentally realized. Theory and simulations suggest that SED can lead to great improvements in particle beam microscopy.
In single-photon lidar, when detector dead times are insignificant, Poisson process models can be used directly and lead to accurate depth and reflectivity imaging with as few as one detected photon per pixel. Under high ambient light or with high dynamic range of intensity, dead times are significant and create statistical dependencies that invalidate a Poisson process model. In this case, Markov chain modeling can mitigate the bias of conventional methods. In focused ion beam microscopy, modeling at the level of individual incident particles and detected secondary electrons inspires a new way to acquire and interpret the data. In both families of applications, old-school statistical modeling and estimation methods lead to significant imaging improvements.
Most relevant papers: 10.1126/science.1246775 10.1109/TCI.2015.2453093 10.1016/j.ultramic.2020.112948 10.1364/OPTICA.403190 10.1109/TCI.2021.3076887 10.1109/tci.2022.3182212 10.1109/JSAIT.2023.3283911
Tangential papers: 10.1364/OE.24.001873 10.1038/ncomms12046 10.1109/TCI.2017.2706028 10.1126/science.aat2298 10.1103/PhysRevA.99.063809 10.1109/TSP.2019.2916046 10.1109/TSP.2019.2914891 10.1109/TCI.2019.2913108 10.1109/MSP.2020.2983772 10.1364/OE.408800 10.1038/s41467-020-19727-4 10.1073/pnas.2024468118 10.1016/j.ultramic.2022.113662 10.1038/s41467-023-39327-2 10.1109/TCI.2023.3282042
Vivek Goyal received a BSE in electrical engineering and a BS in mathematics from the University of Iowa. After MS and PhD degrees in electrical engineering from the University of California, Berkeley, he was a Member of Technical Staff at Bell Laboratories, a Senior Research Engineer for Digital Fountain, and the Esther and Harold E. Edgerton Associate Professor of Electrical Engineering at MIT. His research group spawned 3dim Tech, winner of the 2013 MIT $100K Entrepreneurship Competition Launch Contest Grand Prize, and he was consequently with Google/Alphabet Nest Labs 2014-2016. He is now a Professor and Associate Chair of Doctoral Programs in the Department of Electrical and Computer Engineering at Boston University. Dr. Goyal is a Fellow of the AAAS, IEEE, and Optica, and he and his students have been awarded ten IEEE paper awards and eight thesis awards. He is a co-author of Foundations of Signal Processing (Cambridge University Press, 2014).