Quantum sensors are sensing devices that exploit quantum phenomena in such a way that makes them perform substantially better than their classical counterparts. This course uses an information-theoretic approach to identify and explain the basic design principles and potential applications of quantum sensors. A primary goal of the course is to describe those aspects of quantum phenomena that can be harnessed in order to design and develop novel sensing devices. To this end, the course summarizes recent theoretical and experimental results that showcase the feasibility of quantum sensors. In addition, the course compares the theoretical performance of quantum sensors with their classical counterparts in the areas of radar, lidar, photo-detection, magnetometry, and gravimetry.

Quantum computing, one of the most recent joint ventures between physics and the theory of computation, can be defined as the scientific field whose purpose is to develop hardware and algorithms based on quantum mechanical phenomena. In addition to further advance the mathematical and physical foundations of quantum computing, scientists and engineers who work in this field focus on developing cutting-edge quantum algorithms in areas like artificial intelligence, cryptanalysis, machine learning, database search, chemical simulations, and image processing. The course summarizes recent theoretical and experimental results that showcase the feasibility of large-scale quantum computation. In addition, the course describes the potential applications of quantum computing to signal analysis, sensor fusion, and computer vision.