**Length:** 3 hours

**Intended Audience:** For students, engineers and scientists

a) with an interest in modern applications of quantum science in the areas of sensor fusion, artificial intelligence/machine learning/computing, and communication/information, and/or

a) seeking an understanding of the potential near-term and long-term impacts of the emerging quantum technologies on sensor and information fusion and the Internet of Everything

**Description:** Quantum physics and relativity are the basis of all known fundamental laws of the universe. Although the fundamentals of quantum physics have been well-known since the 1920s, in the last few decades several novel consequences of the laws of quantum physics (particularly, in the areas of atomic, molecular and optical physics and quantum computer science and information theory) have been discovered. These developments have attracted the interest of major civilian and defence industries. In particular, in the areas of sensing, quantum physics sets the bounds on the sensitivity of sensing --- termed the Heisenberg limit --- that is orders of magnitude below the sensitivity of current sensors. In the area of computing, it has been observed that a quantum computer allows some computations to be carried out that are unfeasible using current or future classical computing technology. In the area of communication, quantum physics enables provable secure communication and at much higher data rates than those allowed by classical Shannon limit. Many of these advances could have major near-term and long-term consequences in the areas of sensing, secure communication, big data analysis, and machine learning, and hence sensor and information fusion.

**Prerequisites:** Some background of linear algebra is assumed, and for some topics a rudimentary knowledge of
simple differential equations. No knowledge of quantum physics is assumed.

**Presenter:** Bhashyam Balaji

**Bhashyam Balaji** is a Senior Defence Scientist at Defence R&D Canada, and a Senior Member of IEEE. He obtained his Ph.D. in elementary particle theory from Boston University. He has published over 60 technical articles, many in areas related to application of quantum physics methods (particularly the Feynman path integral methods of quantum field theory), to nonlinear filtering theory. His other research interests include all aspects of radar sensor outputs, including space-time adaptive processing, multi-target tracking, and meta-level tracking including the application of stochastic context-free grammars to syntactic tracking. His recent research also includes theoretical and applied aspects of multisource data fusion, including tracking and fusion of sensor outputs from radar, EO/IR, acoustic, electronic support measures, and magnetic anomaly detection sensors and quantum science and technologies for fusion. He has been an invited speaker to military radar conferences where has also presented tutorials on radar signal processing and multi-target tracking.