Complexity Theory and its Applications in Linear Quantum Optics
  This thesis is intended in part to summarize and also to contribute to the newest developments in passive linear optics that have resulted, directly or indirectly, from the somewhat shocking discovery in 2010 that the BosonSampling problem is likely hard for a classical computer to simulate. In doing so, I hope to provide a historic context for the original result, as well as an outlook on the future of technology derived from these newer developments. An emphasis is made in each section to provide a broader conceptual framework for understanding the consequences of each result in light of the others. This framework is intended to be comprehensible even without a deep understanding of the topics themselves.   The first three chapters focus more closely on the BosonSampling result itself, seeking to understand the computational complexity aspects of passive linear optical networks, and what consequences this may have. Some effort is spent discussing a number of issues inherent in the BosonSampling problem that limit the scope of its applicability, and that are still active topics of research. Finally, we describe two other linear optical settings that inherit the same complexity as BosonSampling. The final chapters focus on how an intuitive understanding of BosonSampling has led to developments in optical metrology and other closely related fields. These developments suggest the exciting possibility that quantum sensors may be viable in the next few years with only marginal improvements in technology. Lastly, some open problems are presented which are intended to lay out a course for future research that would allow for a more complete picture of the scalability of the architecture developed in these chapters. 
Jonathan Olson
quant-ph