Programmable nanophotonics for quantum information processing and artificial intelligence

Thesis: Ph. D., Massachusetts Institute of Technology, Department of Electrical Engineering and Computer Science, 2017.Cataloged from PDF version of thesis.Includes bibliographical references.Over the past decade, progress in digital electronic computing systems has slowed as traditional, transistor-based silicon technologies approach their scaling limits. Quantum computing and non-Von Neumann computing architectures have emerged as promising alternatives for continued computational advancement-garnering significant investment and public interest. As a hardware platform, silicon photonics may play an important role in enabling quantum and classical information processing architectures. Here, I will discuss my thesis work on developing a programmable nanophotonic processor in silicon, as well as applications of this processor within the fields of quantum simulation, quantum computing, and deep learning. I will also cover results on environment-assisted quantum transport, deep learning with coherent nanophotonics, heralded single-photon sources, and highly integrable superconducting nanowire single-photon detectors.by Nicholas Christopher Harris.Ph. D