Measurement of the faintest signals has become a vital part of disciplines as diverse as medicine, astronomy, interplanetary communications and intelligence gathering. While our curiosity has driven us to probe ever-weaker signals in Nature, the framework and philosophy for our measurement tools has remained largely unchanged for centuries, entrenched in a classical interpretation of our world – which we know to be incomplete. In this talk I will present a holistic approach to sensing which combines quantum mechanics, information theory and measurement. We will explore the fundamental differences between a classical and quantum understanding of weak signals. With a quantum representation of Nature, applying a quantum information theoretic analysis can inspire paradigmatic shifts in the design of measurement tools. We will explore several examples where a quantum theoretic approach to sensing has resulted in radical improvements in our ability to detect and characterize photon-starved signals. In unison with the technical portion of this talk, I will provide an impassioned argument that both quantum mechanics and information theory are vital to understanding our natural world and should become mainstream curriculum in the undergraduate education across all disciplines.
Jonathan L. Habif is an experimental physicist and research lead and research professor at the University of Southern California information Sciences Institute (ISI). Professor Habif holds a bachelor’s degree in physics from Colgate University an M.S. and Ph.D. from the University of Rochester in electrical and computer engineering and applied physics. He conducted postdoctoral work in the Research Laboratory for Electronics (RLE) at MIT. His recent research has focused on photon-starved, classical communication and imaging, quantum-secured optical communications in free-space and fiber, and integrated nano-photonic for both classical and non-classical applications. Prof. Habif leads USC’s Laboratory for Quantum-Limited Information (QLIlab) located outside Boston, MA. The QLIlab is dedicated to understanding and demonstrating the fundamental limits for extracting information from physical signals.