The field of Quantum Information Science (QIS) is revolutionizing technologies that range from timing, sensing, networks, to communications, with critical relevance to the Department of Air Force and the Department of Defense. QIS will enable strategic advantages, particularly for position, navigation and timing (PNT). For compact, deployable quantum systems that perform at room temperature, qubits based on solid-state materials represent a highly manufacturable, robust system which can be integrated with nano-electronics and nano-photonics. Next-generation PNT needs that can be addressed by QIS include:
It is important to note that each application requires unique qubit performance considerations. In the past, solid-state quantum defect developments have focused on ad-hoc material concepts for forward design, finding useful responses from newly discovered qubits. At the same time, the recent confluence in development of high-throughput computation leveraging artificial intelligence (AI)/machine learning (ML) algorithms, along with the generation of databases that include first principles computed properties of bulk and 2D materials, has been extensively used for materials discovery through inverse design [1]. This talk will motivate a rational design concept in materials defect design to enable quantum functionalities that will meet the stringent Department of the Air Force requirements in PNT. This goal can be realized by using inverse design in an iterative approach that will identify promising defects in emerging materials, integrated with developing capabilities for tailor-designed defects through deterministic manipulation of atoms and vacancies.
Luke Bissell received his PhD from the Institute of Optics at the University of Rochester in 2011, under Carlos Stroud and Svetlana Lukishova. His thesis research focused on the applications of single nanoparticles for quantum information. In 2006, he was a recipient of the DoD SMART fellowship. At the Air Force Research Laboratory, he has studied the use of quantum dots, metal nanoparticles, and color centers in bulk and nano-diamond for next-generation photodetectors and quantum sensors. His work is also focused on ab initio modeling and characterization of color centers in diamond and SiC for novel quantum information applications. His expertise includes spectral ellipsometry, fluorescence spectroscopy, using confocal microscopy and time-correlated single-photon counting to measure fluorescence antibunching and fluorescence lifetimes, and the preparation of chiral and nematic liquid crystals.
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