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MSE Seminar: “Predicting and Controlling Scalable Quantum Systems”
April 26 at 1:00 PM - 2:00 PM
Quantum materials host spectacular excited-state and nonequilibrium effects, but many of these phenomena remain challenging to control and, consequently, technologically underexplored. My group’s research, therefore, focuses on how quantum systems behave, particularly away from equilibrium, and how we can harness these effects. By creating predictive theoretical and computational approaches to study dynamics, decoherence and correlations in quantum systems, our work could enable technologies that are inherently more powerful than their classical counterparts ranging from scalable quantum information processing and networks, to ultra-high efficiency optoelectronic and energy conversion systems. In this talk, I will present work from my research group on describing, from first principles, the microscopic dynamics, decoherence and optically-excited collective phenomena in quantum matter at finite temperature to quantitatively link predictions with 3D atomic-scale imaging and quantum spectroscopy. Capturing these dynamics poses unique theoretical and computational challenges. The simultaneous contribution of processes that occur on many time and length-scales have remained elusive for state-of-the-art calculations and model Hamiltonian approaches alike, necessitating the development of new methods. I will show selected examples of our approach in ab initio design of active defects in quantum materials, and control of collective phenomena to link these active defects. Building on this, in the second part of my seminar, I will present promising physical mechanisms and quantum device architectures for coupling to other qubit platforms via dipole-, phonon-, and magnon-mediated interactions. Finally, I will discuss ideas in directly emulating quantum information systems, particularly addressing the issues of model abstraction and scalability, and present an outlook on various co-design strategies with algorithms efforts underway.
Register for the Zoom link here.
Assistant Professor of Computational Materials Science, Harvard University
Prineha Narang is an Assistant Professor at the John A. Paulson School of Engineering and Applied Sciences at Harvard University. Prior to joining the faculty, Prineha came to Harvard as a Ziff Fellow and worked as a Research Scholar in Condensed Matter Theory at the MIT Department of Physics. She received an M.S. and Ph.D. in Applied Physics from the California Institute of Technology (Caltech). Prineha’s work has been recognized by many awards and special designations including a National Science Foundation CAREER Award in 2020, being named a Moore Inventor Fellow by the Gordon and Betty Moore Foundation, CIFAR Azrieli Global Scholar by the Canadian Institute for Advanced Research, a Top Innovator by MIT Tech Review (MIT TR35), and a Young Scientist by the World Economic Forum in 2018. In 2017, she was named by Forbes Magazine on their “30under30” list for her work in quantum science and engineering. Outside of science, she is an avid triathlete and runner.