Control and Calibration Strategies for Quantum Simulation

Paul Kairys, University of Tennessee and Oak Ridge National Laboratory
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Abstract: Key to the continued development of chemical, material, and information sciences is the modeling and prediction of quantum mechanical phenomena. While classical computing methods are generally inefficient for such tasks, quantum simulation offers an alternative paradigm where a programmable quantum device is used to emulate the phenomena of an otherwise distinct physical system. Unfortunately, imperfect construction and operation of quantum simulators introduces challenges preventing their widespread adoption. This talk will discuss strategies for mitigating these challenges by implementing quantum simulation using device control and calibration. First, an example of the benefits of calibration and control on simulator performance is provided through a case study on simulating the Shastry-Sutherland Ising model using quantum annealing. Motivated by the increased precision and accuracy provided by such strategies, a paradigm for parameterized Hamiltonian simulation using quantum optimal control is proposed and routes for optimal control objective function engineering are discussed. Next, we assess the feasibility of using optimal control for simulation of dynamical, topological phenomena in scalable device architectures. Specifically, we describe ongoing work to utilize quantum optimal control to realize the quantum simulation of string order melting in superconducting quantum devices. Finally, routes for future work are proposed and discussed.

Bio: Paul Kairys received a B.Sc. in Chemical Engineering from the University of South Florida. In 2018, Paul was awarded an Energy Science Fellowship and began a Ph.D. studying quantum computing at the University of Tennessee, Knoxville and Oak Ridge National Laboratory. In 2020 and 2021, Paul was awarded the Tennessee Science Alliance Student Mentoring and Research Training (SMaRT) Fellowship. Paul's research focus is the development and implementation of quantum simulation techniques for material science, chemistry, and physics. Paul is broadly interested in the intersection of quantum information theory, device engineering, and computational science.

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