[Seminar] Prof. Robert Joynt "Adaptive quantum optimization algorithms for ising-like models"

One of the most promising types of quantum algorithms are those that solve combinatorial optimization problems.  There are a number of difficulties that stand in the way:  small gaps to excited states, barren plateaus in the energy, and incomplete expressibility of the states.  These obstacles can be dealt with by making the quantum algorithms adaptable.  I will describe several ways to do this, and show that considerable improvements over non-adaptive algorithms are possible.

Biography

Robert Joynt received his Ph.D. from the University of Maryland in 1982 and was a postdoctoral fellow at the Cavendish Laboratory of the University of Cambridge and the Institute for Theoretical Physics at ETH-Zurich. He was Professor of Physics at the University of Wisconsin-Madison from 1986 to 2023 and is now Emeritus Professor. He served as Department Chair and was the Founding Director of the MSc in Physics-Quantum Computing. He is Senior Fellow at the Kavli Institute for Theoretical Sciences in Beijing. His research has ranged from the quantum Hall effect to high-Tc superconductivity to neutron stars to quantum computing.

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