报告摘要：

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 mitigated 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.

Robert Joynt is Emeritus Professor of Physics at the University of Wisconsin-Madison, where he has also served as Department Chair. His research has ranged from the quantum Hall effect to high-Tc superconductivity, the quantum adiabatic algorithm, decoherence from evanescent-wave Johnson noise, and new designs for qubit devices.

Prof. Joynt is the founder and director of the MSc program in Quantum Computing at UW-Madison, which began in 2019. This was the first degree program in quantum computing in the US.

报告人简介：

Robert Joynt is Emeritus Professor of Physics at the University of Wisconsin-Madison, where he has also served as Department Chair. His research has ranged from the quantum Hall effect to high-Tc superconductivity, the quantum adiabatic algorithm, decoherence from evanescent-wave Johnson noise, and new designs for qubit devices.

Prof. Joynt is the founder and director of the MSc program in Quantum Computing at UW-Madison, which began in 2019. This was the first degree program in quantum computing in the US.