Dr. Yanzhu Chen
Virginia Tech
Moving the Barrier to Practical Quantum Computing on Two Fronts
Location: 1080 Physics Research Building
Faculty Host: Dan Gauthier
Abstract: Quantum computing has long promised to speed up certain tasks that are intractable on classical computers. However, quantum devices are inherently noisy, with coherence times limited by unwanted interactions between the quantum processor and its environment. Overcoming this limitation requires new techniques for recovering useful information from quantum computations despite the noise, as well as new algorithms with enhanced speed and resource efficiency. In this talk, I will describe recent advances on both these fronts. First, I will present a new class of adaptive, quantum-classical hybrid algorithms that outperform previous quantum simulation algorithms in terms of both speed and resources, bringing practical quantum computing on near-term devices closer to reality. Then I will present a new method for characterizing and mitigating correlated noise, a ubiquitous and especially challenging type of noise that evades most existing error mitigation strategies.
Bio: Yanzhu Chen is a postdoc in the Physics Department and Center for Quantum Information Science and Engineering at Virginia Tech. She received her PhD from Stony Brook University, supervised by Prof. Tzu-Chieh Wei, and joined Virginia Tech in 2021, working with Prof. Sophia Economou and Prof. Edwin Barnes. Yanzhu is interested in quantum algorithms, noise in quantum computing, measurement based quantum computing, and quantum control. Her current works focus on properties and improvements of adaptive variational quantum algorithms and protocols of mitigating errors in quantum information processing.