报告题目：量子计算的硬件-软件协同设计推进
报告人：牛思远 博士
报告人单位：Lawrence Berkeley National Lab.
主持人：盛继腾 教授
时间：2024年12月26日（周四）上午11:00
地点：光学大楼A508会议室
个人简介：
Siyuan Niu is currently a postdoctoral fellow in the Computational Research Division at LawrenceBerkeley National Lab. She received her PhD from the Department of Microelectronics at LIRMM,University of Montpellier, France, her Master’s in Electrical Engineering from Polytech NiceSophia, France, and her Bachelor’s from Xidian University, China. Her research focuses onquantum computing, specifically on quantum compilation, quantum error mitigation and correction,quantum algorithm optimization, and benchmarking and characterization of quantum systems. Herresearch has been published in leading journals and conferences in the field of quantum computing,including Quantum, Quantum Science and Technology, IEEE Transactions on QuantumEngineering, DAC, ICCAD, DATE, etc. She is currently a member of the Berkeley QuantumSynthesis Toolkit (BQSKit) team, contributing to a powerful open-source framework for quantumcompilation, with over 100,000 downloads. She received quantum credits grants from MicrosoftAzure and IonQ for hardware access to support her research projects in 2022. She was one of thewinners of the IBM Open Science Challenge in 2021 and was selected as a DAC Young Fellow thesame year.
报告简介：
Quantum computing is an emerging and rapidly developing field, with significant advancements inboth quantum hardware and algorithms in recent years. However, the inherent noise in quantumhardware poses substantial challenges, hindering the realization of practical quantum applicationsand advantages. In this presentation, I will address these challenges through hardware-software codesign strategies. First, I will present some circuit optimization methods with mid-circuitmeasurement and feed-forward loop. Second, I will introduce a quantum multi-programmingmechanism that enables the parallel execution of multiple quantum circuits, enhancing hardwareutilization and reducing overall runtime. Third, I will discuss a practical and resource-efficient errormitigation technique designed to reduce crosstalk and decoherence errors by employing noveldynamical decoupling strategies. These software optimizations aim to better harness the capabilitiesof current quantum hardware, bringing us closer to realizing practical quantum computingapplications.