德国 DESY

摘要：

Variational Quantum Algorithms (VQAs) are powerful tools for solving combinatorial optimization problems on near-term quantum devices. In this talk, I will compare quantum optimization algorithms inspired by real-time and imaginary-time evolution, presenting our work on improving their performance.

While the Quantum Approximate Optimization Algorithm (QAOA) is widely used, its high circuit depth and measurement demands limit hardware efficiency. In contrast, the Variational Quantum Eigensolver (VQE) offers more flexible ansatz design and shallower circuits. I will present our structure-inspired ansatz (SIA) and warm-start method, which enable efficient parameter initialization and address challenges like barren plateaus and statistical errors.

报告人简介：

柴雅卉，现任德国DESY博士后研究员。2016年毕业于中国科学技术大学，获理论物理学士学位；2021年于北京大学获得理论物理博士学位，师从刘川教授。自2023年起，在德国DESY从事博士后研究工作。其研究领域涵盖量子计算在粒子物理、多体物理及组合优化问题中的应用，以及相关算法的优化。

地点：M 楼 253 会议室