中国科学院理论物理研究所 

报告摘要：

The development of electronic structure methods such as density functional theory (DFT) and the GW approximation has been driven by the quest for a universal theory capable of accurately predicting material properties. Despite the significant progress made by these methods, a unified framework that consistently describes diverse materials with high precision remains an ongoing challenge. In this talk, we will investigate the potential of effective field theory (EFT) principles to provide a systematic foundation for electronic structure theory, focusing on correlation effects in the electron liquid and its applications in first-principles calculations. We will present our field-theoretical approach that addresses the quasiparticle effective mass puzzle and the long-standing missing Coulomb pseudopotential problem. By deriving the microscopic definition of the pseudopotential using an EFT analysis of electron-phonon superconductivity and calculating the previously unknown pseudopotential μ*, we aim to improve the accuracy of superconducting temperature predictions in low-temperature metals. Furthermore, we will introduce our AI for EFT framework, which explores the application of AI techniques to systematically solve many-body field theories. By working towards a rigorous EFT foundation and leveraging AI, we seek to contribute to the advancement of electronic structure theory, enhancing its accuracy, applicability, and predictive power, with the ultimate goal of facilitating the rational design of materials with targeted properties.

报告人简介：

陈锟是中国科学院理论物理研究所副研究员。他致力于发展非局域有效场论，探索材料多电子问题的新型理论基础，并积极将人工智能引入量子场论研究。陈锟先后在中国科学技术大学、合肥微尺度国家实验室和美国马萨诸塞州立大学获得学士和博士学位。博士后期间，他先后在罗格斯大学和Flatiron研究所从事电子关联效应等凝聚态基础问题研究。他曾获郭沫若奖、吴杭生教授纪念奖、中国科学院院长奖特别奖等荣誉。

邀请人：吴泉生 特聘研究员

联系人：王慧颖 why@iphy.ac.cn

报告地点：怀柔园区MA楼505会议室

腾讯会议：977-350-034

会议密码：2024

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