Abstract：

This talk presents a comprehensive survey of electron correlations in the electron gas across diverse parameter regimes, revealing the interplay of electron-electron, electron-ion, and ion-ion effective interactions below the Fermi scale. A tailored electron field theory for the electron gas, coupled with a novel AI-driven solver, enables calculations of many-electron correlations beyond traditional methods, allowing us to systematically investigate these correlations via two-electron correlation functions across the warm dense and low-temperature superconducting regimes. Examining the exchange-correlation kernel—a central quantity for understanding these effective interactions—across a wide temperature range reveals its spatial structure and elucidates the crossover from classical to quantum fluctuations, including a high-temperature scaling relation. These results provide crucial input for ab initio modeling of electron correlations in warm dense matter. Focusing on the low-temperature electron-electron interaction in the Cooper channel, we employ our solver to calculate the Cooper pair scattering amplitude in the uniform electron gas. This allows us to precisely determine the previously unknown first-principles Coulomb pseudopotential (μ*), a key input for ab initio calculations of superconductivity within the Eliashberg theory, resolving the “missing Coulomb pseudopotential” problem. We also address the predicted breakdown of the Eliashberg formalism at extreme densities.

报告人简介：

陈锟，中国科学院理论物理研究所副研究员。专注于人工智能、量子多体等交叉领域中的涌现现象与机制研究。他在中国科学技术大学获得学士学位，随后在合肥微尺度国家实验室和美国马萨诸塞州立大学获得量子信息科学和凝聚态物理博士学位。博士后期间，获西蒙斯基金会多电子问题国际合作项目的支持，先后在罗格斯大学和Flatiron研究所开展研究。受国家级青年人才计划支持，任国家重点研发专项课题负责人。