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报告人：Mikhail Skvortsov，Landau Institute for Theoretical Physics, Russian Academy of Sciences
时间：4月29日（周三）15:00
单位：中国科学院理论物理研究所
地点：南楼6620
摘要:
We develop a full microscopic theory for the optical conductivity, σ(ω), of a dirty current-carrying superconductor. Within the Keldysh sigma model formalism, we obtain the general analytical expression for σ(ω), applicable for arbitrary frequency ω, temperature T, and dc supercurrent I. In addition to altering the usual Mattis-Bardeen conductivity, a finite supercurrent introduces two new contributions: σqp(ω) from quasiparticle redistribution and σSH(ω) from the amplitude (Schmid-Higgs) mode excitation by the ac field. We investigate, both analytically and numerically, the main features of the optical conductivity in the presence of a dc supercurrent. They include a peak in Re σ(ω) above the optical gap and a sign change of Im σ(ω), with both effects becoming more pronounced at higher I and lower T. We also elucidate the role of inelastic relaxation, which governs the low-frequency response, leading to a giant microwave absorption and a suppression of the apparent superfluid density at the critical current. The optical conductivity measurement of a superconductor biased by a finite dc supercurrent enables the direct observation of the Schmid-Higgs mode via transport measurements.
报告人简介:
Mikhail Skvortsov graduated from the Moscow Institute of Physics and Technology in 1995 and got his PhD in 1998. Since then, he has been continuously employed at the Landau Institute for Theoretical Physics. From 2014 to 2021, he served as an Associate Professor at the Skolkovo Institute of Science and Technology. M. A. Skvortsov is a recognized specialist in the physics of disordered and superconducting systems. His key scientific contributions include explaining the giant fluctuation Nernst effect in superconductors, investigating ergodicity and localization on random regular graphs, developing the Keldysh action approach for disordered superconductors, describing the inhomogeneous state in dirty superconductors, constructing the theory of dynamical localization in quantum dots under periodic driving, characterizing the statistics of the never-falling trajectory in the random Whitney problem.
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报告人：Gu Zhang，Nanjing University
时间：4月29日（周三）15:00
单位：北京大学物理学院
地点：西563会议室
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报告人：Tom Kroktsch，University of Hamburg
时间：4月30日（周四）15:00
单位：中国科学院理论物理研究所
地点： 南楼6520
摘要:
The spectrum of gravitational waves emitted throughout the history of the universe is known to extend to frequencies much higher than current large-scale detectors are exploring. Therefore, several projects are now under way to survey high-frequency gravitational waves (HFGWs). First, I will give an overview on the physics potential of HFGW detection for BSM physics and cosmology. Then, I will motivate microwave cavities as novel tools for HFGW searches and introduce an ongoing DESY/Uni Hamburg/FNAL project to use the superconducting 'MAGO' cavity as such a detector. Last, I will discuss synergies with searches for axion-like dark matter to cover even higher frequency ranges.
报告人简介:
Tom Kroktsch received his Bachelor' s degree in Physics from the University of Hamburg in 2022, followed by a Master' s degree in Applied Mathematics from the University of Cambridge in 2023. Since 2023, he has been pursuing his PhD in Theoretical Physics at the University of Hamburg under the supervision of Gudrid Moortgat-Pick.
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报告人：颜世申，山东大学物理学院
时间：4月30日（周四）15:00
单位：北京大学物理学院
地点： 物理大楼中楼212报告厅
摘要:
在自旋电子学中，电荷流与自旋流的相互转换是重要的研究课题，利用自旋流驱动磁性层的磁化翻转是当前的研究前沿和热点。传统自旋轨道力矩器件通常依赖于重金属（如Ta、Pt、W等）的自旋霍尔效应来实现电荷流到自旋流的转变，而近年来，轨道流及其轨道矩，以及自旋涡度耦合效应引起了广泛关注。本研究旨在探索能否利用自旋涡度耦合效应驱动磁化翻转。我们在PtCo/Cu双层膜中发现了巨大的类阻尼轨道矩效率，随Cu厚度增加最高达18×10⁵ (Ωm)⁻¹，比典型Ta系材料高两个数量级，同时驱动CoPt磁化翻转的临界电场显著降低。实验和理论表明，该超高效率源于Cu与PtCo层电子的面内迁移率在膜厚方向的梯度引起的自旋涡度耦合。本研究填补了利用自旋涡度耦合实现磁化翻转的空白，为低功耗自旋电子器件提供了新路径。
报告人简介:
颜世申，山东大学物理学院教授、博士生导师，济南大学自旋电子学研究所所长。曾任山东大学物理学院副院长、学术委员会主任等职。他还是国家杰出青年基金获得者、山东省杰出青年基金获得者、教育部新世纪优秀人才、德国洪堡学者。曾获山东省自然科学一等奖，被评为山东省有突出贡献的中青年专家。研究领域是自旋电子学，研究方向包括人工神经形态计算、自旋轨道矩翻转磁化强度、自旋微波振荡器、电场调控磁性、整流磁电阻等。作为课题负责人完成国家973课题、国家杰出青年基金项目、国家自然科学基金重点项目、111引智计划、军工重大项目等近20项。已获得国家发明专利授权15项，发表SCI论文200多篇；部分成果已被写进了教科书和特邀综述文章，并被许多研究组广泛采用。
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报告人：Donghui Quan，西安交通大学利物浦大学
时间：4月23日（周四）15:30
单位：北京大学物理学院
地点： KIAA-auditorium
摘要:
Understanding the origin and evolution of molecular complexity in the interstellar medium is one central problem in astrophysics and astrochemistry. This field has advanced through traditional approaches, including chemical reaction networks, rate-equations, gas-grain modeling, quantum mechanical calculations, and radiative-transfer-based spectral analysis. These methods have provided the essential foundation for interpreting how molecules form and evolve in different astrophysical environments. However, with the rapid growth of modern observational data from facilities such as ALMA and JWST, the field is increasingly challenged by severe line confusion, incomplete reaction networks, and the difficulty of extracting robust physical and chemical information from complex spectra.In this talk, I will present our recent efforts to build on traditional modeling and incorporate AI-enabled methods for exploring molecular complexity in the interstellar medium. This framework combines physics-based modeling with new data-driven and machine-learning tools for reaction-network expansion, multiphase chemical evolution, and automated spectral-line identification. I will discuss how recent developments such as ChemiVerse, GraSSCoL, and Spectuner can be integrated with traditional modeling strategies to build a more scalable and interconnected framework linking reaction pathways, abundance evolution, synthetic spectra, and observational inference. By combining traditional modeling with AI-enabled methods, we aim to improve the efficiency and reliability of molecular identification and to support more systematic studies of molecular complexity in the interstellar medium. The broader goal is to develop a more predictive framework for understanding how complex, and potentially prebiotic, molecules form and evolve in space.
报告人简介:
Donghui Quan is Professor of Physics in the School of Mathematics and Physics at Xi’an Jiaotong-Liverpool University. He received his B.S. and M.S. degrees from the University of Science and Technology of China, and his Ph.D. in Chemical Physics from The Ohio State University. He also carried out postdoctoral research at the University of Kentucky, and previously held positions at Eastern Kentucky University, Xinjiang Astronomical Observatory of the Chinese Academy of Sciences, and Zhejiang Lab. His research has been focused on astrophysics and astrochemistry for over two decades. In recent years, he has been working on the use of intelligent computing to empower scientific discovery, with particular interest in the formation of molecules in the universe and the chemical origins of life. He has led a research team that has made a series of advances in interstellar molecular modeling, AI-driven chemical reaction prediction, automated spectral-line identification, and large-model development for astronomy. He has served as PI or lead investigator on more than ten major national and regional research projects, and has developed intelligent research platforms and models including ChemiVerse, Spectuner, and GraSSCoL. He has published more than 70 papers in leading journals such as ApJS, MNRAS, and A&A, and has made notable contributions at the intersection of intelligent astronomy and astrophysics.
封面图片来源：
https://kiaa.pku.edu.cn/cn/info/1034/3875.htm
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