1

報告人：Mikhail Skvortsov，Landau Institute for Theoretical Physics, Russian Academy of Sciences

時間：4月29日（周三）15:00

單位：中國科學院理論物理研究所

地點：南樓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.

報告人簡介:

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.

2

報告人：Gu Zhang，Nanjing University

時間：4月29日（周三）15:00

單位：北京大學物理學院

地點：西563會議室

3

報告人：Tom Kroktsch，University of Hamburg

時間：4月30日（周四）15:00

單位：中國科學院理論物理研究所

地點： 南樓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.

報告人簡介:

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.

4

報告人：顏世申，山東大學物理學院

時間：4月30日（周四）15:00

單位：北京大學物理學院

地點： 物理大樓中樓212報告廳

摘要:

在自旋電子學中，電荷流與自旋流的相互轉換是重要的研究課題，利用自旋流驅動磁性層的磁化翻轉是當前的研究前沿和熱點。傳統自旋軌道力矩器件通常依賴于重金屬（如Ta、Pt、W等）的自旋霍爾效應來實現電荷流到自旋流的轉變，而近年來，軌道流及其軌道矩，以及自旋渦度耦合效應引起了廣泛關注。本研究旨在探索能否利用自旋渦度耦合效應驅動磁化翻轉。我們在PtCo/Cu雙層膜中發現了巨大的類阻尼軌道矩效率，隨Cu厚度增加最高達18×10? (Ωm)?1，比典型Ta系材料高兩個數量級，同時驅動CoPt磁化翻轉的臨界電場顯著降低。實驗和理論表明，該超高效率源于Cu與PtCo層電子的面內遷移率在膜厚方向的梯度引起的自旋渦度耦合。本研究填補了利用自旋渦度耦合實現磁化翻轉的空白，為低功耗自旋電子器件提供了新路徑。

報告人簡介:

顏世申，山東大學物理學院教授、博士生導師，濟南大學自旋電子學研究所所長。曾任山東大學物理學院副院長、學術委員會主任等職。他還是國家杰出青年基金獲得者、山東省杰出青年基金獲得者、教育部新世紀優秀人才、德國洪堡學者。曾獲山東省自然科學一等獎，被評為山東省有突出貢獻的中青年專家。研究領域是自旋電子學，研究方向包括人工神經形態計算、自旋軌道矩翻轉磁化強度、自旋微波振蕩器、電場調控磁性、整流磁電阻等。作為課題負責人完成國家973課題、國家杰出青年基金項目、國家自然科學基金重點項目、111引智計劃、軍工重大項目等近20項。已獲得國家發明專利授權15項，發表SCI論文200多篇；部分成果已被寫進了教科書和特邀綜述文章，并被許多研究組廣泛采用。

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報告人：Donghui Quan，西安交通大學利物浦大學

時間：4月23日（周四）15:30

單位：北京大學物理學院

地點： 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.

報告人簡介:

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.

封面圖片來源：

https://kiaa.pku.edu.cn/cn/info/1034/3875.htm

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