生成式人工智能、实用化哈密顿量子模拟、氢硼聚变反应 | 本周物理讲座
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报告人：王磊，中国科学院物理研究所
时间：7月18日（周四）10:00
单位：中国科学院物理研究所
地点：M楼236会议室
摘要：
长期以来计算机最显著的特点是算得快、算得准。生成式人工智能赋予了计算机从经验中学习“直觉”的能力，甚至可以用来“创造”新的经验。定量描述这种“直觉”和“创造”的数学工具和统计物理一样，都是自然界中的概率分布。我将从物理学视角解读ChatGPT和Sora等生成式人工智能产品背后的关键技术：生成模型。生成模型学习数据背后的概率分布，并据此随机采样产生新的数据样本。基于和统计物理的深层联系，生成模型在原子尺度物质结构设计和变分自由能计算中具有特别的优势。我将以晶体按需生成和稠密氢状态方程为例说明生成模型在物质科学研究中的应用前景。
报告人简介：
王磊2006年本科毕业于南京大学，2011年在中国科学院物理研究所获得博士学位，此后在苏黎世联邦理工学院从事计算量子物理的博士后研究，2016年加入中国科学院物理研究所工作。主要研究方向是机器学习与量子多体计算的交叉领域。
王磊
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报告人：龙江，华中科技大学
时间：7月17、18、19日 10:00
单位：中国科学院理论物理所
地点：南楼6620
摘要：
Flat holography is stimulated by the success of AdS/CFT and has attracted much attention due to its potential applications in realistic physical processes. In this seminar, I will introduce Carrollian holography in which the dual field theory is assumed to live on the null boundary of asymptotically flat spacetime. At first, I will review basic elements on Carrollian manifold and introduce quantum flux operators which realize various geometric symmetry of Carrollian manifold. Second, I will explore the definition of Carrollian amplitude which is the central object that integrates geometry, quantum effects and holography. At last, I will discuss its potential applications to gravitational physics.
报告人简介：
Dr. Jiang Long is currently an associate professor of physics at Huazhong University of Sicence and Technology (HUST). He received his PhD in Physics from Peking University in 2015. After that, he became a postdoctoral fellow at Universite libre de Bruxelles (ULB). He moved to the Asia-Pacific Center of Theoretical physics (APCTP) before he joined HUST. His current research focus on flat holography and gravitational physics.
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报告人：李佳乐，伦敦大学学院
时间：7月17日（周三）14:00
单位：中国科学院理论物理研究所
地点：南楼6620
摘要：
The theory of general relativity has been the cornerstone of modern physics for over a century, and yet, many of its predictions remain untested. In recent years, the field of multi-messenger astronomy has emerged as a powerful tool for testing Einstein's theory, enabling us to study the universe through a combination of different cosmic messengers such as gravitational waves, electromagnetic waves, and cosmic rays. In this talk, we will explore how the upcoming Laser Interferometer Space Antenna (LISA) mission will revolutionise our understanding of gravity and astrophysics. LISA is a space-based gravitational wave detector that will be able to observe low-frequency gravitational waves, which are inaccessible to ground-based detectors. With its unprecedented sensitivity, LISA will enable us to probe a wide range of astrophysical phenomena, including the mergers of supermassive black holes, extreme-mass-ratio inspirals, and galactic binaries. I will also discuss how combining LISA observations with optical observations and radio pulsar timing, will allow us to test the relativistic dynamics in binary and triple systems, to constrain the maximum mass of neutron stars and to test gravito-magnetic effect.
报告人简介：
Kaye Jiale Li is a senior PhD student from Mullard Space Science Laboratory, University College London, working with Dr Kinwah Wu and Dr Ziri Younsi. Her research interests centre on multi-messenger astrophysics, with a focus on testing general relativity through the combination of gravitational waves and pulsar timing.
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报告人：赵琦，香港大学
时间：7月17日（周三）14:30
单位：中国科学院物理研究所
地点：B楼II段412会议室
摘要：
量子模拟，作为量子计算机最具潜力的应用之一，可以帮助模拟复杂的量子系统演化，从而帮助解决凝聚态物理、高能物理、量子化学、生物制药等领域中的诸多问题，加速相关的科学技术发展。然而量子模拟距离实际应用仍然有着很长的道路。哈密顿量子模拟算法是一种系统可靠的量子模拟算法。该类算法的误差分析是该领域的重要问题，它决定了量子计算任务中的量子资源估计。主流的误差分析往往只衡量了最坏情况下的初态和观测量，这一分析大大高估了量子算法中的误差，阻碍了量子模拟的实际应用。为了解决这一问题,我们考虑了量子模拟任务中初态和测量对于误差分析的影响，提出了随机初态[PRL129(27),270502，QIP2022talk]、纠缠态[arXiv:2406.02379]和基于局域观测量的量子模拟算法分析。这些结果极大减少了量子模拟任务中的资源需求，推动量子模拟算法的未来实现和应用。
报告人简介：
赵琦，香港大学计算机系助理教授。他主要从事量子模拟、量子纠缠、量子计算、量子信息基础理论等方面的研究，共发表期刊论文43篇，相关的一系列工作发表在国际顶级期刊 Nature, PRL, PRX, npj Quantum Inf., PNAS, IEEE Transactions on Information Theory; 成果也多次入选量子信息理论重要会议 QIP, AQIS, TQC, QCrypt 报告环节，并担任AQIS程序委员会委员（PC member）。主持或参与了国自然-香港研资局联合计划、香港杰出青年学者计划、香港影响力基金、国自然理论物理专款研究项目等。
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报告人：周通，宁波东方理工大学
时间：7月18日（周四）10:00
单位：中国科学院物理研究所
地点：物理所A332
摘要：
Majorana zero modes (MZM) with their nonlocal degrees of freedom and non-Abelian statistics have been viewed as a promising candidate for fault-tolerant quantum computing. However, despite intensive efforts, experimental evidence for MZM remains indirect and does not probe their crucial non-Abelian statistics. In this talk, I will reveal how we demonstrate MZM non-Abelian statistics through fusion and braiding in planar Josephson Junctions (JJs) with gate, phase, or magnetic texture control. Our proposals to identify non-Abelian statistics are supported by dynamical simulations and experimental findings in the fabricated InAs/Al JJs, opening an important route towards topological quantum computing.
报告人简介：
周通，宁波东方理工大学研究员、博导，上海交通大学、中国科学技术大学兼职博导，入选国家级高层次人才、宁波市特优人才等项目。2017年博士毕业于复旦大学，之后在美国纽约州立大学布法罗分校历任博士后研究员、研究科学家、研究助理教授，2023年加入东方理工。长期从事拓扑物态、量子输运与量子计算等研究，已发表论文40余篇，其中一作/通讯作者论文10余篇，包括近三年的Nat. Mater., Nat. Commun., 3篇Phys. Rev. Lett.等, 谷歌学术引用2800余次，H-index 24；多次受邀在APS March Meeting, SPIE, WINDS等国际知名学术会议上做邀请报告。
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报告人：Bhupal Dev，Washington University
时间：7月18日（周四）15:30
单位：中国科学院理论物理研究所
地点：南楼6620
摘要：
Neutrinos and dark matter remain two of the least known sectors of fundamental physics. What if they interact with each other? We will address this question in this talk. We implement a full catalog of constraints on the parameter space of the neutrino-dark matter/mediator couplings and masses, including bounds coming from cosmology, astrophysics, as well as new laboratory constraints from Z-boson and meson decays. As an application, we then consider galactic supernova neutrinos, identify new benchmark points that pass all the aforementioned constraints, compute the full set of cascade equations and sky maps for different dark matter density profiles in the Galaxy, and study their implications for the detection prospects in future large-volume neutrino experiments such as DUNE, Hyper-K and JUNO.
报告人简介：
Bhupal Dev is an Associate Professor of Physics and a member of the McDonnell Center for the Space Sciences at Washington University in St. Louis, USA. He got his PhD from the University of Maryland in 2012, working with Prof. Rabi Mohapatra. He then held postdoctoral positions at the University of Manchester in the UK, Technical University of Munich and Max-Planck-Institute for Nuclear Physics, Heidelberg, Germany, before joining WashU in 2016. He is a recipient of the Fermilab Intensity Frontier Fellowship and the Universities Research Association Visiting Scholars Award.
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报告人：Shangfeng Du，School of Chemical Engineering, University of Birmingham, UK
时间：7月19日（周五）10:00
单位：中国科学院物理研究所
地点：M255会议室
摘要：
The electrode structure plays a critical role in controlling the charge and mass transfer performance, thus determining whether the intrinsic catalytic activity of the electrocatalyst could be fully transported to practical electrodes or not during the operation of polymer electrolyte fuel cells. Electrochemical engineering research is required to further understand the influence mechanisms for reducing different overpotentials to bridge the gap between the highly active electrocatalysts and poor power performance devices. This talk will introduce our design of ordered electrodes based on Pt nanowire arrays for low temperature fuel cells to achieve large current density operation, discussing the lessons learnt during the thin film electrode fabrication, from nanostructure growing for tuning the electrode structure, the surface modification using functional Pd nanoseeds and plasma treatment, and alloying to boost the electrode activity and durability.
报告人简介：
Shangfeng Du is Professor of Electrochemical Engineering, leading research for low temperature fuel cells and electrolysers in Birmingham Energy Institute at the University of Birmingham, UK. He graduated from Tsinghua University in Materials Science and Engineering, and obtained his PhD in Chemical Engineering from the Chinese Academy of Sciences. After working as a research associate at the Max Planck Institute for Metals Research, Germany, he joined the University of Birmingham as a Marie Curie Research Fellow. His research interests lie in electrochemical engineering research for energy application, with a focus on the development and evaluation of electrodes, composite membranes, MEAs and short stacks, as well as their application and degradation research. He has been leading a few EU, UK and industrial projects, (co-)authored several books and more than 70 research papers. He serves as President of the Chinese Society of Chemical Science and Technology in the UK (CSCST-UK).
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报告人：孙小军，广西师范大学
时间：7月22日（下周一）15:00
单位：中国科学院理论物理研究所
地点：南楼6520
摘要：
简要介绍氢硼聚变反应的背景及其潜在的应用前景；针对氢硼聚变反应所应用到的核反应理论基础——轻核反应的统计理论( statistical theory of light nucleus reaction: STLN)及其相关核数据的初步研究进展；提出了今后关于氢硼聚变工程中还需要的核数据实验测量和理论研究等方面的工作目标；最后简介本团队利用机器学习方法应用于中子共振核数据领域的初步进展。
报告人简介：
孙小军，广西师范大学物理学院教授、西安交通大学兼职教授、博士生导师，《广西物理》主编。先后在中国核数据中心攻读博士学位、厦门大学从事博士后科研工作。先后主持4项国家自然科学基金项目、1项广西重点研发项目(军民两用)、2项广西自然科学基金重点项目以及多项横向项目。主要从事轻核反应研究、机器学习在核数据中的应用等领域的研究。
图片来源于：https://new.qq.com/rain/a/20240403A095YK00
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