主办方：中国科学院数学与系统科学研究院 

时　间：2022年1月10日

线　下：数学院南楼219

直播地址：腾讯会议172 320 073

https://www.koushare.com/lives/room/887483

特邀报告人：应明生　　中国科学院软件研究所

　　　　　　朱晓波　　中国科学技术大学

　　　　　　强晓刚　　军事科学院国防科技创新研究院

　　　　　　邓东灵　　清华大学

会议组织： 尚云 骆顺龙 陆汝钤

会议日程：

8:30-8:40	开幕式	主持人
8:40-9:25	应明生 Model Checking for Verification of Quantum Circuits	陆汝钤
9:25-10:10	朱晓波 超导量子计算
10:10-10:20	茶歇
10:20-11:05	强晓刚 硅基集成光学量子计算技术与进展	尚云
11:05-11:50	邓东灵 Some Recent Advances in Quantum Artificial Intelligence

 

 

 

会议详情：

 

1.    应明生

 

报告题目/ Presentation Title：Model Checking for Verification of Quantum Circuits

 

摘要/Abstract: In this talk, I will describe a framework for assertion-based verification of quantum circuits by applying model checking techniques for quantum systems developed in our previous work, in which:

(1) noiseless and noisy quantum circuits are modelled as quantum automata and quantum Markov chains, respectively, and they are further represented by tensor networks;

(2) Quantum assertions are specified by a temporal extension of Birkhoff-von Neumann quantum logic;

(3) Algorithms for reachability analysis and model checking of quantum circuits are developed based on contraction of tensor networks.

 

报告人简介/Brief Bio: Mingsheng Ying is Research Professor at the Institute of Software at the Chinese Academy of Sciences, and holds the Cheung Kong Chair Professorship at Tsinghua University, China. He was Distinguished Professor and Research Director of the Center for Quantum Software  and Information at the University of Technology Sydney, Australia. His research interests include quantum computation, theory of programming languages, and logics in AI. He has published books: Model Checking Quantum Systems: Principles and Algorithms (2021) (with Yuan Feng), Foundations of Quantum Programming (2016) and Topology in Process Calculus: Approximate Correctness and Infinite Evolution of Concurrent Programs (2001). He has served on the editorial board of several publications including Artificial Intelligence Journal. He is currently Editor-in-Chief of ACM Transactions on Quantum Computing. 

2. 朱晓波

 

报告题目/Presentation Title：超导量子计算

 

摘要/Abstract：由于量子计算在某些问题的处理能力上相比于经典计算机有着压倒性的优势，被普遍认为是下一代的计算技术，因而引起了广泛的关注。超导方案因具有良好的可扩展性就，目前备受关注，各大公司纷纷投资进入该领域。本次报告将主要讲解超导量子计算的现状及近期和中远期目标，并介绍我们在该方向上取得的一系列进展。

 

报告人简介/Brief Bio：朱晓波，中国科学技术大学教授。主要从事超导量子计算以及超导约瑟夫森结系统的研究。在磁通量子比特与金刚石中的NV色心的量子混合系统上做出了一系列的重要工作。先后创造了超导量子比特最大纠缠数目纪录。研制了超导量子计算原型机“祖冲之号”，实现了“量子优越性”。

 

3     强晓刚

报告题目/ Presentation Title：硅基集成光学量子计算技术与进展

 

摘要/Abstract：量子计算是建立在量子力学上的新型计算模型，在许多领域应用具有超越经典计算的巨大潜力。光量子芯片技术采用传统微纳加工工艺在单个芯片上集成大量光学器件，具有高集成度、高精确度、高稳定性等优势，是实现可实用化光量子计算的有效途径。硅基集成光学技术具有非线性效应强、集成密度高、CMOS可兼容等优点，为实现大规模集成光量子计算芯片提供了理想的技术平台。基于硅基集成光学技术，片上的纠缠光子源、高精度单光子操控、通用线性光学网络等都已得到了实验验证。我们基于硅基集成光学技术，面向规模化可编程光量子计算芯片技术开展了系统性研究，设计实现了高精度片上马赫泽德干涉仪、可编程通用两比特光量子计算芯片、图论问题专用可编程光量子计算芯片，以及哈密顿量含时演化高效模拟光量子计算芯片，并基于芯片研制实现了软硬件一体集成光学量子计算实验原型系统，进行了一系列量子算法应用与实验研究。这些结果显示了硅基集成光学技术实现未来大规模光量子计算的巨大潜力。

 

报告人简介/Brief Bio：强晓刚，英国布里斯托大学博士，军事科学院国防科技创新研究院研究员，北京量子信息科学研究院兼聘研究员，研究生导师，入选国防科技卓越青年科学基金、国家海外高层次人才计划青年项目、国家特殊领域青年人才托举工程等项目资助。2009年本科毕业于北京大学电子学系，2012年硕士毕业于国防科技大学计算机学院，2017年获得英国布里斯托大学物理博士学位。长期从事集成光学量子计算领域研究，发表SCI论文20余篇，包括以第一/通信作者在Nature Photonics、Science Advances、Nature Communications等国际期刊发表论文，代表性成果包括国际首个通用两比特光量子计算芯片、图论问题专用可编程光量子计算芯片等。

 

4        邓东灵

 

报告题目/ Presentation Title：Some Recent Advances in Quantum Artificial Intelligence

 

摘要/Abstract: Quantum artificial intelligence (Quantum AI) is an emergent interdisciplinary field that explores the interplay between artificial intelligence and quantum physics. On the one hand, judiciously designed quantum algorithms may exhibit exponential advantages in solving certain AI problems; on the other hand, ideas and techniques from AI can also be exploited to tackle challenging problems in the quantum domain. In this talk, I will first make a brief introduction to this field and review some recent progresses. I will talk about several concrete examples to illustrate how AI and quantum physics can promote studies in both fields. At the end of the talk, I will pose some fundamental challenges facing quantum AI that, if overcome, would give a significant boost to this fledgling field full of uncertainties and opportunities.

 

报告人简介/Brief Bio：Dong-Ling Deng is an assistant professor at the Institute for Interdisciplinary Information Sciences, Tsinghua University. He graduated from Nankai University with two Bachelor degrees, one in physics and the other in mathematics. He then studied at the Chern Institute of Mathematics and got a master degree in theoretical physics. After that, he moved to the University of Michigan and obtained his Ph.D. in physics, with thesis awarded “the Kent M. Terwilliger Memorial Thesis Prize”. He did his postdoctoral work as a JQI (Joint Quantum Institute) postdoctoral fellow at the University of Maryland. Prof. Deng’s current research interest mainly concerns quantum artificial intelligence.