Difference between revisions of "Quantum"

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:<font size=3>'''Title''': 专用量子计算机的应用算法 </font>
:<font size=3>'''Title''': 专用量子计算机的应用算法 </font>
:'''Abstract''':在不久的将来,我们可以预期学术界和工业界在量子计算机的研发上有持续的突破。比如对于 50 个量子比特以上的量子芯片,能够达到非常高精度的调控技术。
:'''Abstract''':在不久的将来,我们可以预期学术界和工业界在量子计算机的研发上有持续的突破。比如对于 50 个量子比特以上的量子芯片,能够达到非常高精度的调控技术。很有可能对于一些特定的计算任务,这些量子芯片能够执行到一个程度,是经典计算机无法有效模拟的。可是,这些芯片的量子比特个数还是远远不足以实现教科书里面的量子算法。当前的一个重大的问题就是,如何开发针对近期量子芯片的应用,去解决一些实际的科学或者工程问题?此外,对于一般用户,我们预期这些算力强大的专用量子机能够通过互联网,作为一种云服务去访问。这种形式的量子计算云服务也引发出不少学术问题,比如说,如何验证互联网背后的服务器是否带有真正的量子计算机而不是一个经典模拟器?

Revision as of 04:40, 20 September 2019


  • 2019年10月19、20日: 9 am--5 pm.
  • 南京大学 计算机科学与技术系 (南京大学仙林校区常州楼)111报告厅 在线地图


9:00 am -- 9:50 am 马小松


Title: 光量子信息处理
Coffee Break
10:15 am -- 11:05 am 苏晓龙


Title: 基于光场量子态的量子计算和量子纠错
11:10 am -- 12:00 pm 许金时


Title: 面向高维多模式的光量子模拟
Lunch Break (12 noon -- 1:30 pm)
1:30 pm -- 2:20 pm 王大伟


Title:Synthesis of anti-symmetric spin exchange interaction in superconducting circuits
2:25 pm -- 3:15 pm 鲁大为


Title: Experimental Implementation of Efficient Quantum Pseudorandomness on a 12-spin System
Abstract:Quantum pseudorandomness, also known as unitary designs, comprises a powerful resource for emergent quantum technologies. Although in theory pseudorandom unitary operators can be constructed efficiently, realizing these objects in realistic physical systems is a challenging task. Here, we demonstrate experimental generation and detection of quantum pseudorandomness on a 12-qubit nuclear magnetic resonance system. We first apply random sequences to the interacting nuclear spins, leading to random quantum evolutions that can quickly form unitary designs. Then, in order to probe the growth of quantum pseudorandomness during the time-evolutions, we propose the idea of using the system’s multiple-quantum coherence distribution as an indicator. Based on this indicator, we measure the spreading of quantum coherences and find that substantial quantum pseudorandomness has been achieved at the 12-qubit scale. This may open up a path to experimentally explore quantum randomness on forthcoming large-scale quantum processors.
3:20 pm -- 4:10 pm 戴汉宁


Title: Mass production of entanglement in a defect-free ultracold atom lattice
Coffee Break
9:00 am -- 9:50 am 孙晓明


Coffee Break
10:15 am -- 11:05 am 李绿周


Title: 量子生成对抗网络
11:10 am -- 12:00 pm 李科


Title: Quantum de Finetti theorem under one-way adaptive measurements
Lunch Break (12 noon -- 1:30 pm)
1:30 pm -- 2:20 pm 李颖


Title:Error-resilient quantum computation on near-future quantum computers
2:25 pm -- 3:15 pm 魏朝晖


Title: The experimental detection and quantification of entanglement
3:20 pm -- 4:10 pm 翁文康

南方科技大学 华为量子计算软件与算法首席科学家

Title: 专用量子计算机的应用算法
Abstract:在不久的将来,我们可以预期学术界和工业界在量子计算机的研发上有持续的突破。比如对于 50 个量子比特以上的量子芯片,能够达到非常高精度的调控技术。很有可能对于一些特定的计算任务,这些量子芯片能够执行到一个程度,是经典计算机无法有效模拟的。可是,这些芯片的量子比特个数还是远远不足以实现教科书里面的量子算法。当前的一个重大的问题就是,如何开发针对近期量子芯片的应用,去解决一些实际的科学或者工程问题?此外,对于一般用户,我们预期这些算力强大的专用量子机能够通过互联网,作为一种云服务去访问。这种形式的量子计算云服务也引发出不少学术问题,比如说,如何验证互联网背后的服务器是否带有真正的量子计算机而不是一个经典模拟器?


Coffee Break

Short Bios

Yu Cheng (程宇) will join the Mathematics (MSCS) Department of University of Illinois at Chicago as Assistant Professor in Fall 2019. He is currently a postdoctoral researcher in the Department of Computer Science at Duke University, hosted by Vincent Conitzer, Rong Ge, Kamesh Munagala, and Debmalya Panigrahi. He obtained his Ph.D. in Computer Science from the University of Southern California in 2017, advised by Shang-Hua Teng. His research interests include machine learning, game theory, and optimization.
Jingcheng Liu (刘景铖) is in the final year of his PhD in the CS theory group at UC Berkeley, with an anticipated completion of summer 2019, under the supervision of Professor Alistair Sinclair. He is broadly interested in theoretical computer science. His current research focuses on the interplay between phase transitions in statistical physics, locations of zeros of graph polynomials, and algorithmic questions such as the tractable boundaries of approximate counting, sampling and inference. Before attending UC Berkeley, he completed his undergraduate studies in the ACM Honor Class of 2010, at Shanghai Jiao Tong University.
Weiming Feng (凤维明) is a third year PhD student in the theoretical computer science group at Nanjing University, under the supervision of Professor Yitong Yin. His research mainly focuses on theory of distributed computing and randomized algorithms. Currently, he is working on distributed sampling and dynamic sampling problems.
Lingxiao Huang (黄棱潇) is a postdoc of computer science in EPFL, where he is advised by Nisheeth Vishnoi. He joined EPFL in 2017, after received his Ph.D. in IIIS, Tsinghua University. His current research interest is algorithm design and computational social choice. He is passionate about creating novel algorithms that are motivated by existing practical challenges.
Jiapeng Zhang (张家鹏) is a PhD candidate at UC San Diego, under the supervise of Shachar Lovett. He is working on boolean function analysis, computational complexity and foundations of cryptography.
Penghui Yao (姚鹏晖) is an associate professor in the Department of Computer Science and Technology, Nanjing University. He obtained his doctoral degree from Centre for Quantum Technology, National University of Singapore. Prior to joining Nanjing Univeristy, He was a postdoctoral researcher at CWI Netherlands; IQC University of Waterloo and QuICS University of Maryland. His research mainly focuses on quantum information theory, communication complexity and computational complexity.