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【预告】上海交通大学自然科学研究院 | Machine Learning for Quantum Control

KouShare 蔻享学术 2021-04-27




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此次讲座上海交通大学自然科学研究院主办,于2020年9月8日上午10:00开始。讲座授权蔻享学术进行网络直播。




主题:Machine Learning for Quantum Control


时间:2020年9月8日 10:00
讲人:Barry Sanders 教授
单位:University of Calgary
主办方:上海交通大学自然科学研究院


报告人简介



Dr. Barry Sanders is Director of the Institute for Quantum Science and Technology at the University of Calgary, Lead Investigator of the Alberta Major Innovation Fund Project on Quantum Technologies, a Distinguished Chair Professor at the University of Science and Technology China and a Vajra Visiting Faculty member of the Raman Research Institute in India. He received his Bachelor of Science degree from the University of Calgary in 1984 and a Diploma of Imperial College supervised by Professor Sir Thomas W. B. Kibble in 1985. He completed a PhD in 1987 at Imperial College London supervised by Professor Sir Peter Knight. His postdoctoral research was at the Australian National University, the University of Queensland and the University of Waikato. Dr. Sanders was on the Macquarie University faculty from 1991 until moving to Calgary in 2003.


Dr. Sanders is especially well known for seminal contributions to theories of quantum-limited measurement, highly nonclassical light, practical quantum cryptography and optical implementations of quantum information tasks. His current research interests include quantum algorithms and implementations of quantum information tasks.


Dr. Sanders is a Fellow of the Institute of Physics (U.K.), the Optical Society of America, the Australian Institute of Physics, the American Physical Society and the Royal Society of Canada, and a Senior Fellow of the Canadian Institute for Advanced Research. He is a past President of the Australian Optical Society, past Founding Co-Chair of the Canadian Association of Physicists Division of Atomic, Molecular and Optical Physics and former Leader of the Optical Society of America Quantum Optical Science and Technology Technical Group. In 2016 Sanders was awarded the Imperial College London Doctor of Science (DSc) degree. Dr. Sanders is Editor-in-Chief of New Journal of Physics, a former Associate Editor of Physical Review A, a former Editor of Optics Communications and a former Editor of Mathematical Structures of Computer Science.


报告摘要


We develop a framework that connects reinforcement learning with classical and quantum control, and this framework yields adaptive quantum-control policies that beat the standard quantum limit, inspires new methods for improving quantum-gate design for quantum computing, and suggest new ways to apply classical and quantum machine learning to control.

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