Seminar: How to connect and run algorithms on a networked quantum computer
Mon June 11th, 2018 14:00 to Mon June 11th, 2018 15:00
We are pleased to host Steven Herbert, Research Associate at the University of Cambridge Department of Applied Mathematics and Theoretical Physics, who will be giving a seminar about his work on quantum algorithms.
The likely realisation networked quantum computers in the near-term raises many fascinating technical questions. In particular, the focus of this programme of work is to establish how to connect the component nodes of the networked quantum computer and how to run algorithms thereon such that performance is maximised. In this talk bounds on the theoretical performance of such networked quantum computers will be presented, alongside some initial numerical results on a simple simulated model of the networked quantum computer.
Steven Herbert received the M.A. (cantab) and M.Eng. degrees from the University of Cambridge Department of Engineering in 2010, and the Ph.D. degree from the University of Cambridge Computer Laboratory in 2015. Following the submission of his Ph.D. thesis he continued to work at the University of Cambridge Computer Laboratory as a Research Assistant from May to June 2014, and remained a visiting researcher until December 2016. From January 2015 until July 2016 he worked at Blu Wireless Technology, Bristol, during which time he was a co-inventor of five patents. From September 2016 until January 2018 he was a Research Associate at the University of Edinburgh School of Engineering, where he worked on adaptive beam-pattern design for active sensing, and he is currently a visiting researcher at the University of Edinburgh. He started his current position, Research Associate at the University of Cambridge Department of Applied Mathematics and Theoretical Physics in February 2018, where he is working on quantum computing, and he is also a Teaching By-Fellow at Churchill College, University of Cambridge. His research interests lie in quantum information, quantum computing, network information theory and machine learning.