Optimization with Quantum Computing

NOTE: THIS IS AN EARLY TIME SLOT SESSION - repeated on Thu May 19 at 3:30-4:30 pm ET.
Many classic optimization problems that arise in all areas of business and science remain intractable on classical computers, but could be solved practically with quantum computers. This seminar will cover some of those problems and discuss how quantum computers can be leveraged to solve them. We will demonstrate how the Qiskit Optimization open source software project can be used to describe optimization problems as quadratic programs, and then convert them into models that can be run on a quantum computer.

Note that this is part 4 of a 6-session series on Quantum Computing on Apr 13/14, Apr 20/21, May 4/5, May 18/19, Jun 1/2, and Jun 15/16. The sessions are not prerequisites for each other, and are not recorded. We will provide reference links and do quick recaps of previous content as required, so if you miss an earlier session, you can still get value from subsequent sessions.

Presenter: Sean Wagner

​Sean is a Research Scientist and a Quantum Technical Ambassador at IBM. When he's not programming and experimenting with Qiskit, Sean spends his time working with researchers at academic institutions and industry partners in Canada on projects involving high-performance computing, hardware acceleration, quantum computing, and data science and AI. Dr. Wagner holds a B.A.Sc. degree in Computer Engineering from the University of Waterloo, and M.A.Sc. and Ph.D. degrees in Electrical and Computer Engineering from the University of Toronto.

It is recommended that you register at this Webex link ahead of time to receive a calendar invite and reminder. https://ibm.webex.com/ibm/j.php?RGID=r3e28726e1cc6c04b35d3a997b0713cc4