Optimization and Machine Learning Using Quantum Annealing

This talk will start with a brief overview of quantum computing concepts, quantum annealing, and the D-Wave machine.  We will then describe two examples of applications we have studied using quantum annealing.  The first is an optimization problem that arises in graph theory. The second is a sampling technique we have developed to assist in the training of neural networks. These examples will illustrate some of the practical challenges in using quantum annealing hardware in its current form, as well as techniques we have developed to overcome these challenges.

 

Bio:

Steve Adachi is a research scientist at Lockheed Martin Information Systems & Global Solutions (IS&GS) in Palo Alto CA, USA, and currently the principal investigator for the LM IS&GS research program in quantum computing applications.  Previously he was a system architect for 8 years on several large military satellite programs.  Prior to Lockheed Martin, he spent 10 years at AT&T Bell Labs and Lucent Technologies as a systems engineer, software architect, & project manager, & was a Director of Software Engineering at Covad Communications.  He has a B.S. in Mathematics from Harvey Mudd College, and a Ph.D. in Applied Mathematics from Brown University.