CHMPR Distinguished Lecture Series
Programming and Tuning a Quantum Annealing Computer to Solve Real-World Applications
Dr. Alejandro Perdomo-Ortiz
Quantum Artificial Intelligence Laboratory
NASA Ames Research Center
2:00pm Monday 26 October 2015, ITE 325b
Since September 2013 and through a partnership with Google and USRA, NASA Ames Research Center has been working with a quantum device that has the promise of harnessing quantum-mechanical effects to speed up the solution of optimization problems. Solving real-world applications with quantum algorithms requires overcoming several challenges, ranging from translating the computational problem at hand to the quantum-machine language, to tuning several other parameters of the quantum algorithm that have a significant impact on performance of the device. In this talk, we discuss these challenges, strategies developed to enhance performance, and also a more efficient implementation of several applications. Although we will focus on applications of interest to NASA’s Quantum Artificial Intelligence Laboratory, the methods and concepts presented here apply to a broader family of hard discrete optimization problems that might also be present in many machine-learning algorithms.
Alejandro Perdomo-Ortiz is a Research Scientist at NASA Ames Research Center, Quantum Artificial Intelligence Laboratory, where he works in the design of quantum algorithms to solve hard optimization problems. Alejandro received a Ph.D. in Chemical Physics from Harvard University. He is a three-time winner of Harvard’s Certificate of Excellence in Teaching and a recipient of the Dudley R. Herschbach Teaching Award. He is originally from Cali, Colombia where he performed undergraduate studies in Chemistry at Universidad del Valle. Within the NASA team, he is interested in understanding the scalability and performance of quantum annealing algorithms and their realistic experimental implementations for broad applications in space exploration research.