Lecturer: Prof. Daniel Lidar Affiliation: Department of Electrical Engineering, Chemistry and Physics, Seaver Science Center, University of Southern California Abstract: Quantum information processing holds great promise, yet large-scale, general purpose quantum computers capable of solving hard problems are not yet available despite 20+ years of immense effort. In this talk I will describe some of this promise and effort, as well as the obstacles and ideas for overcoming them using error correction techniques. I will focus on a special purpose quantum information processor called a quantum annealer, designed to speed up the solution to tough optimization problems. In October 2011 USC and Lockheed-Martin jointly founded a quantum computing center housing a commercial quantum annealer built by the Canadian company D-Wave Systems. These processors use superconducting flux qubits to minimize the energy of classical spin-glass models with as many spins as qubits, an NP- hard problem with numerous applications. There has been much controversy surrounding the D-Wave processors, questioning whether they offer any advantage over classical computing. I will survey the recent work we have done to benchmark the processors against highly optimized classical algorithms, to test for quantum effects, and to perform error correction. References: - T. Rønnow et al., “Defining and detecting quantum speedup” Science 345, 420 (2014). - S. Boixo et al., “Quantum annealing with more than one hundred qubits”, Nature Phys. 10, 218 (2014). - K. Pudenz et al., “Error corrected quantum annealing with hundreds of qubits”, Nature Commun. 5, 3243 (2014). - I. Hen et al., “Probing for quantum speedup in spin glass problems with planted solutions”, arXiv:1502.01663 ‏האירוע הזה כולל שיחת וידאו ב-Google Hangouts. הצטרף: https://hangouts.google.com/hangouts/_/mail.huji.ac.il/condensed?hceid=b...