Presented By: Quantum Research Institute
Quantum Research Institute Seminar | Demonstration of algorithmic quantum speedup
Daniel Lidar, USC
Daniel Lidar, Viterbi Professor of Engineering at USC, will be presenting "Demonstration of algorithmic quantum speedup" as part of the Quantum Research Institute's winter seminar series from 11am - noon in the Boulevard Room (1st floor) in Pierpont Commons. A Zoom option is also provided.
Seminar Description:
Despite the development of increasingly capable quantum computers, an experimental demonstration of an algorithmic quantum speedup employing today's non-fault-tolerant devices has remained elusive. In this talk, I will report on three very recent demonstrations of such a speedup, focusing on how solution times scale with problem size. Two of the demonstrations use IBM’s superconducting quantum computers and involve modified versions of foundational black-box quantum algorithms. In contrast with recent quantum supremacy demonstrations, these quantum speedups do not rely on complexity-theoretic conjectures. The third demonstration uses a D-Wave quantum annealer and involves approximate optimization in the context of spin glass problems. In all cases, our work incorporates tailored quantum error suppression methods, which we found to be necessary in order for the quantum speedup to appear.
Seminar Description:
Despite the development of increasingly capable quantum computers, an experimental demonstration of an algorithmic quantum speedup employing today's non-fault-tolerant devices has remained elusive. In this talk, I will report on three very recent demonstrations of such a speedup, focusing on how solution times scale with problem size. Two of the demonstrations use IBM’s superconducting quantum computers and involve modified versions of foundational black-box quantum algorithms. In contrast with recent quantum supremacy demonstrations, these quantum speedups do not rely on complexity-theoretic conjectures. The third demonstration uses a D-Wave quantum annealer and involves approximate optimization in the context of spin glass problems. In all cases, our work incorporates tailored quantum error suppression methods, which we found to be necessary in order for the quantum speedup to appear.
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