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Explore quantum approximation algorithms in this 55-minute lecture presented by Ojas Parekh from Sandia National Laboratories at IPAM's Many-body Quantum Systems via Classical and Quantum Computation Workshop. Delve into the potential advantages of quantum approximation algorithms over classical counterparts, focusing on optimization problems with connections to quantum mechanics. Examine recent work on approximating Quantum Max Cut and other physically motivated local Hamiltonians that generalize classical discrete optimization problems. Gain insights into quantum streaming algorithms for Max Cut and related problems, including a recently established exponential quantum streaming advantage. Discover how approximation algorithms address classical NP-hardness and learn about the Quantum Approximation Optimization Algorithm's role in this field.
