An Improved Quantum Max Cut Approximation via Maximum Matching
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Explore a conference presentation from TQC 2024 that delves into an improved classical approximation algorithm for Quantum Max Cut problems. Learn about finding high energy states in antiferromagnetic Heisenberg Hamiltonians, where researchers achieved a groundbreaking 0.595 approximation ratio, surpassing previous algorithms by Lee (0.562) and King (0.582). Discover how the algorithm leverages maximum weighted matching of input graphs and produces simpler output states using products of at most 2-qubit states, contrasting with earlier approaches that relied on fully entangled output states. Delivered at the 19th Conference on the Theory of Quantum Computation, Communication and Cryptography at the Okinawa Institute for Science and Technology, this 16-minute talk represents cutting-edge research in theoretical quantum information science, supported by industry leaders including JPMorganChase, Google Quantum AI, Horizon Quantum Computing, and Quantinuum.
Syllabus
An improved Quantum Max Cut approximation via Maximum Matching |Eunou Lee and Ojas Parekh | TQC 2024
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Squid: Schools for Quantum Information Development