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- W4387074760 abstract "Quantum algorithms have been widely studied in the context of combinatorial optimization problems. While this endeavor can often analytically and practically achieve quadratic speedups, theoretical and numeric studies remain limited, especially compared to the study of classical algorithms. We propose and study a new class of hybrid approaches to quantum optimization, termed Iterative Quantum Algorithms, which in particular generalizes the Recursive Quantum Approximate Optimization Algorithm. This paradigm can incorporate hard problem constraints, which we demonstrate by considering the Maximum Independent Set (MIS) problem. We show that, for QAOA with depth $p=1$, this algorithm performs exactly the same operations and selections as the classical greedy algorithm for MIS. We then turn to deeper $p>1$ circuits and other ways to modify the quantum algorithm that can no longer be easily mimicked by classical algorithms, and empirically confirm improved performance. Our work demonstrates the practical importance of incorporating proven classical techniques into more effective hybrid quantum-classical algorithms." @default.
- W4387074760 created "2023-09-27" @default.
- W4387074760 creator A5021155420 @default.
- W4387074760 creator A5076190671 @default.
- W4387074760 date "2023-09-22" @default.
- W4387074760 modified "2023-09-28" @default.
- W4387074760 title "Iterative Quantum Algorithms for Maximum Independent Set: A Tale of Low-Depth Quantum Algorithms" @default.
- W4387074760 doi "https://doi.org/10.48550/arxiv.2309.13110" @default.
- W4387074760 hasPublicationYear "2023" @default.
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