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Covers the Quantum Approximate Optimization Algorithm (QAOA) for solving combinatorial optimization problems using quantum computers and its application to Boolean Satisfiability (SAT) problems.
Explores high-performance OPF solvers, addressing challenges in power system optimization and showcasing significant speed-ups and memory-efficient approaches.
Introduces the importance of studying algorithms, presents a clever algorithm for calculating an arithmetic series, and discusses efficiency and correctness in algorithms.
Explores combinatorial optimization using simulated annealing to find ground states in frustrated systems and address challenges in satisfying all interactions simultaneously.
