Delves into complexity theory, focusing on the P vs NP problem and the classification of computational problems based on efficiency.
Introduces computational complexity, decision problems, quantum complexity, and probabilistic algorithms, including NP-hard and NP-complete problems.
Explores complexity classes P and NP, highlighting solvable and verifiable problems, including NP-complete challenges.
Covers the Quantum Approximate Optimization Algorithm (QAOA) for solving combinatorial optimization problems using quantum computers and its application to Boolean Satisfiability (SAT) problems.
Explains the Quantum Phase Estimation (QPE) algorithm and its complexity using two registers and SWAP gates.
