Graph theory problems such as Maximum Cut (Max-Cut), Minimum Vertex Cover, and Traveling Salesman Problem have wide-ranging real-world applications. Max-Cut, which seeks to divide a graph into two subsets to maximize the number of edges between them, is employed in financial portfolio optimization to balance asset risk and returns. In network security, the Minimum Vertex Cover problem, focused on identifying the smallest set of vertices that cover all edges, is crucial for efficient placement of checkpoints or sensors. The Traveling Salesman Problem, a quest to determine the shortest route visiting a set of locations and returning to the start, is fundamental in logistics for route optimization. Quantum computing, with its unparalleled ability to process complex computations, offers significant advantages in tackling these graph theory challenges. Classiq’s platform, with its sophisticated modeling capabilities, translates these problems into quantum-computable formats, paving the way for solutions that surpass the capabilities of classical computational methods