Witryna9 lut 2024 · The quantum approximate optimization algorithm (QAOA) is a promising method of solving combinatorial optimization problems using quantum computing. QAOA on the MaxCut problem has been studied extensively on graphs with specific structure; however, little is known about the general performance of the algorithm on arbitrary …
Solving the Shortest Path Problem with QAOA - ResearchGate
The correlation between number of edges and the metrics computed varies greatly. There is a very strong correlation between the number of edges and \langle C \rangle , which can be seen in Figs. 1 and 2a. This makes intuitive sense for the following reason. Arbitrarily adding edges to a given graph will not … Zobacz więcej For the most part, the diameter of a graph, d, correlates negatively with the QAOA metrics, but the correlation becomes less negative as n increases, which is the reverse of the … Zobacz więcej An automorphism of a graph is a relabeling of vertices that preserves edges and therefore is a type of symmetry. An orbit of a vertex … Zobacz więcej The group size of a graph tends to have high positive correlations with all QAOA properties for small n. However as n increases, the correlations tend to zero. A zero correlation, however, might not indicate that the … Zobacz więcej Since there are so few bipartite graphs compared to non-bipartite for fixed n, looking at the average of each QAOA metric offers more insight into how a graph being bipartite affects the quality of QAOA solution. The … Zobacz więcej WitrynaThe quantum approximate optimization algorithm (QAOA) is a method of approximately solving combinatorial optimization problems. While QAOA is developed to solve a broad class of combinatorial optimization problems, it is not clear which classes of problems are best suited for it. One factor in demonstrating quantum advantage is the relationship … cherry laurel uk
QAOA for MaxCut — PennyLane documentation
Witryna27 sty 2024 · Finding high-quality parameters is a central obstacle to using the quantum approximate optimization algorithm (QAOA). Previous work partially addresses this issue for QAOA on unweighted MaxCut problems by leveraging similarities in the objective landscape among different problem instances. However, we show that the more … Witryna1 sty 2024 · We evaluate the performance of QAOA at depths at most three on the MaxCut problem for all connected non-isomorphic … WitrynaMoreover, Herrman et al [35] discussed the impact of graph structures for QAOA on MaxCut and presented some predictors of QAOA success related to graph density, … cherry laurel vs schip laurel