In this work, we experiment with quantum annealing and the D-Wave suite by developing a new application we call Quantum Graph Pursuit (QGP), which is a dynamic combinatorial optimization problem. We delve into two models’ formulations and their implementation on the D-Wave system, relying both on the hybrid and fully quantum settings. The final objective of our work is twofold: to solve the initial problem, finding the right trade-off between expressiveness and complexity, and to obtain and share general indications on the formulation and implementation process themselves.
Quantum Graph Pursuit: Analysis of the Advantages and Challenges of a Quantum Dynamic Combinatorial Optimization Model from a Software Developer Perspective
Reale, Simone;Nitto, Elisabetta Di
2024-01-01
Abstract
In this work, we experiment with quantum annealing and the D-Wave suite by developing a new application we call Quantum Graph Pursuit (QGP), which is a dynamic combinatorial optimization problem. We delve into two models’ formulations and their implementation on the D-Wave system, relying both on the hybrid and fully quantum settings. The final objective of our work is twofold: to solve the initial problem, finding the right trade-off between expressiveness and complexity, and to obtain and share general indications on the formulation and implementation process themselves.File in questo prodotto:
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Quantum_Graph_Pursuit (6).pdf
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