2025-07-24 –, Main Room 6
In this talk, we would like to show how QUBO.jl makes Quantum Optimization accessible to Operations Research practitioners as it integrates a heterogeneous hardware and software landscape under a common interface, providing users with a smooth modeling experience. By leveraging JuMP’s extension capabilities, QUBO.jl makes it simple to access quantum and other novel devices as if they were regular optimization solvers. This makes it the ideal environment to try and explore potential applications.
Quantum algorithms and devices are being developed by multiple participants in a diverse scientific environment. As potential applications of its products are considered, access to these resources is usually granted through each vendor's specific interface. This poses a barrier for incoming practitioners to experiment with new methods and compare platforms within a common practical scenario. With this in mind, QUBO.jl was developed to bridge the gap between emerging optimization methods and important industrial applications. On one side, JuMP (Julia Mathematical Programming) is extended to provide a common interface for multiple types of quantum and other physics-inspired solution methods in the same way that regular solvers are made available. This exempts interested experts from adapting to the specificities of each platform, especially if one considers that many already use JuMP daily. On the other hand, an extensive set of tools for automatically reformulating mathematical models into Quadratic Unconstrained Binary Optimization (QUBO) makes it possible for users to directly send more complex models they already use and are familiar with to quantum devices. In this talk, we would like to highlight the impact that such a tool has on the journey of the Operations Research community in adopting and prototyping quantum optimization applications.
Open-source, blitz chess, roda de choro enthusiast; Computer and Information Engineer & Mathematician from UFRJ; M.Sc. Student at the Systems Engineering & Computer Science Program, UFRJ; Ph.D. student and member of the SECQUOIA research group at Purdue University. Previously, Research Intern in Public Healthcare at IFF/Fiocruz; Researcher & Developer at PSR Energy Inc. Research Intern in Analog Optimization at Microsoft Research.