QUBO.jl - Bridging Quantum Optimization and Mathematical Programming
The Julia Programming Language via YouTube
MIT Sloan AI Adoption: Build a Playbook That Drives Real Business ROI
Learn EDR Internals: Research & Development From The Masters
Overview
Google, IBM & Meta Certificates — All 10,000+ Courses at 40% Off
One annual plan covers every course and certificate on Coursera. 40% off for a limited time.
Get Full Access
Learn how QUBO.jl bridges the gap between quantum optimization methods and industrial applications in this 15-minute conference talk from JuliaCon Global 2025. Discover how this Julia package extends JuMP (Julia Mathematical Programming) to provide a unified interface for quantum and physics-inspired solution methods, eliminating the need to adapt to vendor-specific platforms. Explore the extensive toolset for automatically reformulating mathematical models into Quadratic Unconstrained Binary Optimization (QUBO) format, enabling direct deployment of complex models to quantum devices. Understand how QUBO.jl addresses the barriers faced by practitioners wanting to experiment with quantum algorithms across different platforms within common practical scenarios. Gain insights into the package's impact on helping the Operations Research community adopt and prototype quantum optimization applications, making quantum computing more accessible to experts already familiar with JuMP's mathematical programming environment.
Syllabus
QUBO.jl | Maciel Xavier | JuliaCon Global 2025
Taught by
The Julia Programming Language