Five Starter Problems: Solving Quadratic Unconstrained Binary Optimization Models on Quantum Computers
arxiv(2024)
摘要
Several articles and books adequately cover quantum computing concepts, such
as gate/circuit model (and Quantum Approximate Optimization Algorithm, QAOA),
Adiabatic Quantum Computing (AQC), and Quantum Annealing (QA). However, they
typically stop short of accessing quantum hardware and solve numerical problem
instances. This tutorial offers a quick hands-on introduction to solving
Quadratic Unconstrained Binary Optimization (QUBO) problems on currently
available quantum computers. We cover both IBM and D-Wave machines: IBM
utilizes a gate/circuit architecture, and D-Wave is a quantum annealer. We
provide examples of three canonical problems (Number Partitioning, Max-Cut,
Minimum Vertex Cover), and two models from practical applications (from cancer
genomics and a hedge fund portfolio manager, respectively). An associated
GitHub repository provides the codes in five companion notebooks. Catering to
undergraduate and graduate students in computationally intensive disciplines,
this article also aims to reach working industry professionals seeking to
explore the potential of near-term quantum applications.
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