Papers › AutoQubo: data-driven automatic QUBO generation
AutoQubo: data-driven automatic QUBO generation
Alberto Moraglio, Serban Georgescu, Przemysław Sadowski
This paper presents a general method to derive automatically a Quadratic Unconstrained Binary Optimisation (QUBO) formulation of, in principle, any combinatorial optimisation problem from its high-level description given in any programming language in a free format. Currently ad-hoc approaches to formulating a problem at a time as a QUBO are the norm. The proposed method goes beyond the state-of-the-art as it is general in its applicability. The method is data-driven and based on sampling, but the obtained QUBO is exact rather than only an approximation of the original problem for optimisation problems occurring in practice. The method is of particular interest in the context of Quantum Ising Machines - quantum computers specialised to optimisation tasks. It can be understood as a compiler that makes these machines usable without specific expertise by automating the translation of high-level description of combinatorial optimisation problems to a low-level format suitable for the quantum hardware.
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