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Quadratic unconstrained binary optimization (QUBO) has become the standardformat for optimization using quantum computers, i.e., for both the quantumapproximate optimization algorithm (QAOA) and quantum annealing (QA). Wepresent a toolkit of methods to transform almost arbitrary problems to QUBO by(i) approximating them as a polynomial and then (ii) translating any polynomialto QUBO. We showcase the usage of our approaches on two example problems (ratiocut and logistic regression).

How to Approximate any Objective Function via Quadratic Unconstrained Binary Optimization