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