Solving continuous variable optimization problems by factorization machine quantum annealing (FMQA) demonstrates the potential of Ising machines to be extended as a solver for integer and real optimization problems. However, the details of the Hamiltonian function surface obtained by factorization machine (FM) have been overlooked. This study shows that in the widely common case where real numbers are represented by a combination of binary variables, the function surface of the Hamiltonian obtained by FM can be very noisy. This noise interferes with the inherent capabilities of quantum annealing and is likely to be a substantial cause of problems previously considered unsolvable due to the limitations of FMQA performance. The origin of the noise is identified and a simple, general method is proposed to prevent its occurrence. The generalization performance of the proposed method and its ability to solve practical problems is demonstrated.

翻译：通过因子分解机量子退火（FMQA）求解连续变量优化问题，展示了伊辛机扩展为整数和实数优化问题求解器的潜力。然而，由因子分解机（FM）获得的哈密顿函数曲面的细节一直被忽视。本研究表明，在实数由二进制变量组合表示的广泛常见情况下，通过FM获得的哈密顿函数曲面可能包含显著噪声。这种噪声干扰了量子退火的固有能力，并很可能是先前因FMQA性能限制而被认为无法解决的问题的主要原因。本文识别了噪声的来源，并提出了一种简单、通用的方法来防止其产生。同时验证了所提方法的泛化性能及其解决实际问题的能力。