如何通过二次无约束二元优化逼近任意目标函数

2022 IEEE International Conference on Software Analysis, Evolution and Reengineering (SANER) Pub Date : 2022-03-01 DOI:10.1109/saner53432.2022.00149

Thomas Gabor, M. Rosenfeld, Sebastian Feld, Claudia Linnhoff-Popien

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引用次数: 7

摘要

二次无约束二进制优化(QUBO)已成为量子计算机优化的标准格式，即量子近似优化算法(QAOA)和量子退火算法(QA)。我们提出了一套方法，通过(i)将几乎任意问题近似为多项式，然后(ii)将任何多项式转换为QUBO，将它们转换为QUBO。我们在两个示例问题(比率切割和逻辑回归)上展示了我们的方法的使用。

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How to Approximate any Objective Function via Quadratic Unconstrained Binary Optimization

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).

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2022 IEEE International Conference on Software Analysis, Evolution and Reengineering (SANER)

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