论文标题
组合优化问题的变异量子算法简介
An introduction to variational quantum algorithms for combinatorial optimization problems
论文作者
论文摘要
现在很容易获得嘈杂的中级量子计算机（NISQ计算机），激励许多研究人员尝试使用变异量子算法（VQAS）。其中，量子近似优化算法（QAOA）是组合优化社区最受欢迎的一种。在本教程中，我们提供了一类变异量子算法的数学描述，假设读者先前对量子物理学的了解没有。我们精确地介绍了量子侧（参数化量子电路）和经典侧（指导函数，优化器）的这些混合算法的关键方面。我们将特别的关注对QAOA提出，详细介绍了该算法所涉及的量子电路，以及由于其可能的指导函数所满足的属性。最后，我们讨论了有关QAOA的最新文献，强调了几种研究趋势。
Noisy intermediate-scale quantum computers (NISQ computers) are now readily available, motivating many researchers to experiment with Variational Quantum Algorithms (VQAs). Among them, the Quantum Approximate Optimization Algorithm (QAOA) is one of the most popular one studied by the combinatorial optimization community. In this tutorial, we provide a mathematical description of the class of Variational Quantum Algorithms, assuming no previous knowledge of quantum physics from the readers. We introduce precisely the key aspects of these hybrid algorithms on the quantum side (parametrized quantum circuit) and the classical side (guiding function, optimizer). We devote a particular attention to QAOA, detailing the quantum circuits involved in that algorithm, as well as the properties satisfied by its possible guiding functions. Finally, we discuss the recent literature on QAOA, highlighting several research trends.
