论文标题
限制量子近似优化的方法
Approaches to Constrained Quantum Approximate Optimization
论文作者
论文摘要
我们研究了不同量子方法的成本和收益，以找到约束组合优化问题的近似解决方案，重点是最大独立集。在Lagrange乘数方法中，我们分析了输出对图密度和电路深度的依赖性。然后分析量子交替的ANSATZ方法，并检查对初始状态不同选择的依赖性。量子交替的ANSATZ方法虽然强大，但在量子资源方面却很昂贵。提出了一种基于“动态量子变量ANSATZ”（DQVA）的新算法，该算法是在动态变化的，以确保最大程度地利用量子资源的固定分配。我们的分析和新提出的算法也可以推广到其他相关的约束组合优化问题。
We study the costs and benefits of different quantum approaches to finding approximate solutions of constrained combinatorial optimization problems with a focus on Maximum Independent Set. In the Lagrange multiplier approach we analyze the dependence of the output on graph density and circuit depth. The Quantum Alternating Ansatz Approach is then analyzed and we examine the dependence on different choices of initial states. The Quantum Alternating Ansatz Approach, although powerful, is expensive in terms of quantum resources. A new algorithm based on a "Dynamic Quantum Variational Ansatz" (DQVA) is proposed that dynamically changes to ensure the maximum utilization of a fixed allocation of quantum resources. Our analysis and the new proposed algorithm can also be generalized to other related constrained combinatorial optimization problems.
