论文标题
建模二元二进制优化的线性不等式约束，以实现变异量子量化
Modeling Linear Inequality Constraints in Quadratic Binary Optimization for Variational Quantum Eigensolver
论文作者
论文摘要
本文介绍了用于变量量子本素层的量身定制形式的使用，这些形式具有表示线性约束的二进制二进制优化问题解决方案的搜索域上某些约束的属性。通常在几个优化问题中出现的四个约束被建模。提出的方法的主要优点是变异形式上的参数数量保持恒定，并取决于约束上出现的变量数量。此外，这种变异形式总是为代表的约束而产生可行的解决方案，这些约束与通常用于将约束问题转化为无约束问题的惩罚技术不同。该方法是在真实量子计算机中实现的两个已知优化问题：设施位置问题和设定的包装问题。比较了使用2个局部变异形式和一般QAOA实现的VQE获得的两个问题，并表明使用了较少的量子门和参数，从而导致更快的收敛性。
This paper introduces the use of tailored variational forms for variational quantum eigensolver that have properties of representing certain constraints on the search domain of a linear constrained quadratic binary optimization problem solution. Four constraints that usually appear in several optimization problems are modeled. The main advantage of the proposed methodology is that the number of parameters on the variational form remain constant and depend on the number of variables that appear on the constraints. Moreover, this variational form always produces feasible solutions for the represented constraints differing from penalization techniques commonly used to translate constrained problems into unconstrained one. The methodology is implemented in a real quantum computer for two known optimization problems: the Facility Location Problem and the Set Packing Problem. The results obtained for this two problems with VQE using 2-Local variational form and a general QAOA implementation are compared, and indicate that less quantum gates and parameters were used, leading to a faster convergence.
