论文标题
通过量子zeno动力学的限制优化
Constrained Optimization via Quantum Zeno Dynamics
论文作者
论文摘要
受限的优化问题在科学和工业中无处不在。量子算法在解决优化问题方面已经显示出希望，但是当前的算法都无法有效处理任意约束。我们介绍了一种使用量子Zeno动力学来解决具有多个任意约束（包括不平等）的优化问题的技术。我们表明，量子优化的动力学可以通过重复的投影测量值有效地限制在易于故障的量子计算机上的构成子空间，仅需要少量的辅助圈子，而无需进行后选择。我们的技术具有广泛的适用性，我们通过将其纳入量子近似优化算法（QAOA）和以进行优化的变异量子电路来证明。我们对具有多个现实限制的投资组合优化问题进行数值评估，并观察到更好的解决方案质量和比最新技术更高的概率。我们在Quantinuum H1-2量子处理器上实施了概念概念证明。
Constrained optimization problems are ubiquitous in science and industry. Quantum algorithms have shown promise in solving optimization problems, yet none of the current algorithms can effectively handle arbitrary constraints. We introduce a technique that uses quantum Zeno dynamics to solve optimization problems with multiple arbitrary constraints, including inequalities. We show that the dynamics of quantum optimization can be efficiently restricted to the in-constraint subspace on a fault-tolerant quantum computer via repeated projective measurements, requiring only a small number of auxiliary qubits and no post-selection. Our technique has broad applicability, which we demonstrate by incorporating it into the quantum approximate optimization algorithm (QAOA) and variational quantum circuits for optimization. We evaluate our method numerically on portfolio optimization problems with multiple realistic constraints and observe better solution quality and higher in-constraint probability than state-of-the-art techniques. We implement a proof-of-concept demonstration of our method on the Quantinuum H1-2 quantum processor.
