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arXiv 2510.08061quant-ph
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通过解码量子干涉术优化二次约束

Optimization of Quadratic Constraints by Decoded Quantum Interferometry

Weizmann Institute of Science(魏茨曼科学研究所)

Daniel Cohen Hillel

AI总结:

本文提出了解码量子干涉术优化二次约束问题,通过二次最优多项式交集问题验证算法有效性,并推广了半圆定律的证明。

摘要:

最近,Jordan 等人提出了解码量子干涉术(DQI),这是一种新颖的量子算法,利用量子傅里叶变换将线性优化问题——max-XORSAT 和 max-LINSAT——转化为解码问题。本文将 DQI 扩展到涉及二次约束的优化问题,称为 max-QUADSAT。利用其与二次高斯和的联系,我们给出了一个高效的算法来为 max-QUADSAT 准备 DQI 状态(免责声明:在算法的一个步骤中发现了一个错误,除非找到修复方法,否则该结果无效)。为了证明我们的算法实现了量子优势,我们引入了二次最优多项式交集(二次-OPI)问题,这是 OPI 的一个受限变种,据我们所知,标准的 DQI 框架对此问题没有算法加速。我们展示了二次-OPI 是 max-QUADSAT 的一个实例,并使用我们的算法对其进行优化。最后,我们提出了一种新的广义证明,证明了满足约束比例的“半圆定律”,将其推广到任何 DQI 状态的问题中,其中随机分配的满足约束数量的分布足够接近二项分布。这一条件在 max-LINSAT 的 DQI 状态中恰好成立,并在 max-QUADSAT 情况下近似成立,随着问题规模的增加,近似程度呈指数级提高。这为我们的算法建立了性能保证。

英文摘要:

A recent paper by Jordan et al. introduced Decoded Quantum Interferometry (DQI), a novel quantum algorithm that uses the quantum Fourier transform to reduce linear optimization problems -- max-XORSAT and max-LINSAT -- to decoding problems. In this paper, we extend DQI to optimization problems involving quadratic constraints, which we call max-QUADSAT. Leveraging a connection to quadratic Gauss sums, we give an efficient algorithm to prepare the DQI state for max-QUADSAT (DISCLAIMER: A mistake was found in one of the algorithm's steps, which invalidates this result unless a fix is found). To demonstrate that our algorithm achieves a quantum advantage, we introduce the Quadratic Optimal Polynomial Intersection (quadratic-OPI) problem, a restricted variant of OPI for which, to our knowledge, the standard DQI framework offers no algorithmic speedup. We show that quadratic-OPI is an instance of max-QUADSAT and use our algorithm to optimize it. Lastly, we present a new generalized proof of the "semicircle law" for the fraction of satisfied constraints, generalizing it to any DQI state of problems where the distribution of the number of satisfied constraints for a random assignment is sufficiently close to a binomial distribution. This condition holds exactly for the DQI state of max-LINSAT, and approximately holds in the max-QUADSAT case, with the approximation becoming exponentially better as the problem size increases. This establishes performance guarantees for our algorithm.

机构、总结、中文摘要均由AI分析而来,可能存在错误,请以论文正文为准。

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