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arXiv 2210.01601quant-phcs.CC
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线性回归的量子通信复杂度

Quantum communication complexity of linear regression

Ashley Montanaro, Changpeng Shao

AI总结:

本研究证明量子计算机在无秩限制的线性回归和哈密顿量模拟中,具有通信复杂度上的多项式及指数级加速,并提出近最优量子协议及下界,同时开发了高效的量子奇异值变换协议。

摘要:

量子计算机在解决线性代数问题方面可能比经典计算机实现加速。然而,在某些情况下——例如对于低秩矩阵——去量化算法表明不可能存在指数级的量子加速。在这项工作中,我们证明了在秩不受限制的情况下,量子计算机对于一些基础线性代数问题在通信复杂度方面具有可证明的多项式和指数级加速。我们主要关注求解线性回归和哈密顿量模拟。在量子情形中,任务是制备结果的量子态。为了公平比较,在经典情形中,任务是从结果中采样。我们在两方和多方的模型中研究这两个问题,提出了近最优的量子协议,并证明了量子/经典的下界。在此过程中,我们提出了一种高效的量子奇异值变换的量子协议,这是一种设计量子算法的强大技术。这将有助于为许多其他问题开发高效的量子协议。

英文摘要:

Quantum computers may achieve speedups over their classical counterparts for solving linear algebra problems. However, in some cases -- such as for low-rank matrices -- dequantized algorithms demonstrate that there cannot be an exponential quantum speedup. In this work, we show that quantum computers have provable polynomial and exponential speedups in terms of communication complexity for some fundamental linear algebra problems \update{if there is no restriction on the rank}. We mainly focus on solving linear regression and Hamiltonian simulation. In the quantum case, the task is to prepare the quantum state of the result. To allow for a fair comparison, in the classical case, the task is to sample from the result. We investigate these two problems in two-party and multiparty models, propose near-optimal quantum protocols and prove quantum/classical lower bounds. In this process, we propose an efficient quantum protocol for quantum singular value transformation, which is a powerful technique for designing quantum algorithms. This will be helpful in developing efficient quantum protocols for many other problems.

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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