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arXiv 2310.20191quant-ph
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量子子空间校正用于约束条件

Quantum Subspace Correction for Constraints

Kelly Ann Pawlak, Jeffrey M. Epstein, Daniel Crow, Srilekha Gandhari, Ming Li, Thomas C. Bohdanowicz, Jonathan King

AI总结:

该论文提出量子子空间校正技术,通过稳定子测量检测并恢复约束违反,在独立集问题上实现完美采样,并能在次线性时间内制备精确吉布斯分布,同时可用于容错深度缩减。

摘要:

我们证明,在计算问题的伊辛表示中,可以构造出稳定满足约束子空间的算子。我们提供了一种显式方法,在给定一组约束条件下构造酉算子及相应的测量。稳定子测量能够检测约束违反,并提供恢复回约束子空间的途径。我们将此技术称为“量子子空间校正”。作为示例,我们使用最简单的局部约束子空间——独立集——显式研究了稳定子。我们发现了一种算法,当与停止条件配对时,该算法保证在所有满足约束的状态上产生完美的均匀或加权分布:这是部分拒绝采样的量子模拟。停止条件可以修改用于子图近似。我们表明,在低于临界硬度$λ_d^*$的$d$-正则图上,它能在次线性时间内制备精确的吉布斯分布。最后,我们探讨了量子子空间校正用于容错深度缩减的潜在用途。特别地,我们研究了该技术如何在使用绝热态制备算法准备最大独立集时,检测并恢复由Trotter化引起的错误。

英文摘要:

We demonstrate that it is possible to construct operators that stabilize the constraint-satisfying subspaces of computational problems in their Ising representations. We provide an explicit recipe to construct unitaries and associated measurements given a set of constraints. The stabilizer measurements allow the detection of constraint violations, and provide a route to recovery back into the constrained subspace. We call this technique ''quantum subspace correction". As an example, we explicitly investigate the stabilizers using the simplest local constraint subspace: Independent Set. We find an algorithm that is guaranteed to produce a perfect uniform or weighted distribution over all constraint-satisfying states when paired with a stopping condition: a quantum analogue of partial rejection sampling. The stopping condition can be modified for sub-graph approximations. We show that it can prepare exact Gibbs distributions on $d-$regular graphs below a critical hardness $λ_d^*$ in sub-linear time. Finally, we look at a potential use of quantum subspace correction for fault-tolerant depth-reduction. In particular we investigate how the technique detects and recovers errors induced by Trotterization in preparing maximum independent set using an adiabatic state preparation 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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