arXivDaily arXiv每日学术速递 周一至周五更新
arXiv 2002.12814quant-phcs.CC
收藏

关于估计浅层电路输出熵的研究

On estimating the entropy of shallow circuit outputs

Alexandru Gheorghiu, Matty J. Hoban

AI总结:

本文证明由对数深度或常数深度浅层量子电路产生的分布或态的熵估计至少与LWE问题一样困难,并给出其处于中间困难区间的复杂性理论证据,同时探讨了对AdS/CFT量子引力研究的潜在应用。

摘要:

估计概率分布和量子态的熵是信息处理中的一项基本任务。在此,我们研究了当概率分布或量子态由浅层电路产生时,这一任务的困难性。具体而言,我们证明,对于由对数深度电路或具有有界扇入和无界扇出的常数深度电路所产生的分布或态,熵估计的难度至少与带误差学习(LWE)问题相当,因此即使对于高效的量子计算也被认为是不可行的。这表明量子电路无需复杂即可使熵的计算成为一项困难任务。我们还给出了复杂性理论证据,表明对数深度电路的这一问题不像一般多项式规模电路的对应问题那样困难,似乎处于一个中间困难区间。最后,我们通过将我们的结果与AdS/CFT的体-边界字典的复杂性联系起来,讨论了我们工作在未来量子引力研究中的潜在应用。

英文摘要:

Estimating the entropy of probability distributions and quantum states is a fundamental task in information processing. Here, we examine the hardness of this task for the case of probability distributions or quantum states produced by shallow circuits. Specifically, we show that entropy estimation for distributions or states produced by either log-depth circuits or constant-depth circuits with gates of bounded fan-in and unbounded fan-out is at least as hard as the Learning with Errors (LWE) problem, and thus believed to be intractable even for efficient quantum computation. This illustrates that quantum circuits do not need to be complex to render the computation of entropy a difficult task. We also give complexity-theoretic evidence that this problem for log-depth circuits is not as hard as its counterpart with general polynomial-size circuits, seemingly occupying an intermediate hardness regime. Finally, we discuss potential future applications of our work for quantum gravity research by relating our results to the complexity of the bulk-to-boundary dictionary of AdS/CFT.

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。

↑