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量子算法在连续吉布斯采样中实现可证明分离

研究人员已经证明了在连续吉布斯采样问题上存在可证明的量子-经典分离。他们的发现表明,经典算法需要指数级的查询才能从某些吉布斯状态进行采样,而量子算法可以用显著更少的查询来实现相同的精度。这种优势在较低的温度和较高的维度下更为明显,暗示了量子计算在复杂采样任务中的潜力。 AI

影响 展示了量子在复杂采样任务中具有优势的潜力,与未来AI研究相关。

排序理由 该集群包含一篇详细介绍量子计算新理论成果的学术论文。[lever_c_demoted from research: ic=1 ai=0.7]

在 arXiv cs.LG 阅读 →

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量子算法在连续吉布斯采样中实现可证明分离

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该集群包含一篇详细介绍量子计算新理论成果的学术论文。[lever_c_demoted from research: ic=1 ai=0.7]
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报道来源 [1]

  1. arXiv cs.LG TIER_1 English(EN) · Enrico Olivucci, Mariia Sobchuk, Sehmimul Hoque, Jeffrey Hnybida, Kyungho W. Kim, Ala Shayeghi, Pooya Ronagh ·

    连续Gibbs采样可证明的量子-经典分离

    arXiv:2608.24527v1 Announce Type: cross Abstract: We prove the first quantum--classical separation for a sampling problem over a continuous domain. For a class of Gibbs states $p\propto e^{-\beta E}$ on the torus $\mathbb{T}^d$ with smooth ($s$-Gevrey) potential and barrier ampli…