论文标题
自旋泡沫，改进极限和重新归一化
Spin foams, Refinement limit and Renormalization
论文作者
论文摘要
自旋泡沫为量子重力提供了路径积分，这些量子重力采用了离散化作为调节剂。为了获得独立的预测，我们必须在适当的细化极限中去除这些基准结构。在本章中，我们介绍了当前的研究状态：我们首先讨论了差异性对称性在离散系统中的作用，在背景独立理论中规模的概念以及我们如何通过恢复性化来始终如一地改善理论以降低调节器的依赖性。我们提出了一致的边界公式，该公式为背景独立理论提供了重新归一化的框架，并讨论了张量网络方法和受限的自旋泡沫，该泡沫提供了旨在构建旋转泡沫的一致边界振幅的具体重新归一化算法。我们还讨论了有效的自旋泡沫，这些泡沫允许构建扰动精致极限和相关的有效连续作用。
Spin foams provide path integrals for quantum gravity, which employ discretizations as regulator. To obtain regulator independent predictions, we must remove these fiducial structures in a suitable refinement limit. In this chapter we present the current state of research: We begin with a discussion on the role of diffeomorphism symmetries in discrete systems, the notion of scale in background independent theories and how we can consistently improve theories via renormalization to reduce regulator dependence. We present the consistent boundary formulation, which provides a renormalization framework for background independent theories, and discuss tensor network methods and restricted spin foams, which provide concrete renormalization algorithms aiming at the construction of consistent boundary amplitudes for spin foams. We furthermore discuss effective spin foams, which have allowed for the construction of a perturbative refinement limit and an associated effective continuum action.
