自旋泡沫大尺度结构的计算研究
Towards computational insights into the large-scale structure of spin foams
摘要：
理解大尺度物理对于量子引力的自旋泡沫方法至关重要。我们从统计物理学的角度使用简化但功能丰富的模型来应对这一挑战。特别是，这使我们能够明确地回答是否打破对称性将恢复重整化：我们观察到一个弱的相变在Migdal-Kadanoff和张量网络重整化。在这项工作中，我们给出了一个简洁的介绍的概念，结果和承诺，这一新的研究方向。
英文摘要：
Understanding the large-scale physics is crucial for the spin foam approach to quantum gravity. We tackle this challenge from a statistical physics perspective using simplified, yet feature-rich models. In particular, this allows us to explicitly answer whether broken symmetries will be restored by renormalization: We observe a weak phase transition in both Migdal-Kadanoff and tensor network renormalization. In this work we give a concise presentation of the concepts, results and promises of this new direction of research.
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