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arXiv 1209.3252math-phhep-thmath.MP
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随机张量模型的1/N展开

A review of the 1/N expansion in random tensor models

Razvan Gurau

摘要:

矩阵模型是一个非常成功的框架分析研究随机二维表面的应用量子引力在二维,弦论,共形场论,统计物理在随机几何等,他们的成功依赖于所谓的1/N展开介绍了特胡夫特。在更高维度中,矩阵模型推广到张量模型。在缺乏可行的1/N展开张量模型已经很长一段时间不太成功地提供了一个分析控制理论的随机高维拓扑空间。这种情况最近发生了巨大变化。一般复张量的模型已被证明允许由任意维度的球形拓扑图主导的1/N展开,并经历到连续统理论的相变。

英文摘要:

Matrix models are a highly successful framework for the analytic study of random two dimensional surfaces with applications to quantum gravity in two dimensions, string theory, conformal field theory, statistical physics in random geometry, etc. Their success relies crucially on the so called 1/N expansion introduced by 't Hooft. In higher dimensions matrix models generalize to tensor models. In the absence of a viable 1/N expansion tensor models have for a long time been less successful in providing an analytically controlled theory of random higher dimensional topological spaces. This situation has drastically changed recently. Models for a generic complex tensor have been shown to admit a 1/N expansion dominated by graphs of spherical topology in arbitrary dimensions and to undergo a phase transition to a continuum theory.

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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