标题： 在高斯随机景观中的通胀 显示英文标题

标题： Inflation in a Gaussian Random Landscape

摘要： 随机的多场函数可以为景观型宇宙学设定一般性预期。 我们考虑由高斯随机函数定义的景观的暴胀含义，这可能是最简单的此类情景。 该景观的许多关键特性，包括势能中鞍点随高度的分布，仅取决于其维度$N$和一个参数${\gamma}$，该参数由随机函数的功率谱决定。 我们证明，对于只有一个下坡方向的鞍点，相对于平均质量，负质量项会随着$N$的增加而变小，这一结果可能对景观情景中的${\eta}$问题有潜在影响。 对于某些功率谱，普朗克尺度的鞍点具有${\eta} \sim 1$，并且永恒的拓扑暴胀在这些情景中会很常见。 低处的鞍点通常具有较大的${\eta}$，但其中能够支持暴胀的鞍点比例是可以计算的，这使我们能够确定哪些情景可以产生类似于我们的宇宙。 最后，通过推断不同多元宇宙提议的相对可行性，我们还说明了定量分析多元宇宙情景是可行的。 显示英文摘要

摘要： Random, multifield functions can set generic expectations for landscape-style cosmologies. We consider the inflationary implications of a landscape defined by a Gaussian random function, which is perhaps the simplest such scenario. Many key properties of this landscape, including the distribution of saddles as a function of height in the potential, depend only on its dimensionality, $N$, and a single parameter, ${\gamma}$, which is set by the power spectrum of the random function. We show that for saddles with a single downhill direction the negative mass term grows smaller, relative to the average mass, as $N$ increases, a result with potential implications for the ${\eta}$-problem in landscape scenarios. For some power spectra Planck-scale saddles have ${\eta} \sim 1$ and eternal, topological inflation would be common in these scenarios. Lower-lying saddles typically have large ${\eta}$, but the fraction of these saddles which would support inflation is computable, allowing us to identify which scenarios can deliver a universe that resembles ours. Finally, by drawing inferences about the relative viability of different multiverse proposals we also illustrate ways in which quantitative analyses of multiverse scenarios are feasible.