标题： 不那么平坦的度量 显示英文标题

标题： Not So Flat Metrics

摘要： 为了控制$\alpha'$导数展开，几何弦紧化是在大体积近似背景下理解的。 在本文中，我们考虑这些高阶导数项的约化，并提出一种改进的大体积近似估计，该估计使用通过机器学习方法获得的数值卡拉比-丘度量。 此外，我们在IIB弦理论的背景下，考虑数值卡拉比-丘度量的$\alpha'^3$修正。 这种修正代表了现实弦紧化的重要贡献之一——与通量和局部源的反作用等其他因素一起——所有这些对弦现象学都有重要影响。 作为校正度量的一个简单应用，我们计算了标量拉普拉斯算子谱的变化。 显示英文摘要

摘要： In order to be in control of the $\alpha'$ derivative expansion, geometric string compactifications are understood in the context of a large volume approximation. In this letter, we consider the reduction of these higher derivative terms, and propose an improved estimate on the large volume approximation using numerical Calabi-Yau metrics obtained via machine learning methods. Further to this, we consider the $\alpha'^3$ corrections to numerical Calabi-Yau metrics in the context of IIB string theory. This correction represents one of several important contributions for realistic string compactifications -- alongside, for example, the backreaction of fluxes and local sources -- all of which have important consequences for string phenomenology. As a simple application of the corrected metric, we compute the change to the spectrum of the scalar Laplacian.