论文标题
Brane网的脑网
Brain Webs for Brane Webs
论文作者
论文摘要
我们提出了一种新技术，用于分类由IIB字符串理论中Brane网络引起的5D超符合字段理论，使用机器学习中的技术来识别不同的网络，从而引起相同的理论。我们专注于具有三个外腿的网，对此问题类似于分类7个烤架的网。培训暹罗神经网络以确定任何两个Brane网络之间的等效性显示，当在较弱的条件下被认为等效时，性能的提高。因此，机器学习告诉我们，猜想的7个武器集的分类尚不完整，我们以明确的例子确认。
We propose a new technique for classifying 5d Superconformal Field Theories arising from brane webs in Type IIB String Theory, using technology from Machine Learning to identify different webs giving rise to the same theory. We concentrate on webs with three external legs, for which the problem is analogous to that of classifying sets of 7-branes. Training a Siamese Neural Network to determine equivalence between any two brane webs shows an improved performance when webs are considered equivalent under a weaker set of conditions. Thus, Machine Learning teaches us that the conjectured classification of 7-brane sets is not complete, which we confirm with explicit examples.
