Contrast data mining for the MSSM from strings

We apply techniques from data mining to the heterotic orbifold landscape in order to identify new MSSM-like string models. To do so, so-called contrast patterns are uncovered that help to distinguish between areas in the landscape that contain MSSM-like models and the rest of the landscape. First, we develop these patterns in the well-known Z(6)-II orbifold geometry and then we generalize them to all other Z(N) orbifold geometries. Our contrast patterns have a clear physical interpretation and are easy to check for a given string model. Hence, they can be used to scale down the potentially interesting area in the landscape, which significantly enhances the search for MSSM-like models. Thus, by deploying the knowledge gain from contrast mining into a new search algorithm we create many novel MSSM-like models, especially in corners of the landscape that were hardly accessible by the conventional search algorithm, for example, MSSM-like Z(6)-II models with Delta(54) flavor symmetry. (C) 2020 The Author(s). Published by Elsevier B.V.