87 citations · 259 across the 22 of their papers we have counts for
14 papers · 1 filter
Balanced Metrics Know About SYZ
Per Berglund, Tristan Hübsch, Vishnu Jejjala +2
Numerical Ricci-flat metrics on Calabi-Yau manifolds are becoming increasingly accurate. However, they often lack the interpretability required to extract theoretical insights. In…
Hermitian Yang--Mills connections on general vector bundles: geometry and physical Yukawa couplings
Challenger Mishra, Justin Tan
We compute solutions to the Hermitian Yang-Mills equations on holomorphic vector bundles via an alternating optimisation procedure founded on geometric machine learning. The pr…
cymyc -- Calabi-Yau Metrics, Yukawas, and Curvature
Per Berglund, Giorgi Butbaia, Tristan Hübsch +4
We introduce \texttt{cymyc}, a high-performance Python library for numerical investigation of the geometry of a large class of string compactification manifolds and their associate…
Precision String Phenomenology
Per Berglund, Giorgi Butbaia, Tristan Hübsch +4
Calabi--Yau compactifications of the heterotic string provide a promising route to recovering the four-dimensional particle physics described by the Standard Model.…
Physical Yukawa Couplings in Heterotic String Compactifications
Giorgi Butbaia, Damián Mayorga Peña, Justin Tan +4
One of the challenges of heterotic compactification on a Calabi-Yau threefold is to determine the physical Yukawa couplings of the resulting four-dimensional $\ma…
Machine Learned Calabi-Yau Metrics and Curvature
Per Berglund, Giorgi Butbaia, Tristan Hübsch +4
Finding Ricci-flat (Calabi-Yau) metrics is a long standing problem in geometry with deep implications for string theory and phenomenology. A new attack on this problem uses neural…
Neural Network Approximations for Calabi-Yau Metrics
Vishnu Jejjala, Damian Kaloni Mayorga Pena, Challenger Mishra
Ricci flat metrics for Calabi-Yau threefolds are not known analytically. In this work, we employ techniques from machine learning to deduce numerical flat metrics for the Fermat qu…
Getting CICY High
Kieran Bull, Yang-Hui He, Vishnu Jejjala +1
Supervised machine learning can be used to predict properties of string geometries with previously unknown features. Using the complete intersection Calabi-Yau (CICY) threefold dat…
Machine Learning CICY Threefolds
Kieran Bull, Yang-Hui He, Vishnu Jejjala +1
The latest techniques from Neural Networks and Support Vector Machines (SVM) are used to investigate geometric properties of Complete Intersection Calabi-Yau (CICY) threefolds, a c…
Discrete Symmetries of Complete Intersection Calabi-Yau Manifolds
Andre Lukas, Challenger Mishra
In this paper, we classify non-freely acting discrete symmetries of complete intersection Calabi- Yau manifolds and their quotients by freely-acting symmetries. These non-freely ac…
Highly Symmetric Quintic Quotients
Philip Candelas, Challenger Mishra
The quintic family must be the most studied family of Calabi-Yau threefolds. Particularly symmetric members of this family are known to admit quotients by freely acting symmetries…
Calabi-Yau Threefolds With Small Hodge Numbers
Philip Candelas, Andrei Constantin, Challenger Mishra
We present a list of Calabi-Yau threefolds known to us, and with holonomy groups that are precisely SU(3), rather than a subgroup, with small Hodge numbers, which we understand to…
Hodge Numbers for CICYs with Symmetries of Order Divisible by 4
Philip Candelas, Andrei Constantin, Challenger Mishra
We compute the Hodge numbers for the quotients of complete intersection Calabi-Yau three-folds by groups of orders divisible by 4. We make use of the polynomial deformation method…
The Family Problem: Hints from Heterotic Line Bundle Models
Andrei Constantin, Andre Lukas, Challenger Mishra
Within the class of heterotic line bundle models, we argue that N=1 vacua which lead to a small number of low-energy chiral families are preferred. By imposing an upper limit on th…