From the 1 of 6 linked papers with an AI index.
6 papers
Learning to Trace Seiberg Dualities
Jonathan J. Heckman, Shani Meynet, Alessandro Mininno +1
The paper applies machine learning, including transformers and MLPs, to identify Seiberg dualities in supersymmetric quiver gauge theories by learning quiver mutations, showing imp…
Exploring Line Bundle Standard Models with Transformers
Jacky H. T. Yip, Alessandro Mininno, Gary Shiu
We propose a Transformer-based Reinforcement Learning architecture, "LB-Explorer", to search for heterotic line bundle standard models arising from compactifications on smooth Cala…
Generating Special Triangulations with Transformers
Charles Arnal, Jacky H. T. Yip, François Charton +1
Triangulations, i.e., well-structured decompositions of geometric objects into triangle-like pieces, are central objects in many domains of mathematics and physics. In particular,…
Primordial non-Gaussianity -- Fast simulations and persistent summary statistics
Juan Calles, Gabriella Contardo, Jorge Noreña +3
We investigate the sensitivity of topological and traditional summary statistics to primordial non-Gaussianity (PNG) using two suites of simulations. First, we introduce a new simu…
Transforming Calabi-Yau Constructions: Generating New Calabi-Yau Manifolds with Transformers
Jacky H. T. Yip, Charles Arnal, François Charton +1
Fine, regular, and star triangulations (FRSTs) of four-dimensional reflexive polytopes give rise to toric varieties, within which generic anticanonical hypersurfaces yield smooth C…
Cosmology with Persistent Homology: Parameter Inference via Machine Learning
Juan Calles, Jacky H. T. Yip, Gabriella Contardo +3
Building upon [2308.02636], we investigate the constraining power of persistent homology on cosmological parameters and primordial non-Gaussianity in a likelihood-free inference pi…