We continue earlier efforts in computing the dimensions of tangent space cohomologies of Calabi–Yau manifolds using deep learning. In this paper, we consider the dataset of all Calabi–Yau fourfolds constructed as complete intersections in products of projective spaces. Employing neural networks inspired by stateoftheart computer vision architectures, we improve earlier benchmarks and demonstrate that all four nontrivial Hodge numbers can be learned at the same time using a multitask architecture. With 30% (80%) training ratio, we reach an accuracy of 100% for
The best upper limit for the electron electric dipole moment was recently set by the ACME collaboration. This experiment measures an electron spinprecession in a cold beam of ThO molecules in their metastable
 Publication Date:
 NSFPAR ID:
 10303201
 Journal Name:
 New Journal of Physics
 Volume:
 22
 Issue:
 2
 Page Range or eLocationID:
 Article No. 023013
 ISSN:
 13672630
 Publisher:
 IOP Publishing
 Sponsoring Org:
 National Science Foundation
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