Reconstruction of modular data from representations
arXiv:2203.14829 · doi:10.1007/s00220-023-04775-w
Abstract
Modular data is the most significant invariant of a modular tensor category. We pursue an approach to the classification of modular data of modular tensor categories by building the modular and matrices directly from irreducible representations of . We discover and collect many conditions on the representations to identify those that correspond to some modular data. To arrive at concrete matrices from representations, we also develop methods that allow us to select the proper basis of the representations so that they have the form of modular data. We apply this technique to the classification of rank- modular tensor categories, obtaining a classification up to modular data. Most of the calculations can be automated using a computer algebraic system, which can be employed to classify modular data of higher rank modular tensor categories.
78pp Latex and 271pp of supplementary materials
References in corpus (1)
Cited by in corpus (6)
- Bosonic Rational Conformal Field Theories in Small Genera, Chiral Fermionization, and Symmetry/Subalgebra Duality
- Gapped Phases in (2+1)d with Non-Invertible Symmetries: Part I
- Classification of Fermionic Topological Orders from Congruence Representations
- Gapped boundaries of fermionic topological orders and higher central charges
- Modular extension of topological orders from congruence representations
- Classification of integral modular data up to rank 13