Gauging Non-Invertible Symmetries in (2+1)d Topological Orders
Mahesh K. N. Balasubramanian, Matthew Buican, Clement Delcamp, and Rajath Radhakrishnan

TL;DR
This paper develops methods to gauge non-invertible symmetries in (2+1)d topological orders, generalizing invertible symmetry gauging and providing tools for constructing non-Abelian topological phases from Abelian ones.
Contribution
It introduces formal and practical techniques for gauging non-invertible symmetries, unifying approaches for different symmetry types and exploring their implications in topological quantum field theories.
Findings
Derived constraints on gaugeable symmetries and their duals.
Unified the gauging procedures for non-invertible 0-form and 1-form symmetries.
Provided a recipe for generating non-Abelian topological orders from Abelian ones.
Abstract
We present practical and formal methods for gauging non-invertible symmetries in (2+1)d topological quantum field theories. Along the way, we generalize various aspects of invertible 0-form gauging, including symmetry fractionalization, discrete torsion, and the fixed point theorem for symmetry action on lines. Our approach involves two complementary strands: the fusion of topological interfaces and Morita theory of fusion 2-categories. We use these methods to derive constraints on gaugeable symmetries and their duals while unifying the prescription for gauging non-invertible 0-form and 1-form symmetries and various higher structures. With a view toward recent advances in creating non-Abelian topological orders from Abelian ones, we give a simple recipe for non-invertible 0-form gauging that takes large classes of the latter to the former. We also describe conditions under which…
Peer Reviews
No public reviews on file for this paper yet. If you reviewed it on a platform where reviews are public (OpenReview, ICLR, NeurIPS, ICML), you can paste yours below so the community can read it here.
Videos
No videos yet. Explain this paper in a talk, walkthrough, or lecture? Add one.
Taxonomy
TopicsOptics and Image Analysis
