Detecting Complex-Energy Braiding Topology in a Dissipative Atomic Simulator with Transformer-Based Geometric Tomography
Abstract
The Transformer-based machine learning framework effectively captures the topology-geometry interplay in energy band braiding. We validate this by constructing tunable dissipative two-level systems and extracting their complex eigenenergies. This repository provides the experimental fitting results based on BEC.
Fields of Study & Subjects
Topological Materials and Phenomena
Quantum Mechanics and Non-Hermitian Physics
Cold Atom Physics and Bose-Einstein Condensates
Publication details
- Journal / source
- Zenodo (CERN European Organization for Nuclear Research)
- Publication date
- 9 February 2026
- Document type
- Dataset