Search for localized Wannier functions of topological band structures via compressed sensing
J. C. Budich, J. Eisert, E. J. Bergholtz, S. Diehl, and P. Zoller

TL;DR
This paper extends compressed sensing methods to find maximally localized Wannier functions in topological band structures, enabling systematic identification of localized representatives and exploring their existence in topological insulators.
Contribution
It develops a practical, symmetry-preserving compressed sensing framework for Wannier functions, including efficient algorithms and applications to topological superconductors and insulators.
Findings
Efficient $O(N \, log N)$ algorithm for Wannier function localization
Numerical evidence against existence of compact Wannier functions in 2D topological insulators
Benchmark results demonstrating the method's power in topological superconductors
Abstract
We investigate the interplay of band structure topology and localization properties of Wannier functions. To this end, we extend a recently proposed compressed sensing based paradigm for the search for maximally localized Wannier functions [Ozolins et al., PNAS 110, 18368 (2013)]. We develop a practical toolbox that enables the search for maximally localized Wannier functions which exactly obey the underlying physical symmetries of a translationally invariant quantum lattice system under investigation. Most saliently, this allows us to systematically identify the most localized representative of a topological equivalence class of band structures, i.e., the most localized set of Wannier functions that is adiabatically connected to a generic initial representative. We also elaborate on the compressed sensing scheme and find a particularly simple and efficient implementation in which each…
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.
