English

Symmetric approximant formalism for statistical topological matter

Mesoscale and Nanoscale Physics 2026-01-05 v1 Disordered Systems and Neural Networks

Abstract

The standard approach to characterizing topological matter, computing topological invariants, fails when the symmetry protecting the topological phase is preserved only on average in a disordered system. Because topological invariants rely on enforcing the symmetry exactly, they can overcount phases by incorrectly identifying certain non-robust features as robust. Moreover, in intrinsic statistical topological insulators, enforcing the symmetry exactly is guaranteed to destroy the topological phase. We define a mapping that addresses both issues and provides a unified framework for describing disordered topological matter.

Keywords

Cite

@article{arxiv.2601.00784,
  title  = {Symmetric approximant formalism for statistical topological matter},
  author = {R. Johanna Zijderveld and Adam Yanis Chaou and Isidora Araya Day and Anton R. Akhmerov},
  journal= {arXiv preprint arXiv:2601.00784},
  year   = {2026}
}

Comments

19 pages, 6 figures

R2 v1 2026-07-01T08:48:42.510Z