Probing the Topology of Fermionic Gaussian Mixed States with {U(1)} symmetry by Full Counting Statistics
Liang Mao, Hui Zhai, and Fan Yang

TL;DR
This paper introduces a method to detect topological features in fermionic Gaussian mixed states using full counting statistics, revealing stable gapless modes and topological invariants in systems with U(1) symmetry.
Contribution
It presents a novel approach to identify topological invariants in mixed states via full counting statistics and gapless mode detection.
Findings
Full counting statistics can detect gapless modes in modular Hamiltonians.
A topological indicator quantized to unity signals nontrivial mixed states.
Validated with models in one- and two-dimensional systems.
Abstract
Topological band theory has been studied for free fermions for decades, and one of the most profound physical results is the bulk-boundary correspondence. Recently a focus in topological physics is extending topological classification to mixed states. Here, we focus on Gaussian mixed states where the modular Hamiltonians of the density matrix are quadratic free fermion models with {U(1)} symmetry and can be classified by topological invariants. The bulk-boundary correspondence is then manifested as stable gapless modes of the modular Hamiltonian and degenerate spectrum of the density matrix. In this article, we show that these gapless modes can be detected by the full counting statistics, mathematically described by a function introduced as {F(\theta)}. A divergent derivative at {\theta=\pi} can be used to probe the gapless modes in the modular Hamiltonian. Based on this, a topological…
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Taxonomy
TopicsGaussian Processes and Bayesian Inference · Scientific Research and Discoveries · Neural Networks and Applications
