Topological spin excitations in non-Hermitian spin chains with a generalized kernel polynomial algorithm

• URL: http://arxiv.org/abs/2208.06425v1
• Date: Fri, 12 Aug 2022 18:00:07 GMT
• Title: Topological spin excitations in non-Hermitian spin chains with a generalized kernel polynomial algorithm
• Authors: Guangze Chen, Fei Song and Jose L. Lado
• Abstract summary: We show a numerical approach to compute spectral functions of a non-Hermitian many-body system. We show that the local spectral functions reveal topological spin excitations in a non-Hermitian spin model. Our method offers an efficient way to compute local spectral functions in non-Hermitian quantum many-body models.
• Score: 1.054316838380053
• License: http://arxiv.org/licenses/nonexclusive-distrib/1.0/
• Abstract: Spectral functions of non-Hermitian Hamiltonians can reveal the existence of topologically non-trivial line gaps and the associated topological edge modes. However, the computation of spectral functions in a non-Hermitian many-body system remains an open challenge. Here, we put forward a numerical approach to compute spectral functions of a non-Hermitian many-body Hamiltonian based on the kernel polynomial method and the matrix-product state formalism. We show that the local spectral functions computed with our algorithm reveal topological spin excitations in a non-Hermitian spin model, faithfully reflecting the non-trivial line gap topology in a many-body model. We further show that the algorithm works in the presence of the non-Hermitian skin effect. Our method offers an efficient way to compute local spectral functions in non-Hermitian many-body systems with tensor-networks, allowing to characterize line gap topology in non-Hermitian quantum many-body models.

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