Extracting average properties of disordered spin chains with translationally invariant tensor networks
Year: 2026
Type: article
Abstract: We develop a tensor network-based method for calculating disorder-averaged finite-temperature expectation values in random spin chains without having to explicitly sample over disorder configurations. The algorithm exploits statistical translation invariance and works directly in the thermodynamic limit. We benchmark our method on the infinite-randomness critical point of the random transverse field Ising model.
Source: SciPost Physics Core
Authors: Kevin Vervoort, Wei Tang, Nick Bultinck
Institution: Ghent University
Language: English
Topic: Quantum many-body systems
Subfield: Atomic and Molecular Physics, and Optics
Field: Physics and Astronomy
Domain: Physical Sciences
Open Access status: diamond
OpenAlex ID: W4417521546
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