The classical two-dimensional Heisenberg model revisited: An $SU(2)$-symmetric tensor network study
Philipp Schmoll, Augustine Kshetrimayum, Jens Eisert, Roman Orus,, Matteo Rizzi

TL;DR
This study uses advanced tensor network methods to analyze the classical 2D Heisenberg model, providing insights into its phase transition behavior and supporting the asymptotic freedom hypothesis.
Contribution
The paper introduces an $SU(2)$-symmetric tensor network approach to accurately study the classical Heisenberg model at large scales and temperatures.
Findings
Correlation length diverges rapidly at low temperatures
Results are compatible with asymptotic freedom hypothesis
No definitive evidence of finite-temperature phase transition
Abstract
The classical Heisenberg model in two spatial dimensions constitutes one of the most paradigmatic spin models, taking an important role in statistical and condensed matter physics to understand magnetism. Still, despite its paradigmatic character and the widely accepted ban of a (continuous) spontaneous symmetry breaking, controversies remain whether the model exhibits a phase transition at finite temperature. Importantly, the model can be interpreted as a lattice discretization of the non-linear sigma model in dimensions, one of the simplest quantum field theories encompassing crucial features of celebrated higher-dimensional ones (like quantum chromodynamics in dimensions), namely the phenomenon of asymptotic freedom. This should also exclude finite-temperature transitions, but lattice effects might play a significant role in correcting the mainstream picture. In…
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