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arxiv: 0804.2901 · v2 · submitted 2008-04-17 · ❄️ cond-mat.stat-mech

A study of the quantum classical crossover in the spin dynamics of the 2D S=5/2 antiferromagnet Rb2MnF4: neutron scattering, computer simulations, and analytic theories

classification ❄️ cond-mat.stat-mech
keywords temperatureclassicaldynamicsfoundbehavioursimulationswave-vectorantiferromagnet
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We report comprehensive inelastic neutron scattering measurements of the magnetic excitations in the 2D spin-5/2 Heisenberg antiferromagnet Rb2MnF4 as a function of temperature from deep in the Neel ordered phase up to paramagnetic, 0.13 < kBT/4JS < 1.4. Well defined spin-waves are found for wave-vectors larger than the inverse correlation length $\eta^{-1}$ for temperatures up to near the Curie-Weiss temperature, $\Theta_{CW}$. For wave-vectors smaller than $\eta^{-1}$, relaxational dynamics occurs. The observed renormalization of spin-wave energies, and evolution of excitation line-shapes, with increasing temperature are quantitatively compared with finite-temperature spin-wave theory, and computer simulations for classical spins. Random phase approximation calculations provide a good description of the low-temperature renormalisation of spin-waves. In contrast, lifetime broadening calculated using the first Born approximation shows, at best, modest agreement around the zone boundary at low temperatures. Classical dynamics simulations using an appropriate quantum-classical correspondence were found to provide a good description of the intermediate- and high-temperature regimes over all wave-vector and energy scales, and the crossover from quantum to classical dynamics observed around $\Theta_{CW}/S$, where the spin S=5/2. A characterisation of the data over the whole wave-vector/energy/temperature parameter space is given. In this, $T^2$ behaviour is found to dominate the wave-vector and temperature dependence of the line widths over a large parameter range, and no evidence of hydrodynamic behaviour or dynamical scaling behaviour found within the accuracy of the data sets.

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