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Exceptionally fast spin dynamics in two-dimensional Heisenberg antiferromagnets

Giammarco FABIANI (Radboud University, Pays-Bas)
When Jun 17, 2021
from 02:00 to 03:00
Where Visioconférence
Attendees Giammarco FABIANI
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Jeudi 17 Juin

 

Title:  Exceptionally fast spin dynamics in two-dimensional Heisenberg antiferromagnets

Giammarco FABIANI (Radboud University, Pays-Bas)

 

Abstract: 

Magnons, the collective excitations of magnetic materials can oscillate up to 100 THz over a distance
of less than one nanometer. With intrinsically small energy loss, such magnons have great potential
for smaller, faster and more energy-efficient data processing. However, owing to the exceptionally
strong magnon-magnon interactions, understanding the magnon spectrum at such short
wavelengths has been challenging even for the simplest model: the antiferromagnetic Heisenberg
model in 2D [1]. As a result, studying the space-time dynamics of this model defines an intricate
quantum many-body problem out of equilibrium, for which until recently no accurate methods were
available.
Here we adopt a machine learning inspired ansatz [2] to simulate the dynamics of the 2D Heisenberg
model [3-5]. In this approach, the wavefunction of the system is approximated with a restricted
Boltzmann machine, which allows us to simulate systems up to 24x24 spins. We show that quench-
like perturbations of the exchange interaction excite dynamics of spin correlations, which spread
highly anisotropically. Interestingly, we find that magnon-magnon interactions enhance the
spreading speed up to 40% above the highest magnon velocity. Furthermore, opposed to well-
known results in one dimension, we find that the dynamics of entanglement is not determined by
the highest magnon velocity, but changes much faster on the time scale determined by the
oscillation frequency of zone-edge magnon pairs. We believe that our results are fundamental for
understanding magnetism on the shortest length and timescale and may have high impact on the
future development of faster and smaller magnon-based information processing.
[1] H. Shao et al, Phys Rev X 7, 041072(2017)
[2] G. Carleo & M. Troyer, Science 355, 602(2017)
[3] G. Fabiani & J.H. Mentink, SciPost Phys 7, 004(2019)
[4] G. Fabiani & J.H. Mentink, arXiv:1912.10845
[5] G. Fabiani, M. D. Bouman, J.H. Mentink, arXiv:2101.10945