Real-space observation of ergodicity transitions in artificial spin ice

Michael Saccone (), Francesco Caravelli, Kevin Hofhuis, Scott Dhuey, Andreas Scholl, Cristiano Nisoli and Alan Farhan ()
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Michael Saccone: Center for Nonlinear Studies and Theoretical Division, Los Alamos National Laboratory
Francesco Caravelli: Center for Nonlinear Studies and Theoretical Division, Los Alamos National Laboratory
Kevin Hofhuis: Laboratory for Mesoscopic Systems, Department of Materials, ETH Zurich
Scott Dhuey: Molecular Foundry, Lawrence Berkeley National Laboratory
Andreas Scholl: Advanced Light Source, Lawrence Berkeley National Laboratory
Cristiano Nisoli: Center for Nonlinear Studies and Theoretical Division, Los Alamos National Laboratory
Alan Farhan: Baylor University

Nature Communications, 2023, vol. 14, issue 1, 1-9

Abstract: Abstract Ever since its introduction by Ludwig Boltzmann, the ergodic hypothesis became a cornerstone analytical concept of equilibrium thermodynamics and complex dynamic processes. Examples of its relevance range from modeling decision-making processes in brain science to economic predictions. In condensed matter physics, ergodicity remains a concept largely investigated via theoretical and computational models. Here, we demonstrate the direct real-space observation of ergodicity transitions in a vertex-frustrated artificial spin ice. Using synchrotron-based photoemission electron microscopy we record thermally-driven moment fluctuations as a function of temperature, allowing us to directly observe transitions between ergodicity-breaking dynamics to system freezing, standing in contrast to simple trends observed for the temperature-dependent vertex populations, all while the entropy features arise as a function of temperature. These results highlight how a geometrically frustrated system, with thermodynamics strictly adhering to local ice-rule constraints, runs back-and-forth through periods of ergodicity-breaking dynamics. Ergodicity breaking and the emergence of memory is important for emergent computation, particularly in physical reservoir computing. Our work serves as further evidence of how fundamental laws of thermodynamics can be experimentally explored via real-space imaging.

Date: 2023
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DOI: 10.1038/s41467-023-41235-4

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