Thermal skyrmion diffusion applied in probabilistic computing (1805.05924v1)

Abstract: Thermally activated processes are key to understanding the dynamics of physical systems. Thermal diffusion of (quasi-)particles for instance not only yields information on transport and dissipation processes but is also an exponentially sensitive tool to reveal emergent system properties and enable novel applications such as probabilistic computing. Here we probe the thermal dynamics of topologically stabilized magnetic skyrmion quasi-particles. We demonstrate in a specially tailored low pinning multilayer material system pure skyrmion diffusion that dominates the dynamics. Finally, we analyse the applicability to probabilistic computing by constructing a device, which uses the thermally excited skyrmion dynamics to reshuffle a signal. Such a skyrmion reshuffler is the key missing component for probabilistic computing and by evaluating its performance, we demonstrate the functionality of our device with high fidelity thus enabling probabilistic computing.

• The paper presents experimental and numerical evidence of thermally induced skyrmion diffusion, confirmed by room-temperature MSD measurements and LLG simulations.
• It employs magneto-optical Kerr-effect imaging and generalized Thiele modeling to reveal significant thermal noise impacts on skyrmion motion in Ta/CoFeB/Ta stacks.
• The study demonstrates a novel reshuffler device that decorrelates input signals for effective probabilistic computing in energy-efficient spintronic systems.

Thermal Skyrmion Diffusion Applied in Probabilistic Computing

The paper presents an exploration of thermally activated skyrmion dynamics and their potential applications in probabilistic computing. The authors experimentally and numerically investigated the characteristics of skyrmions, which are topologically stabilized magnetic textures, within a specially designed low pinning multilayer system. By leveraging the underlying thermally induced diffusion properties of skyrmions, the authors constructed a novel device capable of reshuffling input data streams, thus serving as a crucial component for skyrmion-based probabilistic computing.

Key Findings and Methods

The investigation focused on thermally activated skyrmion diffusion within structurally asymmetric multilayer stacks of Ta/CoFeB/Ta systems, utilizing magneto-optical Kerr-effect imaging for observation. The research highlights several significant findings:

1. Diffusive Skyrmion Motion: The paper identifies pure diffusive motion for skyrmions at room temperature, as confirmed by both empirical observations and stochastic Landau-Lifshitz-Gilbert (LLG) equation-based simulations. The mean squared displacement (MSD) shows linear time dependence, leading to a diffusion coefficient $$\mathcal{D} = 0.31(15) \times 10^{-12} \, \text{m}^2/\text{s}$$ at 296 K.
2. Thermal Dynamics Models: The theoretical modeling, built upon a generalized Thiele equation, was juxtaposed with simulation results revealing notable differences. Contrary to prior assumptions, their findings emphasize that skyrmion motion is significantly influenced by thermal noise, which challenges previous conclusions regarding skyrmion stability and predictable motion in low damping systems.
3. Skyrmion Reshuffler Device: Harnessing the natural diffusive properties of skyrmions, a reshuffler device was realized. This device decorrelates the input and output signal streams while maintaining signal fidelity, thereby enabling skyrmion-based probabilistic computing. The experimental reshuffler operation maintained high signal fidelity, indicating the feasibility of using skyrmions in probabilistic computing circuits.

Theoretical and Practical Implications

The implications of this research extend into both theoretical and practical domains. Practically, the thermal skyrmion dynamics exhibit potential as key components in next-generation computing architectures, particularly those employing probabilistic paradigms rather than deterministic logic gates. Skyrmion-based devices could lead to more energy-efficient, robust systems capable of handling stochastic computing tasks with enhanced efficacy.

Theoretically, the obtained results suggest modifications to classical diffusion theory when applied to skyrmions. The deviation from the expected inverse relation between diffusion coefficients and damping highlights a critical need to re-evaluate spintronic models, specifically for magnetic quasi-particles subject to non-uniform magnetic fields and energy landscapes. Experimentation showed a size-dependent diffusion coefficient, indicating that other unaccounted forces or system properties influence skyrmion dynamics beyond established theoretical predictions.

Future Directions

While the paper provides a significant contribution to understanding skyrmion dynamics, further research is necessary. Future studies could extend the exploration of energy landscape effects on diffusion at various temperatures and skyrmion sizes, potentially refining our understanding of skyrmion interactions with complex landscapes or defects. Additionally, scaling the reshuffler device for integration into large-scale, probabilistic computing architectures remains a compelling avenue for development, and optimizing skyrmion nucleation within different material systems could unlock further applications for these magnetic textures.

To conclude, the innovative research presented in this paper underscores the potential of skyrmion-based systems in both advancing our theoretical knowledge of spintronics and paving the way for practical implementations in emerging computing frameworks.