PhD : Effective magnetization dynamics in coupled spintronic nano-oscillators

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Testo originale dell'annuncio (in inglese)

General Scope: Research in spintronics has advanced considerably over the past decades, both experimentally and theoretically, leading to a wide range of promising technological applications. Magnetic tunnel junctions are already employed in non-volatile memory technologies [1] due to their compact size (~100 nm), CMOS compatibility, low energy consumption, and strong resistance to radiation. These properties make them attractive candidates for the realization of artificial neurons [2], synapses [3], random number generators [4], and radiofrequency oscillators. Such devices constitute key building blocks for emerging computing paradigms, including artificial neural networks [5] and Ising machines [6]. Designing and optimizing these spintronic devices requires exploring a large parameter space, which experimentally entails substantial costs in terms of time and resources. Consequently, the development of efficient and accurate simulation approaches is essential to support experimental efforts. Simulating the dynamics of these systems remains challenging, particularly when thermal fluctuations are included through coupled stochastic differential equations, leading to significant computational demands. To address this issue, we have developed novel numerical models capable of accurately reproducing thermal effects on magnetization dynamics without relying on computationally intensive simulations [7]. These approaches provide an efficient framework for studying collective dynamics and optimizing coupled device architectures, while relying on a detailed understanding of the quantum interactions underlying magnetization dynamics. PhD Subject: This project focuses on the magnetization dynamics of magnetic nanostructures, including related quantum aspects. The objective is to investigate how different physical mechanisms—such as magnetic fields, spin-transfer torques, spin-orbit torques, and temperature effects—can be combined to enhance device performance and broaden their functionalities. Using atomistic modeling approaches spanning quantum to classical descriptions, the project will explore the magnetization dynamics of magnetic tunnel junctions under various coupling conditions, including electrical and magnetic interactions. Thermal effects will be rigorously incorporated through coupling with a quantum thermostat. The work will involve integrating spin-transfer and spin-orbit torques into the equations governing magnetic moments within a high-performance numerical framework. These equations will be solved using symplectic integration schemes to ensure accurate and stable long-term simulations. The study will subsequently be extended to networks of coupled spintronic oscillators. At each stage, thermal effects will be systematically included via a quantum thermostat, which faithfully reproduces temperature variations based on the known thermal weight of magnons in the underlying atomic system. This research will provide detailed insight into the thermal dynamics of spintronic nano-oscillators through the development of a unique atomistic simulation framework. Close collaboration with experimental partners will ensure strong alignment between the numerical investigations and the latest experimental developments in the field. [1] www.mram-info.com/tags/mram-production [2] L. Farcis et al. Nano. Lett. 23, 7869 (2023) [3] M. Mansueto et al. Phys. Rev. Applied 12, 044029 (2019) [4] N.T. Phan et al. Phys. Rev. Applied 21, 034063 (2024) [5] M. Romera et al. Nature 563, 230 (2018) [6] T. Wang et al., I., Seki, S. (eds) Unconventional Computation and Natural Computation. UCNC 2019 [7] M.Fattouhi et al, Phys. Rev. B 112, 014435 (2025), AIP Advances 16, 025324 (2026) Required Skills: • Master’s degree in Nanophysics, Nanosciences, or Physics, with a strong background in numerical modeling and programming. Knowledge of high-performance computing methods would be appreciated.