arXiv subjects

Dieter Suess

Publications and source records attributed to Dieter Suess.

At least 55 records · Page 3Linked to original sources

arXiv2024

Magnetic anisotropy and GGG substrate stray field in YIG films down to millikelvin temperatures

Quantum magnonics investigates the quantum-mechanical properties of magnons such as quantum coherence or entanglement for solid-state quantum information technologies at the nanoscale. The most promising material for quantum magnonics is the ferrimagnetic yttrium iron garnet (YIG), which hosts magnons with the longest lifetimes. YIG films of the highest quality are grown on a paramagnetic gadolinium gallium garnet (GGG) substrate. The literature has reported that ferromagnetic resonance (FMR) frequencies of YIG/GGG decrease at temperatures below 50 K despite the increase in YIG magnetization. We investigated a 97 nm-thick YIG film grown on 500 $\mathrmμ$m-thick GGG substrate through a series of experiments conducted at temperatures as low as 30 mK, and using both analytical and numerical methods. Our findings suggest that the primary factor contributing to the FMR frequency shift is the stray magnetic field created by the partially magnetized GGG substrate. This stray field is antiparallel to the applied external field and is highly inhomogeneous, reaching up to 40 mT in the center of the sample. At temperatures below 500 mK, the GGG field exhibits a saturation that cannot be described by the standard Brillouin function for a paramagnet. Including the calculated GGG field in the analysis of the FMR frequency versus temperature dependence allowed the determination of the cubic and uniaxial anisotropies. We find that the total anisotropy increases more than three times with the decrease in temperature down to 2 K. Our findings enable accurate predictions of the YIG/GGG magnetic systems behavior at low and ultra-low millikelvin temperatures, crucial for developing quantum magnonic devices.

cond-mat.mes-hall↗

arXiv2023

Nonreciprocal Spin Waves in Nanoscale Domain Walls Detected by Scanning X-ray Microscopy in Perpendicular Magnetic Anisotropic Fe/Gd Multilayers

Spin wave nonreciprocity in domain walls (DWs) allows for unidirectional signal processing in reconfigurable magnonic circuits. Using scanning transmission x-ray microscopy (STXM), we examined coherently-excited magnons propagating in Bloch-like DWs in amorphous Fe/Gd multilayers with perpendicular magnetic anisotropy (PMA). Near 1 GHz we detected magnons with short wavelengths down to $λ= 281$ nm in DWs whose minimum width amounted to $δ_{\rm DW} = 52$ nm. Consistent with micromagnetic simulations, the STXM data reveal their nonreciprocal magnon band structures. We identified Bloch points which disrupted the phase evolution of magnons and induced different $λ$ adjacent to the topological defects. Our observations provide direct evidence of nonreciprocal spin waves within Bloch-like DWs, serving as programmable waveguides in magnonic devices with directed information flow.

cond-mat.mes-hall↗

arXiv2023

Parallel-in-Time Integration of the Landau-Lifshitz-Gilbert Equation with the Parallel Full Approximation Scheme in Space and Time

Speeding up computationally expensive problems, such as numerical simulations of large micromagnetic systems, requires efficient use of parallel computing infrastructures. While parallelism across space is commonly exploited in micromagnetics, this strategy performs poorly once a minimum number of degrees of freedom per core is reached. We use magnum.pi, a finite-element micromagnetic simulation software, to investigate the Parallel Full Approximation Scheme in Space and Time (PFASST) as a space- and time-parallel solver for the Landau-Lifshitz-Gilbert equation (LLG). Numerical experiments show that PFASST enables efficient parallel-in-time integration of the LLG, significantly improving the speedup gained from using a given number of cores as well as allowing the code to scale beyond spatial limits.

physics.comp-ph↗

arXiv2023

Laser-induced real-space topology control of spin wave resonances

Femtosecond laser excitation of materials that exhibit magnetic spin textures promises advanced magnetic control via the generation of ultrafast and non-equilibrium spin dynamics. We explore such possibilities in ferrimagnetic [Fe(0.35 nm)/Gd(0.40 nm)]$_{160}$ multilayers, which host a rich diversity of magnetic textures from stripe domains at low magnetic fields, a dense bubble/skyrmion lattice at intermediate fields, and a single domain state for high magnetic fields. Using femtosecond magneto-optics, we observe distinct coherent spin wave dynamics in response to a weak laser excitation allowing us to unambiguously identify the different magnetic spin textures. Moreover, employing strong laser excitation we show that we achieve versatile control of the coherent spin dynamics via non-equilibrium and ultrafast transformation of magnetic spin textures by both creating and annihilating bubbles/skyrmions. We corroborate our findings by micromagnetic simulations and by Lorentz transmission electron microscopy before and after laser exposure.

cond-mat.mtrl-sci↗

arXiv2023

Single device offset-free magnetic field sensing principle with tunable sensitivity and linear range based on spin-orbit-torques

We propose a novel device concept using spin-orbit-torques to realize a magnetic field sensor, where we eliminate the sensor offset using a differential measurement concept. We derive a simple analytical formulation for the sensor signal and demonstrate its validity with numerical investigations using macrospin simulations. The sensitivity and the measurable linear sensing range in the proposed concept can be tuned by either varying the effective magnetic anisotropy or by varying the magnitude of the injected currents. We show that undesired perturbation fields normal to the sensitive direction preserve the zero-offset property and only slightly modulate the sensitivity of the proposed sensor. Higher-harmonics voltage analysis on a Hall cross experimentally confirms the linearity and tunability via current strength. Additionally, the sensor exhibits a non-vanishing offset in the experiment which we attribute to the anomalous Nernst effect.

cond-mat.mes-hall↗

arXiv2023

magnum.np -- A PyTorch based GPU enhanced Finite Difference Micromagnetic Simulation Framework for High Level Development and Inverse Design

magnum.np is a micromagnetic finite-difference library completely based on the tensor library PyTorch. The use of such a high level library leads to a highly maintainable and extensible code base which is the ideal candidate for the investigation of novel algorithms and modeling approaches. On the other hand magnum.np benefits from the devices abstraction and optimizations of PyTorch enabling the efficient execution of micromagnetic simulations on a number of computational platforms including GPU and potentially TPU systems. We demonstrate a competitive performance to state-of-the art micromagnetic codes such a mumax3 and show how our code enables the rapid implementation of new functionality. Furthermore, handling inverse problems becomes possible by using PyTorch's autograd feature.

physics.comp-ph↗

arXiv2023

Physics-informed machine learning and stray field computation with application to micromagnetic energy minimization

We study the full 3d static micromagnetic equations via a physics-informed neural network (PINN) ansatz for the continuous magnetization configuration. PINNs are inherently mesh-free and unsupervised learning models. In our approach we can learn to minimize the total Gibbs free energy with additional conditional parameters, such as the exchange length, by a single low-parametric neural network model. In contrast, traditional numerical methods would require the computation and storage of a large number of solutions to interpolate the continuous spectrum of quasi-optimal magnetization configurations. We also consider the important and computationally expensive stray field problem via PINNs, where we use a basically linear learning ansatz, called extreme learning machines (ELM) within a splitting method for the scalar potential. This reduces the stray field training to a linear least squares problem with precomputable solution operator. We validate the stray field method by means of numerical example comparisons from literature and illustrate the full micromagnetic approach via the NIST $μ$MAG standard problem $\#3$.

physics.comp-ph↗

arXiv2022

Self-consistent solution of magnetic and friction energy losses of a magnetic nanoparticle

We present a simple simulation model for analysing magnetic and frictional losses of magnetic nano-particles in viscous fluids subject to alternating magnetic fields. Assuming a particle size below the single-domain limit, we use a macrospin approach and solve the Landau-Lifshitz-Gilbert equation coupled to the mechanical torque equation. Despite its simplicity the presented model exhibits surprisingly rich physics and enables a detailed analysis of the different loss processes depending on field parameters and initial arrangement of the particle and the field. Depending on those parameters regions of different steady states emerge: a region with dominating Néel relaxation and high magnetic losses and another region region with high frictional losses at low fields or low frequencies. The energy increases continuously even across regime boundaries up to frequencies above the Brownian relaxation limit. At those higher frequencies the steady state can also depend on the initial orientation of the particle in the external field. The general behavior and special cases and their specific absorption rates are compared and discussed.

physics.atm-clus↗

arXiv2022

Generation and annihilation of skyrmions and antiskyrmions in magnetic heterostructures

We demonstrate the controlled generation and annihilation of (anti)skyrmions with tunable chirality in magnetic heterostructures by means of micromagnetic simulations. By making use of magnetic (anti)vortices in patterned ferromagnetic layer, we stabilize full lattices of (anti)skyrmions in an underlying skyrmionic thin film in a reproducible manner. The stability of the (anti)skyrmion depends on the polarization of the (anti)vortex, whereas their chirality is given by those of the (anti)vortices. Furthermore, we demonstrate that the core coupling between the (anti)vortices and (anti)skyrmions allows to annihilate the spin-objects in a controlled fashion by applying short pulses of in-plane external magnetic fields, representing a new key paradigm in skyrmionic devices.

cond-mat.mes-hall↗

arXiv2022

Accurate finite-difference micromagnetics of magnets including RKKY interaction -- analytical solution and comparison to standard micromagnetic codes

Within this paper we show the importance of accurate implementations of the RKKY interactions for antiferromagnetically coupled ferromagnetic layers with thicknesses exceeding the exchange length. In order to evaluate the performance of different implementations of RKKY interaction, we develop a benchmark problem by deriving the analytical formula for the saturation field of two infinitely thick magnetic layers that are antiparallelly coupled. This benchmark problem shows that state-of-the-art implementations in commonly used finite-difference codes lead to errors of the saturation field that amount to more than 20% for mesh sizes of 2 nm which is well below the exchange length of the material. In order to improve the accuracy, we develop higher order cell based and nodal based finite-difference codes that significantly reduce the error compared to state-of-the-art implementations. For the second order cell based and first order nodal based finite element approach the error of the saturation field is reduced by about a factor of 10 (2% error) for the same mesh size of 2 nm.

cond-mat.mtrl-sci↗

arXiv2022

On the origin of noncollinear magnetization coupling across RuX layers

We present a simple atomistic model for the description of noncollinear coupling in magnetic multilayers with hybrid spacer layers made of Ru alloyed to ferromagnetic atoms such as Fe. In contrast to previous analytical and micromagnetic models that explain the noncollinear coupling by means of lateral fluctuations in the coupling constant, the presented model accounts for atom-atom coupling in all three spatial dimensions within the spacer layer. The new model is able to accurately predict the dependence of the macroscopic bilinear and biquadratic coupling constants on the spacer-layer composition and thickness, showing much better quantitative agreement than lateral-fluctuation models. Moreover, it predicts noncollinear coupling even for infinitely stiff ferromagnetic layers which goes beyond the predictions of previous models.

cond-mat.mtrl-sci↗

arXiv2022

In-situ alignment of anisotropic hard magnets of 3D printed magnets

Within this work, we demonstrate in-situ easy-axis alignment of single-crystal magnetic particles inside a polymer matrix using fused filament fabrication. Two different magnetic materials are investigated: (i) Strontium hexaferrite inside a PA6 matrix, fill grade: 49 vol% and (ii) Samarium iron nitride inside a PA12 matrix, fill grade: 44 vol%. In the presence of the external alignment field, the strontium hexaferrite particles inside the PA6 matrix can be well aligned with a ratio of remanent magnetization to saturation magnetization of 0.7. No significant alignment for samarium iron nitride could be achieved. The results show the feasibility to fabricate magnets with arbitrary and locally defined easy axis using fused filament fabrication since the permanent magnets used for the alignment (or alternatively an electromagnet) can be mounted on a rotatable platform.

cond-mat.mtrl-sci↗

arXiv2021

Full analytical solution for the magnetic field of uniformly magnetized cylinder tiles

We present an analytical solution for the magnetic field of a homogeneously magnetized cylinder tile and by extension solutions for full cylinders, rings, cylinder sectors and ring segments. The derivation is done by direct integration in the magnetic surface charge picture. Results are closed-form expressions and elliptic integrals. All special cases are treated individually, which enables the field computation for all possible position arguments. An implementation is provided in Python together with a performance analysis. The implementation is tested against numerical solutions and applied to compute the magnetic field in a discrete Halbach cylinder.

physics.class-ph↗

arXiv2021

Prediction of magnetization dynamics in a reduced dimensional feature space setting utilizing a low-rank kernel method

We establish a machine learning model for the prediction of the magnetization dynamics as function of the external field described by the Landau-Lifschitz-Gilbert equation, the partial differential equation of motion in micromagnetism. The model allows for fast and accurate determination of the response to an external field which is illustrated by a thin-film standard problem. The data-driven method internally reduces the dimensionality of the problem by means of nonlinear model reduction for unsupervised learning. This not only makes accurate prediction of the time steps possible, but also decisively reduces complexity in the learning process where magnetization states from simulated micromagnetic dynamics associated with different external fields are used as input data. We use a truncated representation of kernel principal components to describe the states between time predictions. The method is capable of handling large training sample sets owing to a low-rank approximation of the kernel matrix and an associated low-rank extension of kernel principal component analysis and kernel ridge regression. The approach entirely shifts computations into a reduced dimensional setting breaking down the problem dimension from the thousands to the tens.

physics.comp-ph↗

arXiv2021

Proposal for a micromagnetic standard problem: domain wall pinning at phase boundaries

We propose a novel micromagnetic standard problem calculating the coercive field for unpinning a domain wall at the interface of a multiphase magnet. This problem is sensitive to discontinuities in material parameters for the exchange interaction, the uniaxial anisotropy, and the spontaneous magnetization. We derive an explicit treatment of jump conditions at material interfaces for the exchange interaction in the finite-difference discretization. The micromagnetic simulation results are compared with analytical solutions and show good agreement. The proposed standard problem is well-suited to test the implementation of both finite-difference and finite-element simulation codes.

physics.comp-ph↗

arXiv2021

Machine learning methods for the prediction of micromagnetic magnetization dynamics

Machine learning (ML) entered the field of computational micromagnetics only recently. The main objective of these new approaches is the automatization of solutions of parameter-dependent problems in micromagnetism such as fast response curve estimation modeled by the Landau-Lifschitz-Gilbert (LLG) equation. Data-driven models for the solution of time- and parameter-dependent partial differential equations require high dimensional training data-structures. ML in this case is by no means a straight-forward trivial task, it needs algorithmic and mathematical innovation. Our work introduces theoretical and computational conceptions of certain kernel and neural network based dimensionality reduction approaches for efficient prediction of solutions via the notion of low-dimensional feature space integration. We introduce efficient treatment of kernel ridge regression and kernel principal component analysis via low-rank approximation. A second line follows neural network (NN) autoencoders as nonlinear data-dependent dimensional reduction for the training data with focus on accurate latent space variable description suitable for a feature space integration scheme. We verify and compare numerically by means of a NIST standard problem. The low-rank kernel method approach is fast and surprisingly accurate, while the NN scheme can even exceed this level of accuracy at the expense of significantly higher costs.

physics.comp-ph↗

arXiv2021

Magnetostatics and micromagnetics with physics informed neural networks

Partial differential equations and variational problems can be solved with physics informed neural networks (PINNs). The unknown field is approximated with neural networks. Minimizing the residuals of the static Maxwell equation at collocation points or the magnetostatic energy, the weights of the neural network are adjusted so that the neural network solution approximates the magnetic vector potential. This way, the magnetic flux density for a given magnetization distribution can be estimated. With the magnetization as an additional unknown, inverse magnetostatic problems can be solved. Augmenting the magnetostatic energy with additional energy terms, micromagnetic problems can be solved. We demonstrate the use of physics informed neural networks for solving magnetostatic problems, computing the magnetization for inverse problems, and calculating the demagnetization curves for two-dimensional geometries.

cond-mat.mtrl-sci↗

arXiv2021

Dipolar-stabilized first and second-order antiskyrmions in ferrimagnetic multilayers

Skyrmions and antiskyrmions are topologically protected spin structures with opposite topological charge. Particularly in coexisting phases, these two types of magnetic quasi-particles may show fascinating physics and potential for spintronic devices. While skyrmions are observed in a wide range of materials, until now antiskyrmions were exclusive to materials with D2d symmetry. In this work, we show first and second-order antiskyrmions stabilized by magnetic dipole-dipole interaction in Fe/Gd-based multilayers. We modify the magnetic properties of the multilayers by Ir insertion layers. Using Lorentz transmission electron microscopy imaging, we observe coexisting antiskyrmions, Bloch skyrmions, and type-2 bubbles and determine the range of material properties and magnetic fields where the different spin objects form and dissipate. We perform micromagnetic simulations to obtain more insight into the studied system and conclude that the reduction of saturation magnetization and uniaxial anisotropy leads to the existence of this zoo of different spin objects and that they are primarily stabilized by dipolar interaction.

cond-mat.mtrl-sci↗