Pith. sign in

REVIEW 3 major objections 6 minor 1 cited by

Micromagnetic Simulation and Optimization of Spin-Wave Transducers

T0 review · 3 major / 6 minor · reviewed 2026-08-10 · deepseek-v4-flash

Challenge this review Re-run · record.json Download PDF Read on arXiv ↗

Pith's one-line read The paper claims that spin-wave resistance can be computed directly from micromagnetic simulation, replacing analytical formulas for arbitrary transducer geometries.

desk verdict Useful integration of spin-wave resistance into micromagnetics, but absent external validation leaves the generalized claim unproven and the abstract's 0.75 efficiency does not appear in the body. read the letter →

arxiv 2501.16553 v1 pith:KJI3A4YL submitted 2025-01-27 physics.comp-ph

Florian Bruckner , Kristýna Davídková , Claas Abert , Andrii Chumak , Dieter Suess This is my paper · ORCID
classification physics.comp-ph
keywords spin-waveresistancemagnonictransducermicromagneticsimulationefficiencyYIGwaveguidelumped-elementmodelmagnetostaticsurfacewavesinversedesign
verification ladder T0 review T1 audit T2 compute T3 formal

The pith

A machine-rendered reading of the paper's core claim, the machinery that carries it, and where it could break.

The reading

This paper introduces a way to compute the spin-wave resistance of a magnonic transducer directly from time-domain micromagnetic simulation, rather than from analytical formulas that are tied to specific geometries. The central identity is $R_{\mathrm{sw}} = 2P_{\mathrm{sw}}/|\hat I_1|^2$, where $P_{\mathrm{sw}}$ is the time-averaged power flowing into the spin wave, obtained from the time derivative of the micromagnetic energy or from the induced flux linkage. A sympathetic reader would care because the method accepts arbitrary transducer and waveguide shapes inside one simulation framework, and because the reported single-parameter sweeps identify design rules that push the spin-wave efficiency up to 0.75. These rules matter for nanoscale 5G magnonic hardware, where current transducers suffer large insertion losses.

What carries the argument

The key quantity is the lumped-circuit picture of the magnonic system, in which the transducer efficiency factorizes as $\eta_T = \eta_{\mathrm{sw}}\eta_m$, with the spin-wave efficiency $\eta_{\mathrm{sw}}=R_{\mathrm{sw}}/(R_{\mathrm{sw}}+R_\Omega)$ and the impedance-matching efficiency $\eta_m=1-|\Gamma|^2$. The new load-bearing identity is $R_{\mathrm{sw}}=2P_{\mathrm{sw}}/|\hat I_1|^2$, with the spin-wave power $P_{\mathrm{sw}}$ obtained from the time average of $\partial E/\partial t$ or from the voltage induced by the flux linkage $\psi_m$. This identity turns a field-level simulation output into a circuit parameter, and it is what allows transducer optimization to run entirely inside a single micromagnetic solver. The solver integrates the magnetization dynamics under the Oersted field of a homogeneous impressed current density, an assumption that limits the operating range to conductors smaller than the skin depth.

What would settle it

Measure the input reflection or transmitted spin-wave power of a fabricated U-shaped transducer as a function of conductor height at 4 GHz and compare the extracted $R_{\mathrm{sw}}$ with the simulated curve: agreement below the 1 µm skin depth and systematic deviation above it would confirm that the homogeneous-current assumption, not the power-extraction identity, is the limiting approximation. A cheaper computational check is to recalculate the same geometries with a full-wave electromagnetic field solver and compare the resulting current distribution and resistance.

Watch

Extended reading notes

Core claim

On the paper's own terms, the central discovery is that the real part of the spin-wave impedance can be read out of an ordinary micromagnetic simulation. The transducer is described by a lumped circuit, so for a sinusoidal impressed current with peak value $\hat I_1$ the time-averaged spin-wave power is $P_{\mathrm{sw}} = \frac{1}{2} R_{\mathrm{sw}} \hat I_1^2$, and therefore $R_{\mathrm{sw}} = 2P_{\mathrm{sw}}/|\hat I_1|^2$. The paper evaluates $P_{\mathrm{sw}}$ in two equivalent ways: from the numerical time derivative of the micromagnetic energy, $p_{\mathrm{sw}}(t)=\partial E/\partial t$, and from the induced voltage obtained through the flux linkage $\psi_m = \mu_0 \int M_s \mathbf{m}\cdot \hat{\mathbf{h}}_{\mathrm{oe}}\, dV$. Because the Oersted field of the impressed current density is computed inside the finite-difference solver, no geometry-specific analytical expression is needed. Using a U-shaped transducer above a YIG waveguide in the magnetostatic surface-wave configuration, the paper shows that widening the conductors, increasing their center-to-center distance, and thickening the waveguide all raise efficiency, with an optimum transducer height near 500 nm; the abstract reports single-parameter spin-wave efficiencies up to 0.75.

Load-bearing premise

The load-bearing assumption is that the current density inside the antenna conductor is uniform across its cross-section, with skin and proximity effects ignored; the paper states this holds only when the conductor is thinner than the skin depth (about 1 µm for copper at 4 GHz), yet the height sweep reaches 2 µm.

Editorial extensions

If this is right

  • Transducer design becomes a simulation loop: for any conductor layout, one simulation at the operating frequency yields $R_{\mathrm{sw}}$ and hence the efficiency, so gradient-based or inverse-design optimization can be applied directly.
  • The two independent routes to $P_{\mathrm{sw}}$—energy derivative and flux linkage—agree in the reported sweeps, providing an internal consistency check for the computed resistance.
  • The design trends identified with the U-shaped transducer are expected to carry over to coplanar-waveguide transducers, because the U-shape was chosen to avoid unequal branch currents while exhibiting the same excitation physics.
  • The same formalism can extract all four impedance parameters $Z_{11}, Z_{12}, Z_{21}, Z_{22}$ of the two-port magnonic system, extending the method from a single transducer to complete filter circuits.

Reading between the lines

Editorial extensions of the paper, not claims the author makes directly.

  • Because the solver assumes a homogeneous current density and ignores skin and proximity effects, the height sweep beyond about 1 µm—the copper skin depth at 4 GHz—probably overstates $R_{\mathrm{sw}}$; a full-wave current-distribution model would show whether the reported optimum near 500 nm shifts.
  • The energy-derivative route measures the total energy added to the simulation volume; in a damped magnet or with absorbing boundary conditions, that energy includes dissipation or escaping flux, so the method as demonstrated with zero damping would need a correction to isolate the spin-wave power.
  • At the 26 GHz 5G high band the skin depth shrinks below the 1 µm scale, so applying these design rules at that frequency requires either narrower conductors or a current-redistribution model, not just the same geometry scaled down.
Share X Bluesky LinkedIn Reddit HN

Editorial analysis

A structured set of objections, weighed in public.

Desk editor's note, referee report, and a circularity audit.

Referee Report

3 major / 6 minor

Summary. The paper introduces a micromagnetic simulation method for computing the spin-wave resistance Rsw of magnonic transducers. The method evaluates the time-averaged spin-wave power Psw either from the numerical time derivative of the micromagnetic energy (Eq. 6) or from the induced voltage and flux linkage (Eq. 7), and then obtains Rsw = 2 Psw / |I1|^2 (Eq. 5). The approach is implemented in the author's magnum.np framework and demonstrated on a U-shaped copper transducer above a YIG waveguide in the Damon-Eshbach configuration. Parameter sweeps over transducer height, width, center-to-center distance, and YIG thickness are presented, with the spin-wave efficiency ηsw shown in the figures reaching approximately 0.6 at the largest distance (Fig. 5). The abstract, however, claims efficiencies up to 0.75.

Significance. If validated, this method would replace analytical transducer models with a simulation-driven framework applicable to arbitrary geometries, providing a practical tool for optimizing magnonic transducers for 5G and other RF applications. The agreement between the two independent estimators (power and flux linkage) across all sweeps is a strong positive signal for implementation quality and numerical consistency. The paper also benefits from being implemented in a single, publicly used simulation framework, which improves reproducibility. However, the lack of any external validation against analytical theory or experimental data leaves the absolute accuracy of the computed Rsw unestablished, and the abstract overstates the achieved efficiency relative to the displayed results.

major comments (3)
  1. [Section 2, Eq. (5)] The central claim that Eq. (5) yields reliable spin-wave resistance for arbitrary geometries is not validated against any external benchmark. The internal agreement of the two estimators rules out many implementation bugs but not common-mode errors in the Oersted-field model, the quasistatic assumptions, or the finite-domain treatment. I recommend adding a comparison with an analytical solution, such as the Ganguly-Webb microstrip formula for a simple planar geometry, or with experimental data from a known device, to establish the absolute accuracy of the method.
  2. [Section 3.1, Fig. 3] The height sweep extends to h = 2 µm, while the paper itself states that the homogeneous-current-density assumption is valid only when the conductor cross-section is smaller than the skin depth, about 1 µm in copper at 4 GHz. The reported Rsw and ηsw values for h > 1 µm are therefore computed with an unphysical uniform current distribution. The qualitative optimum near 500 nm falls within the valid range, but the quantitative results and the discussion of the height trade-off must be restricted to h ≤ δ or supported by a non-uniform current model.
  3. [Abstract and Section 3] The abstract states that the spin-wave efficiency 'can reach values up to 0.75,' but none of the figures support this: the maximum ηsw seen in the single-parameter sweeps is approximately 0.6 in Fig. 5 for the largest center-to-center distance. This discrepancy is a clear overstatement that must be corrected, either by revising the abstract to match the presented results or by adding the specific configuration that yields 0.75 and explaining how it is obtained.
minor comments (6)
  1. [Section 2, Eq. (5)] The notation for the peak current is inconsistent: Eq. (1) uses \(\hat{I}_1\), while Eq. (5) uses \(|I_1|\). Please unify the notation.
  2. [Table 1] The mesh discretization line 'dx 25 nm × 100 µm × 10 nm' and the mesh elements '2800 × 1 × 45' imply a simulation length of 70 µm along x, which is inconsistent with the stated transducer length L0 = 100 µm if L0 is oriented along x. Please specify the coordinate axes and the cell sizes explicitly to resolve this ambiguity.
  3. [Section 3.1 and figure captions] The captions for Figs. 3 and 4 contain typos: 'tranducer' should be 'transducer' and 'RSW' should be 'Rsw'.
  4. [Section 4, Conclusion] The phrase 'SA W-based technology' should be 'SAW-based technology'.
  5. [Section 2, Eq. (6)] It would aid the reader to state explicitly that h_lin includes the exchange, anisotropy, and demagnetizing fields, and that the Oersted field is deliberately excluded from the energy expression E, since its contribution is accounted for separately in the power balance.
  6. [Section 3.4] The text says the spin-wave resistance 'stagnates for waveguides much thicker than the chosen wavelength,' but Fig. 6 shows a monotonic increase up to t = 2 µm. Please clarify whether 'stagnates' refers to the asymptotic behavior beyond the plotted range or revise the wording to match the figure.

Circularity Check

0 steps flagged · score 0.0 of 10

No significant circularity: the spin-wave resistance is computed from LLG dynamics and energy balance, not fitted or defined into existence.

full rationale

The paper's central step is Eq. (5), Rsw = 2 Psw / |I1|^2, which is the circuit-theory definition rearranged; the actual computation is the numerical evaluation of Psw from time-domain LLG dynamics (Eq. 3) driven by a Biot-Savart Oersted field (Eq. 4). Psw is obtained from two independent estimators, the energy time-derivative (Eq. 6) and the induced-voltage/flux-linkage expression (Eq. 7); neither estimator is tuned to match the reported Rsw values, and their agreement is an implementation check rather than a fitted coincidence. The bias field is a physical operating parameter scanned to satisfy the wavelength-matching condition, not a fitted constant that forces the spin-wave resistance. The cited magnum.np [28] is a software dependency for solving the LLG equation; the method's equations are stated self-containedly, so no load-bearing result is imported solely from a self-citation. The paper's own admission that the homogeneous-current-density assumption is valid only below the skin depth (~1 µm) while the height sweep extends to 2 µm is a validity limitation for those quantitative values, but it is not a circularity of the derivation.

Assumptions & free parameters 1 free parameters · 4 assumptions · 0 invented entities

The core method is a direct LLG computation with no fitted constants. The main tuning knob is the per-geometry bias field used to maximize Rsw. The modeling assumptions, zero damping, homogeneous current density, the energy-derivative identification, and the U-shaped approximation, are the load-bearing choices that determine the reported numbers. No new physical entities are introduced.

free parameters (1)
  • Optimal bias field μ0H_bias per geometry = not reported, chosen so λsw ≈ 2d and Rsw is maximal
    Every efficiency point in the sweeps is evaluated at a bias field tuned to that geometry. This is a physical, experimentally settable parameter, not a fitted theory constant, but it is a per-design tuning knob that the reported maxima depend on.
assumptions (4)
  • domain assumption LLG dynamics with zero Gilbert damping (α = 0)
    Table 1 sets damping to zero. The method therefore computes radiated spin-wave power, not total dissipated power; real YIG damping would reduce delivered efficiency. This enters in Section 2 and the simulation setup.
  • domain assumption Homogeneous current density across the antenna cross-section
    Stated in Section 2 as valid only when the conductor cross-section is smaller than the skin depth. The height sweep in Section 3.1 exceeds this limit for h > 1 micrometer.
  • standard math Time derivative of micromagnetic energy equals radiated spin-wave power
    Equation 6 follows from lossless LLG dynamics with a static bias field and a sinusoidal Oersted field, averaged over periods. This is the mathematical bridge from simulation output to Rsw.
  • domain assumption U-shaped transducer with neglected overhang represents the relevant CPW behavior
    Section 3 states the U-shape avoids unequal branch currents of a CPW and that parts extending beyond the waveguide are neglected. This simplification is not quantitatively justified.

how reviews work

0 comments
Cite this review

Pith. "Pith review of Micromagnetic Simulation and Optimization of Spin-Wave Transducers." pith.science (2026). https://pith.science/paper/KJI3A4YL

@misc{pith2026250116553,
  author       = {Pith},
  title        = {Pith review of: Micromagnetic Simulation and Optimization of Spin-Wave Transducers},
  year         = {2026},
  howpublished = {\url{https://pith.science/paper/KJI3A4YL}},
  note         = {Machine review of arXiv:2501.16553}
}
read the original abstract

The increasing demand for higher data volume and faster transmission in modern wireless telecommunication systems has elevated requirements for 5G high-band RF hardware. Spin-Wave technology offers a promising solution, but its adoption is hindered by significant insertion loss stemming from the low efficiency of magnonic transducers. This work introduces a micromagnetic simulation method for directly computing the spin-wave resistance, the real part of spin-wave impedance, which is crucial for optimizing magnonic transducers. By integrating into finite-difference micromagnetic simulations, this approach extends analytical models to arbitrary transducer geometries. We demonstrate its effectiveness through parameter studies on transducer design and waveguide properties, identifying key strategies to enhance the overall transducer efficiency. Our studies show that by varying single parameters of the transducer geometry or the YIG thickness, the spin-wave efficiency, the parameter describing the efficiency of the transfer of electromagnetic energy to the spin wave, can reach values up to 0.75. The developed numerical model allows further fine-tuning of the transducers to achieve even higher efficiencies.

Figures

Figures reproduced from arXiv: 2501.16553 by the authors.

Figure 1
Figure 1. Equivalent circuit representation of a magnonic filter consisting of [PITH_FULL_IMAGE:figures/full_fig_p003_1.png] view at source ↗
Figure 2
Figure 2. Setup of one U-shaped transducer (brown) consisting of two con [PITH_FULL_IMAGE:figures/full_fig_p006_2.png] view at source ↗
Figure 3
Figure 3. Simulation of the spin-wave resistance Rsw and spin-wave efficiency ηsw for varying tranducer height h. The dashed line indicates the ohmic resistance Eqn. (8). The dotted line indicates the relative decay of the maximum Oersted field inside of the YIG waveguide. the dimensions of the YIG waveguide and also the selected wavelength re￾main unchanged, the optimal bias field only needs to be determined once. The spin-w… view at source ↗
Figures from the paper (3 more)
Figure 4
Figure 4. Figure 4: Simulation of the spin-wave resistance Rsw and spin-wave efficiency ηsw for varying tranducer width w. The dashed line indicates the ohmic resistance Eqn. (8). The dotted line shows the maximum amplitude of the spatial Fourier transform. gap g = d − w = 100 nm have bee…
Figure 5
Figure 5. Figure 5: Simulation of the spin-wave resistance Rsw and spin-wave efficiency ηsw for varying Center-to-Center distance d and constant gap g = 100 nm between the two transducer lines. The optimal bias h bias has been deter￾mined for each distance d. The dashed line indicates the…
Figure 6
Figure 6. Figure 6: Simulation of the spin-wave resistance Rsw and spin-wave effi￾ciency ηsw for varying waveguide thickness t. The optimal bias h bias has been determined for each thickness t. The dashed line indicates the ohmic resistance Eqn. (8). and material properties impose limits.…

Discussion (0). Continue with ORCID to comment.

Forward citations

Cited by 1 Pith paper

Reviewed papers in the Pith corpus that reference this work. Sorted by Pith novelty score. Full citation record

  1. Influence of photon-magnon coupling to enhance spin-wave excitation

    cond-mat.mes-hall 2025-06 conditional novelty 6.0 of 10

    A simulated inverse split-ring resonator antenna coupled to a thin permalloy film excites spin waves up to about 4.5 times more intensely than a conventional microstrip line in the weak photon-magnon coupling regime.

Reference graph

Works this paper leans on

30 extracted references · 28 canonical work pages · cited by 1 Pith paper

  1. [27]

    Design rules for low-insertion-loss magnonic transducers

    R. Erd´ elyi, G. Csaba, L. Maucha, F. Kohl, J. Greil, M. Becherer, P. Pirro, and ´A. Papp, “Design rules for low-insertion-loss magnonic transducers,” arXiv preprint arXiv:2410.14370 , 2024

    work page Pith review arXiv 2024

  2. [1]

    The 2021 magnonics roadmap,

    A. Barman, G. Gubbiotti, S. Ladak, A. O. Adeyeye, M. Krawczyk, J. Gr¨ afe, C. Adelmann, S. Cotofana, A. Naeemi, V. I. Vasyuchka,et al., 11 “The 2021 magnonics roadmap,” Journal of Physics: Condensed Mat- ter, vol. 33, no. 41, p. 413001, 2021

    work page 2021

  3. [2]

    Advances in magnetics roadmap on spin-wave computing,

    A. V. Chumak, P. Kabos, M. Wu, C. Abert, C. Adelmann, A. Adeyeye, J. ˚Akerman, F. G. Aliev, A. Anane, A. Awad, et al. , “Advances in magnetics roadmap on spin-wave computing,” IEEE Transactions on Magnetics, vol. 58, no. 6, pp. 1–72, 2022

    work page 2022

  4. [3]

    Introduction to spin wave com- puting,

    A. Mahmoud, F. Ciubotaru, F. Vanderveken, A. V. Chumak, S. Ham- dioui, C. Adelmann, and S. Cotofana, “Introduction to spin wave com- puting,” Journal of Applied Physics , vol. 128, no. 16, 2020

    work page 2020

  5. [4]

    Three-dimensional nanomagnetism,

    A. Fern´ andez-Pacheco, R. Streubel, O. Fruchart, R. Hertel, P. Fischer, and R. P. Cowburn, “Three-dimensional nanomagnetism,”Nature com- munications, vol. 8, no. 1, pp. 1–14, 2017

    work page 2017

  6. [5]

    Spin-wave logical gates,

    M. Kostylev, A. Serga, T. Schneider, B. Leven, and B. Hillebrands, “Spin-wave logical gates,” Applied Physics Letters, vol. 87, no. 15, 2005

    work page 2005

  7. [6]

    Nanoscale neural network us- ing non-linear spin-wave interference,

    ´A. Papp, W. Porod, and G. Csaba, “Nanoscale neural network us- ing non-linear spin-wave interference,” Nature communications, vol. 12, no. 1, p. 6422, 2021

    work page 2021

  8. [7]

    Offset- free magnetic field sensor based on a standing spin wave,

    M. Gattringer, C. Abert, Q. Wang, A. Chumak, and D. Suess, “Offset- free magnetic field sensor based on a standing spin wave,” Physical Review Applied, vol. 20, no. 4, p. 044083, 2023

    work page 2023

Show all 30 references
  1. [8]

    Hybrid quantum systems based on magnonics,

    D. Lachance-Quirion, Y. Tabuchi, A. Gloppe, K. Usami, and Y. Naka- mura, “Hybrid quantum systems based on magnonics,” Applied Physics Express, vol. 12, no. 7, p. 070101, 2019

    2019

  2. [9]

    Opportunities and challenges for spintronics in the microelec- tronics industry,

    B. Dieny, I. L. Prejbeanu, K. Garello, P. Gambardella, P. Freitas, R. Lehndorff, W. Raberg, U. Ebels, S. O. Demokritov, J. Akerman, et al. , “Opportunities and challenges for spintronics in the microelec- tronics industry,” Nature Electronics, vol. 3, no. 8, pp. 446–459, 2020

    2020

  3. [10]

    Re- view on spin-wave rf applications,

    K. O. Levchenko, K. Dav ´ ıdkov´ a, J. Mikkelsen, and A. V. Chumak, “Re- view on spin-wave rf applications,” arXiv preprint arXiv:2411.19212 , 2024

    2024 arXiv

  4. [11]

    Nanoscaled spin-wave frequency selective limiter (fsl) for 5g technology,

    K. Dav ´ ıdkov´ a, K. Levchenko, F. Bruckner, R. Verba, F. Majcen, Q. Wang, C. Dubs, V. Vlaminck, J. Kl ´ ıma, M. Urb´ anek, D. Suess, and A. Chumak, “Nanoscaled spin-wave frequency selective limiter (fsl) for 5g technology,” Zenodo, doi: 10.5281/zenodo.14644054 , 2025

    doi

  5. [12]

    Next generation 5g wireless net- works: A comprehensive survey,

    M. Agiwal, A. Roy, and N. Saxena, “Next generation 5g wireless net- works: A comprehensive survey,” IEEE communications surveys & tu- torials, vol. 18, no. 3, pp. 1617–1655, 2016. 12

    2016

  6. [13]

    Low damping and microstruc- tural perfection of sub-40nm-thin yttrium iron garnet films grown by liquid phase epitaxy,

    C. Dubs, O. Surzhenko, R. Thomas, J. Osten, T. Schneider, K. Lenz, J. Grenzer, R. H¨ ubner, and E. Wendler, “Low damping and microstruc- tural perfection of sub-40nm-thin yttrium iron garnet films grown by liquid phase epitaxy,” Physical Review Materials , vol. 4, no. 2, p. 02...

    2020

  7. [14]

    Microstrip excitation of magneto- static surface waves: Theory and experiment,

    A. K. Ganguly and D. C. Webb, “Microstrip excitation of magneto- static surface waves: Theory and experiment,” IEEE Transactions on Microwave Theory and Techniques, vol. 23, no. 12, pp. 998–1006, 1975

    1975

  8. [15]

    Excitation of magnetostatic backward volume waves,

    J. Parekh and H. Tuan, “Excitation of magnetostatic backward volume waves,” IEEE Transactions on Magnetics, vol. 16, no. 5, pp. 1165–1167, 1980

    1980

  9. [16]

    Theory for magnetostatic forward volume wave excitation,

    J. Parekh, “Theory for magnetostatic forward volume wave excitation,” Journal of Applied Physics , vol. 50, no. B3, pp. 2452–2454, 1979

    1979

  10. [17]

    Lumped circuit model for inductive antenna spin- wave transducers,

    F. Vanderveken, V. Tyberkevych, G. Talmelli, B. Sor´ ee, F. Ciubotaru, and C. Adelmann, “Lumped circuit model for inductive antenna spin- wave transducers,” Scientific Reports, vol. 12, no. 1, p. 3796, 2022

    2022

  11. [18]

    Efficient electromagnetic transducers for spin-wave devices,

    D. A. Connelly, G. Csaba, H. R. O. Aquino, G. H. Bernstein, A. Orlov, W. Porod, and J. Chisum, “Efficient electromagnetic transducers for spin-wave devices,” Scientific Reports, vol. 11, no. 1, p. 18378, 2021

    2021

  12. [19]

    Micromagnetic modelling-the current state of the art,

    J. Fidler and T. Schrefl, “Micromagnetic modelling-the current state of the art,” Journal of Physics D: Applied Physics, vol. 33, no. 15, p. R135, 2000

    2000

  13. [20]

    Micromagnetics and spintronics: models and numerical methods,

    C. Abert, “Micromagnetics and spintronics: models and numerical methods,” The European Physical Journal B , vol. 92, pp. 1–45, 2019

    2019

  14. [21]

    Topologically protected vor- tex structures for low-noise magnetic sensors with high linear range,

    D. Suess, A. Bachleitner-Hofmann, A. Satz, H. Weitensfelder, C. Vogler, F. Bruckner, C. Abert, K. Pr¨ ugl, J. Zimmer, C. Huber, S. Luber, W. Raberg, T. Schrefl, and H. Br¨ uckl, “Topologically protected vor- tex structures for low-noise magnetic sensors with high linear range,...

    2018

  15. [22]

    Nanoscale magnonic networks,

    Q. Wang, G. Csaba, R. Verba, A. V. Chumak, and P. Pirro, “Nanoscale magnonic networks,” Physical Review Applied, vol. 21, no. 4, p. 040503, 2024

    2024

  16. [23]

    Inverse-design magnonic devices,

    Q. Wang, A. Chumak, and P. Pirro, “Inverse-design magnonic devices,” Nature Communications, vol. 12, no. 1, 2021

    2021

  17. [24]

    Spin-wave optics in yig realized by ion-beam irradiation,

    M. Kiechle, A. Papp, S. Mendisch, V. Ahrens, M. Golibrzuch, G. H. Bernstein, W. Porod, G. Csaba, and M. Becherer, “Spin-wave optics in yig realized by ion-beam irradiation,” Small, vol. 19, no. 21, p. 2207293, 2023. 13

    2023

  18. [25]

    Magnonic inverse- design processor,

    N. Zenbaa, C. Abert, F. Majcen, M. Kerber, R. Serha, S. Knauer, Q. Wang, T. Schrefl, D. Suess, and A. Chumak, “Magnonic inverse- design processor,” arXiv preprint arXiv:2403.17724 , 2024

    2024 arXiv

  19. [26]

    A magnonic directional coupler for integrated magnonic half- adders,

    Q. Wang, M. Kewenig, M. Schneider, R. Verba, F. Kohl, B. Heinz, M. Geilen, M. Mohseni, B. L¨ agel, F. Ciubotaru, C. Adelmann, C. Dubs, S. D. Cotofana, O. V. Dobrovolskiy, T. Br¨ acher, P. Pirro, and A. V. Chumak, “A magnonic directional coupler for integrated magnonic half- ad...

    2020

  20. [28]

    magnum.np: a pytorch based gpu enhanced finite difference micromagnetic simulation framework for high level development and inverse design,

    F. Bruckner, S. Koraltan, C. Abert, and D. Suess, “magnum.np: a pytorch based gpu enhanced finite difference micromagnetic simulation framework for high level development and inverse design,” Scientific Reports, vol. 13, no. 1, p. 12054, 2023

    2023

  21. [29]

    Spin pumping and magnetization dynamics in metallic multilayers,

    Y. Tserkovnyak, A. Brataas, and G. E. Bauer, “Spin pumping and magnetization dynamics in metallic multilayers,” Physical Review B , vol. 66, no. 22, p. 224403, 2002

    2002

  22. [30]

    Magnetostatic modes of a ferromagnetic slab,

    R. Damon and J. Eshbach, “Magnetostatic modes of a ferromagnetic slab,” Journal of Applied Physics , vol. 31, no. 5, pp. S104–S105, 1960. 14

    1960

Pith tools

Reviewed August 10, 2026 · model on record in the stance chip above.