Tunable, microscopic, and energy-efficient solutions for radio-frequency (RF) signal manipulation in the GHz regime are a key technology for efficient communication and sensing applications. Spin waves offer micrometer wavelengths at GHz frequencies, combined with strong magnetic-field tunability, making them inherently well-suited for tunable analog signal processing. Here, we demonstrate a novel concept: a micron-scale tunable RF phase shifter based on the wavelength shift of propagating spin waves. High energy efficiency is achieved by using the stray field of a micromagnet on a piezoelectrically actuated MEMS cantilever to locally induce this shift. The device shows a phase shift of more than 360° at a center frequency of 6.1 GHz using a phase-shifting area of less than 0.02mm^2. By changing the magnetic bias field, its functionality is experimentally confirmed over a range of center frequencies from 3 GHz to 8.2 GHz, and simulations show its applicability up to 14 GHz. A system-level characterization of an embedded device version demonstrates the qualification of magnonic phase shifters for highly integrated RF systems.

Microscopic radio-frequency (RF) devices based on propagating spin waves (SWs) are promising for compact, energy-efficient RF signal processing, but their implementation is impeded by fabrication complexity and the lack of efficient electrical readout. In this work, we demonstrate a SW-based Rowland circle spectrometer with electrical input and local electrical output transducers. The device is realized using a scalable fabrication process based on sputter deposition and wet-chemical etching of Yttrium-Iron-Garnet (YIG), forming concave grating structures with micrometer-scale features. The device functionality is confirmed by combined electrical and magneto-optical measurements, which show that the deflection of SW wavefronts at different input frequencies closely follows the analytically predicted behavior. The linear excitation of SWs via two input tones further confirms the spectrometer operation for simultaneously propagating waves. Beyond the single-device demonstration, we propose a concept for scalable architectures comprising multiple Rowland circles with tunable operating points. When combined with broadband parallel electrical readout, this approach enables control over bandwidth and spectral resolution, which are relevant to spectral occupancy detection in wireless communication systems.

The realization of fully reconfigurable, voltage-controlled, and programmable on-chip magnonic devices is essential to fully harness the potential of spin waves for signal processing, logic and neuromorphic computing. Yet, existing demonstrations of electrical tuning of magnonic responses are either volatile, current-driven and thus energy-inefficient, or rely on local strain modification limiting their scalability for wafer-scale integration. Here, we address this challenge using a BiFeO3/La0.67Sr0.33MnO3 multiferroic thin film heterostructure. We show that ferroelectric domain engineering in BiFeO3 enables deterministic tuning of the magnon dispersion of La0.67Sr0.33MnO3, producing frequency shifts up to ∼ 150 MHz and allowing reconfigurable waveguiding. Micro-focused Brillouin light scattering directly images these effects, revealing electrically defined magnonic waveguides and spatially programmable dispersion. Compared to conventional approaches, this method provides non-volatile and reversible control. Furthermore, using an inverse-design simulation code, we demonstrate the capability of our platform to perform advanced magnonic functions such as frequency demultiplexing. Our results open a new avenue for using magnetoelectric heterostructures for magnonic logic, with further applicability to reservoir and neuromorphic computing and AI driven magnonic devices.

Spin waves are promising information carriers for analog and wave-based computing, requiring compact and precisely engineered scattering landscapes. Focused ion beam (FIB) irradiation enables such control by locally modifying the spin-wave dispersion in yttrium iron garnet (YIG), yet the underlying crystallographic mechanisms remain unclear. Here, we present an experimentally validated framework that attributes FIB-induced spin-wave steering to magnetoelastic effects arising from irradiation-induced lattice dislocations. Following FIB irradiation and wet-chemical etching, local height profiles were obtained by atomic force microscopy (AFM) and used as fixed geometric constraints in fits of spin-wave dispersion relations measured by time-resolved magneto-optical Kerr effect (trMOKE) microscopy. The dispersion relation was extended by an explicit magnetoelastic field term, treated as a fit parameter. Its evolution reveals three successive deformation regimes, elastic, plastic, and partial amorphization, explaining the observed non-monotonic dependence of the spin-wave wavelength on ion dose. A three-phase deformation scenario based on SRIM simulations reproduces the extracted magnetoelastic field trends, validating the fitting approach. Micromagnetic simulations incorporating strain tensors derived from the experimental magnetoelastic field reproduce the characteristic non-monotonic wavelength behavior. These results establish a physical basis for FIB-engineered graded-index (GRIN) spin-wave landscapes and magnetoelastically programmable magnonic devices.

Magnonics is a promising platform for integrated radio-frequency (rf) devices, leveraging its inherent nonreciprocity and reconfigurability. However, the efficiency of spin-wave transducers driven by rf currents remains a major challenge. In this study, we systematically investigate a spin-wave transducer composed of micrometer-sized rf antennas on yttrium iron garnet films of different thickness—an ideal testbed for integrated magnonic devices. Using propagating spin-wave spectroscopy, we analyze spin-wave transmission, identifying key loss mechanisms and improving device efficiency by reducing ohmic resistance. The resulting improvements enable the reduction of insertion loss to below 10 dB in microscaled spin-wave transducers. At the same time large nonreciprocity can be exploited to achieve significant isolation on the microscale.

We investigate the effect of focused-ion-beam (FIB) irradiation on spin waves with sub-micron wavelengths in yttrium-iron-garnet films. Time-resolved scanning transmission x-ray microscopy was used to image the spin waves in irradiated regions and deduce corresponding changes in the magnetic parameters of the film. We find that the changes of Ga+irradiation can be understood by assuming a few percent change in the effective magnetizationMeffof the film due to a trade-off between changes in anisotropy and effective film thickness. Our results demonstrate that FIB irradiation can be used to locally alter the dispersion relation and the effective refractive indexneffof the film, even for submicron wavelengths. To achieve the same change innefffor shorter wavelengths, a higher dose is required, but no significant deterioration of spin wave propagation length in the irradiated regions was observed, even at the highest applied doses.

We present a computational framework for the design of magnonic transducers, where waveguide antennas generate and pick up spin-wave signals. Our method relies on the combination of circuit-level models with micromagnetic simulations and allows simulation of complex geometries in the magnonic domain. We validated our model with experimental measurements, which showed good agreement with the predicted scattering parameters of the system. Using our model, we identified scaling rules of the antenna radiation resistance and we show strategies to maximize transduction efficiency between the electric and magnetic domains. We designed a transducer pair on YIG with 5 dB insertion loss in a 100 MHz band, an unusually low value for micron-scale spin-wave devices. This demonstrates that magnonic devices can be very efficient and competitive in RF applications.

One of the most appealing features of magnonics is the easy tunability of spin-wave propagation via external magnetic fields. Typically, this requires bulky and power-hungry electromagnets, which are not compatible with device miniaturization. Here, we propose a different approach, exploiting the stray field from permanent micromagnets integrated on the same chip of a magnonic waveguide. In our monolithic device, we employ two SmCo square micromagnets (10 x 10 mu m2) flanking a CoFeB conduit at different distances from its axis, which produces a tunable transverse bias field between 7.5 and 3.0 mT in the conduit region between the magnets. This field is large enough to significantly affect the spin-wave propagation, when an external transverse bias field of 60 mT is applied to stabilize the Damon-Eshbach configuration. Spin waves excited by an antenna just outside the region between the magnets, indeed, enter a region with a variable higher (or lower) effective field depending on the parallel (or antiparallel) alignment between the external and micromagnets fields. Consequently, the attenuation length and phase shift of Damon-Eshbach spin waves can be tuned in a wide range by changing the parallel-antiparallel configuration of the external bias and the distance between SmCo micromagnets and the CoFeB conduit. This work demonstrates the potential of permanent micromagnets for the realization of low-power, integrated magnonic devices with tunable functionalities.

This work examines the impact of electromagnetic crosstalk in magnonic devices when using inductive spin-wave (SW) transducers. We present detailed electrical SW spectroscopy measurements showing the signal contributions to be considered in magnonic device design. We further provide a rule-of-thumb estimation for the crosstalk responsible for the secondary SW excitation at the output transducer. Simulations and calibrated electrical characterizations underpin this method. In addition, we visualize the secondary SW excitation via time-resolved magneto-optical Kerr effect (trMOKE) imaging in the forward-volume (FV) configuration in a 100 nm yttrium-iron-garnet (YIG) system.

We present the spatial separation of spin waves with distinct wavelengths when traveling through machine-learned magnetization landscapes, which can be used to demultiplex the corresponding excitation frequencies. Focused ion beam irradiation is used to modify the magnetization of YIG locally, and the maximum achievable magnetization change is used as a training basis to generate a binary 2D magnetization profile. The pattern is created with an inverse design approach using a micromagnetic solver embedded in the PyTorch framework. Subsequently, the magnetization pattern is experimentally realized using the corresponding FIB dose and its performance is demonstrated using time-resolved MOKE microscopy.

We demonstrate the application of machnine learning techniques to the design of magnonic neuromorphic devices. Specifically, we show that these techniques are applicable not only to inverse-design propagating waves but to engineer the modal dynamics of nanomagnets in such a way that these magnets solve basic classification tasks.

Direct focused-ion-beam writing is presented as an enabling technology for realizing functional spin-wave devices of high complexity, and demonstrate its potential by optically-inspired designs. It is shown that ion-beam irradiation changes the characteristics of yttrium iron garnet films on a submicron scale in a highly controlled way, allowing one to engineer the magnonic index of refraction adapted to desired applications. This technique does not physically remove material, and allows rapid fabrication of high-quality architectures of modified magnetization in magnonic media with minimal edge damage (compared to more common removal techniques such as etching or milling). By experimentally showing magnonic versions of a number of optical devices (lenses, gratings, Fourier-domain processors) this technology is envisioned as the gateway to building magnonic computing devices that rival their optical counterparts in their complexity and computational power.

We demonstrate direct focused ion beam (FIB) writing as an enabling technology for realizing spin-wave-optics devices. It is shown that ion-beam irradiation changes the characteristics of YIG films on a submicron scale in a highly controlled way, allowing to engineer the magnonic index of refraction adapted to desired applications. This technique does not physically remove material, and allows rapid fabrication of high-quality architectures of modified magnetization in magnonic media with minimal edge damage (compared to more common techniques such as etching or milling). By experimentally showing magnonic versions of a number of optical devices (lenses, gratings, Fourier-domain processors) we envision this technology as the gateway to building magnonic computing devices that rival their optical counterparts in their complexity and computational power.

We present the design and experimental realization of a device that acts like a spin-wave lens i.e., it focuses spin waves to a specified location. The structure of the lens does not resemble any conventional lens design, it is a nonintuitive pattern produced by a machine learning algorithm. As a spin-wave design tool, we used our custom micromagnetic solver "SpinTorch" that has built-in automatic gradient calculation and can perform backpropagation through time for spin-wave propagation. The training itself is performed with the saturation magnetization of a YIG film as a variable parameter, with the goal to guide spin waves to a predefined location. We verified the operation of the device in the widely used mumax3 micromagnetic solver, and by experimental realization. For the experimental implementation, we developed a technique to create effective saturation-magnetization landscapes in YIG by direct focused-ion-beam irradiation. This allows us to rapidly transfer the nanoscale design patterns to the YIG medium, without patterning the material by etching. We measured the effective saturation magnetization corresponding to the FIB dose levels in advance and used this mapping to translate the designed scatterer to the required dose levels. Our demonstration serves as a proof of concept for a workflow that can be used to realize more sophisticated spin-wave devices with complex functionality, e.g., spin-wave signal processors, or neuromorphic devices.

Magnonics addresses the physical properties of spin waves and utilizes them for data processing. Scalability down to atomic dimensions, operation in the GHz-to-THz frequency range, utilization of nonlinear and nonreciprocal phenomena, and compatibility with CMOS are just a few of many advantages offered by magnons. Although magnonics is still primarily positioned in the academic domain, the scientific and technological challenges of the field are being extensively investigated, and many proof-of-concept prototypes have already been realized in laboratories. This roadmap is a product of the collective work of many authors, which covers versatile spin-wave computing approaches, conceptual building blocks, and underlying physical phenomena. In particular, the roadmap discusses the computation operations with the Boolean digital data, unconventional approaches, such as neuromorphic computing, and the progress toward magnon-based quantum computing. This article is organized as a collection of sub-sections grouped into seven large thematic sections. Each sub-section is prepared by one or a group of authors and concludes with a brief description of current challenges and the outlook of further development for each research direction.

We experimentally demonstrate the operation of a Rowland-type concave grating for spin waves, with potential application as a microwave spectrometer. In this device geometry, spin waves are coherently excited on a diffraction grating and form an interference pattern that focuses spin waves to a point corresponding to their frequency. The diffraction grating was created by focused-ion-beam irradiation, which was found to locally eliminate the ferrimagnetic properties of YIG, without removing the material. We found that in our experiments spin waves were created by an indirect excitation mechanism, by exploiting nonlinear resonance between the grating and the coplanar waveguide. Although our demonstration does not include separation of multiple frequency components, since this is not possible if the nonlinear excitation mechanism is used, we believe that using linear excitation the same device geometry could be used as a spectrometer. Our work paves the way for complex spin-wave optic devices-chips that replicate the functionality of integrated optical devices on a chip-scale.

We experimentally demonstrate the operation of a spin-wave Rowland spectrometer. In the proposed device geometry, spin waves are coherently excited on a diffraction grating and form an interference pattern that spatially separates spectral components of the incoming signal. The diffraction grating was created by focused-ion-beam irradiation, which was found to locally eliminate the ferrimagnetic properties of YIG, without removing the material. We found that in our experiments spin waves were created by an indirect mechanism, by exploiting nonlinear resonance between the grating and the coplanar waveguide. Our work paves the way for complex spin-wave optic devices – chips that replicate the functionality of integrated optical devices on a chip-scale.

We demonstrate the design of a neural network hardware, where all neuromorphic computing functions, including signal routing and nonlinear activation are performed by spin-wave propagation and interference. Weights and interconnections of the network are realized by a magnetic-field pattern that is applied on the spin-wave propagating substrate and scatters the spin waves. The interference of the scattered waves creates a mapping between the wave sources and detectors. Training the neural network is equivalent to finding the field pattern that realizes the desired input-output mapping. A custom-built micromagnetic solver, based on the Pytorch machine learning framework, is used to inverse-design the scatterer. We show that the behavior of spin waves transitions from linear to nonlinear interference at high intensities and that its computational power greatly increases in the nonlinear regime. We envision small-scale, compact and low-power neural networks that perform their entire function in the spin-wave domain.

We study the computational potential of a spin-wave (SW) substrate by applying two metrics known from reservoir computing. At low intensities, SW scatterers can perform linear operations, while at higher intensities, nonlinear phenomena dominate, possibly enabling high-function, general-purpose computing. The transition between the linear and nonlinear regimes can be quantified by the intensity-dependent kernel rank (KR) and generalization rank (GR). The KR and GR metrics prove that the SW substrate displays the nonlinearities required for computing and give recipes for device designs that utilize nonlinearity.

A new class of device has been proposed that converts millimeter electrical signals into spin waves with micrometer wavelengths, with which computing can be done in a small footprint. The spin waves are then converted back into electrical signals. Essential for this is the design of proper transducers between the two domains. We have simulated an electrical-to-spin-wave transducer that shows improved bandwidth. We are developing a numerical simulation design tool that crosses between these domains.