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Shangyuan Wang

Publications and source records attributed to Shangyuan Wang.

3 recordsLinked to original sources

Visualizing modified spin-wave wavefronts near magnetic defects and domains using nitrogen-vacancy centers

Direct, real-space imaging of spin-wave propagation and wavefronts in magnetic materials is crucial for advancing both fundamental understanding of spin dynamics and the development of functional devices. This, however, remains a significant challenge, especially in materials with complex magnetic characteristics at the nanoscale. Here, we employ scanning nitrogen-vacancy center spectroscopy to achieve visualization of spin waves in two archetypical magnetic films: yttrium-iron-garnet and lanthanum strontium manganese oxide. We reveal a wavelength-dependent spin-wave filtering effect near point-like magnetic scatterers and a modified spin wavefront in antiferromagnetically coupled stripe domains. The spin-wave characteristics are explained using micromagnetic simulations and analytical calculations. These findings point to possible fine control of spin-wave propagation near complex magnetic structures and extend the scope of spin-wave imaging based on nitrogen-vacancy centers beyond uniform magnets.

cond-mat.mes-hall

Disambiguating electrical detection of magnetization dynamics in magnetic insulators

Electrical detection of magnetization dynamics in magnetic insulators underpins both fundamental studies of magnon transport and the development of low-loss magnonic devices. In heavy-metal/magnetic-insulator heterostructures, spin pumping and spin-torque ferromagnetic resonance (ST-FMR) are widely used for this purpose and are often treated separately in different measurement geometries. In practice, the competition between these two effects gives rise to electrical voltage signals of opposite signs, which can lead to ambiguous interpretations of the underlying physics. Here, we show how to disambiguate their respective contributions and provide a framework for interpreting experiments involving microwave excitation of magnetic insulators and detection of magnetization dynamics via spin-charge conversion in heavy metals. We systematically investigate spin pumping and ST-FMR in nonlocal and local devices using Pt-capped thin films of thulium and bismuth-yttrium iron garnets. We show how spin-wave character, magnetic dissipation, magnetic field orientation and device geometry govern the sign and magnitude of the resulting signals. In several cases, the voltage generated by microwave excitation changes sign between an out-of-plane or in-plane magnetic configuration. We disentangle a contribution due to spin pumping, induced by exponentially decaying propagating spin waves, and a weakly distance-dependent contribution from ST-FMR, remotely induced by inductive coupling. We show that both the spin wave excitation profile across the film thickness and magnetic damping largely determine which of the two contributions dominates. Hence, the sign of the electrical signal cannot be uniquely assigned to the chirality of the magnon modes.

cond-mat.mes-hall

An optical biomimetic eyes with interested object imaging

We presented an optical system to perform imaging interested objects in complex scenes, like the creature easy see the interested prey in the hunt for complex environments. It utilized Deep-learning network to learn the interested objects's vision features and designed the corresponding "imaging matrices", furthermore the learned matrixes act as the measurement matrix to complete compressive imaging with a single-pixel camera, finally we can using the compressed image data to only image the interested objects without the rest objects and backgrounds of the scenes with the previous Deep-learning network. Our results demonstrate that no matter interested object is single feature or rich details, the interference can be successfully filtered out and this idea can be applied in some common applications that effectively improve the performance. This bio-inspired optical system can act as the creature eye to achieve success on interested-based object imaging, object detection, object recognition and object tracking, etc.

cs.CV