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Coherent phonons in the Terahertz (THz) regime have gained attention as potential candidates for next-generation high-speed, low-energy information carriers in atomically thin phononic or phonon-integrated on-chip devices. Nevertheless, achieving efficient control of the phonon generation dynamics over THz coherent phonons continues to pose a considerable challenge. In this work, we explore THz coherent phonon generation in exfoliated van der Waals (vdW) flakes of WSe2 on Au (WSe2/Au) and Si (WSe2/Si) by using time-resolved pump–probe spectroscopy. The generation of THz coherent phonons was studied as a function of the WSe2 layer thickness and laser wavelength. Notably, a significant enhancement in THz coherent phonon generation was observed in the WSe2/Au structure, but only within a specific range of WSe2 thicknesses and laser wavelengths. The results from numerical simulations, which consider a self-hybridized optical cavity depending on WSe2 thickness and optical reflectance and Raman spectroscopy measurements, all align well with the time-domain observations of THz coherent phonon generation. We propose that the observed enhancement in THz coherent phonon generation is strongly influenced by light–matter interactions in the WSe2 cavity, a mechanism that may be applicable to a broader range of vdW materials. These findings offer promising insights for the development of THz phononic or phonon-integrated devices. 

Optical control of magnons in two-dimensional (2D) materials promises new functionalities for spintronics and magnonics in atomically thin devices. Here, we report control of magnon dynamics, using laser polarization, in a ferromagnetic van der Waals (vdW) material, Fe_3.6Co_1.4GeTe₂. The magnon amplitude, frequency, and lifetime are controlled and monitored by time-resolved pump-probe spectroscopy. We show substantial (over 25%) and continuous modulation of magnon dynamics as a function of incident laser polarization. Our results suggest that the modification of the effective demagnetization field and magnetic anisotropy by the pump laser pulses with different polarizations is due to anisotropic optical absorption. This implies that pump laser pulses modify the local spin environment, which enables the launch of magnons with tunable dynamics. Our first-principles calculations confirm the anisotropic optical absorption of different crystal orientations. Our findings suggest a new route for the development of opto-spintronic or opto-magnonic devices. 

Low-rank compression is an important model compression strategy for obtaining compact neural network models. In general, because the rank values directly determine the model complexity and model accuracy, proper selection of layer-wise rank is very critical and desired. To date, though many low-rank compression approaches, either selecting the ranks in a manual or automatic way, have been proposed, they suffer from costly manual trials or unsatisfied compression performance. In addition, all of the existing works are not designed in a hardware-aware way, limiting the practical performance of the compressed models on real-world hardware platforms. To address these challenges, in this paper we propose HALOC, a hardware-aware automatic low-rank compression framework. By interpreting automatic rank selection from an architecture search perspective, we develop an end-to-end solution to determine the suitable layer-wise ranks in a differentiable and hardware-aware way. We further propose design principles and mitigation strategy to efficiently explore the rank space and reduce the potential interference problem.Experimental results on different datasets and hardware platforms demonstrate the effectiveness of our proposed approach. On CIFAR-10 dataset, HALOC enables 0.07% and 0.38% accuracy increase over the uncompressed ResNet-20 and VGG-16 models with 72.20% and 86.44% fewer FLOPs, respectively. On ImageNet dataset, HALOC achieves 0.9% higher top-1 accuracy than the original ResNet-18 model with 66.16% fewer FLOPs. HALOC also shows 0.66% higher top-1 accuracy increase than the state-of-the-art automatic low-rank compression solution with fewer computational and memory costs. In addition, HALOC demonstrates the practical speedups on different hardware platforms, verified by the measurement results on desktop GPU, embedded GPU and ASIC accelerator.