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Realizing strong nonlinear optical responses is a long-standing goal of both fundamental and technological importance. Recently significant efforts have focused on exploring excitons in solids as a pathway to achieving nonlinearities even down to few-photon levels. However, a crucial tradeoff arises as strong light-matter interactions require large oscillator strength and short radiative lifetime of the excitons, which limits their interaction strength and nonlinearity. Here we experimentally demonstrate strong nonlinear optical responses by exploiting the coupling between excitons and carriers in an atomically thin semiconductor of trilayer tungsten diselenide. By controlling the electric field and electrostatic doping of the trilayer, we observe the hybridization between intralayer and interlayer excitons along with the formation of Fermi polarons due to the interactions between excitons and free carriers. We find substantial optical nonlinearity can be achieved under both continuous wave and pulsed laser excitation, where the resonance of the hole-doped Fermi polaron blueshifts by as much as ~10 meV. Intriguingly, we observe a remarkable asymmetry in the optical nonlinearity between electron and hole doping, which is tunable by the applied electric field. We attribute these features to the strong interactions between excitons and free charges with optically induced valley polarization. Our results establish that atomically thin heterostructures are a highly versatile platform for engineering nonlinear optical response with applications to classical and quantum optoelectronics, and open avenues for exploring many-body physics in hybrid Fermionic-Bosonic systems., Comment: 4 figures with SI

Magnetism in topological materials creates phases exhibiting quantized transport phenomena with applications in spintronics and quantum information. The emergence of such phases relies on strong interaction between localized spins and itinerant states comprising the topological bands, and the subsequent formation of an exchange gap. However, this interaction has never been measured in any intrinsic magnetic topological material. Using a multimodal approach, this exchange interaction is measured in MnBi2Te4, the first realized intrinsic magnetic topological insulator. Interrogating nonequilibrium spin dynamics, itinerant bands are found to exhibit a strong exchange coupling to localized Mn spins. Momentum-resolved ultrafast electron scattering and magneto-optic measurements reveal that itinerant spins disorder via electron-phonon scattering at picosecond timescales. Localized Mn spins, probed by resonant X-ray scattering, disorder concurrently with itinerant spins, despite being energetically decoupled from the initial excitation. Modeling the results using atomistic simulations, the exchange coupling between localized and itinerant spins is estimated to be >100 times larger than superexchange interactions. This implies an exchange gap of >25 meV should occur in the topological surface states. By directly quantifying local-itinerant exchange coupling, this work validates the materials-by-design strategy of utilizing localized magnetic order to create and manipulate magnetic topological phases, from static to ultrafast timescales.

Answering complex questions about images is an ambitious goal for machine intelligence, which requires a joint understanding of images, text, and commonsense knowledge, as well as a strong reasoning ability. Recently, multimodal Transformers have made great progress in the task of Visual Commonsense Reasoning (VCR), by jointly understanding visual objects and text tokens through layers of cross-modality attention. However, these approaches do not utilize the rich structure of the scene and the interactions between objects which are essential in answering complex commonsense questions. We propose a Scene Graph Enhanced Image-Text Learning (SGEITL) framework to incorporate visual scene graphs in commonsense reasoning. To exploit the scene graph structure, at the model structure level, we propose a multihop graph transformer for regularizing attention interaction among hops. As for pre-training, a scene-graph-aware pre-training method is proposed to leverage structure knowledge extracted in the visual scene graph. Moreover, we introduce a method to train and generate domain-relevant visual scene graphs using textual annotations in a weakly-supervised manner. Extensive experiments on VCR and other tasks show a significant performance boost compared with the state-of-the-art methods and prove the efficacy of each proposed component., Comment: AAAI 2022

Due to the absence of matching carbon atoms at honeycomb centers with carbon atoms in adjacent graphene sheets, theorists predicted that a sliding process is needed to form AA, AB, or ABC stacking when directly converting graphite into sp3 bonded diamond. Here, using twisted bilayer graphene, which naturally provides AA and AB stacking configurations, we report the ultrafast formation of a transient 2D diamond-like structure (which is not observed in aligned graphene) under femtosecond laser irradiation. This photo-induced phase transition is evidenced by the appearance of new bond lengths of 1.94A and 3.14A in the time-dependent differential pair distribution function using MeV ultrafast electron diffraction. Molecular dynamics and first principles calculation indicate that sp3 bonds nucleate at AA and AB stacked areas in moire pattern. This work sheds light on the direct graphite-to-diamond transformation mechanism, which has not been fully understood for more than 60 years.