Current-induced motion of twisted skyrmions

Twisted skyrmions, whose helicity angles are different from that of Bloch skyrmions and N\'eel skyrmions, have already been demonstrated in experiments recently. In this work, we first contrast the magnetic structure and origin of the twisted skyrmion with other three types of skyrmion including Bloch skyrmion, N\'eel skyrmion and antiskyrmion. Following, we investigate the dynamics of twisted skyrmions driven by the spin transfer toque (STT) and the spin Hall effect (SHE) by using micromagnetic simulations. It is found that the spin Hall angle of the twisted skyrmion is related to the dissipative force tensor and the Gilbert damping both for the motions induced by the STT and the SHE, especially for the SHE induced motion, the skyrmion Hall angle depends substantially on the skyrmion helicity. At last, we demonstrate that the trajectory of the twisted skyrmion can be controlled in a two dimensional plane with a Gilbert damping gradient. Our results provide the understanding of current-induced motion of twisted skyrmions, which may contribute to the applications of skyrmion-based racetrack memories

Self-attention Dual Embedding for Graphs with Heterophily

Graph Neural Networks (GNNs) have been highly successful for the node classification task. GNNs typically assume graphs are homophilic, i.e. neighboring nodes are likely to belong to the same class. However, a number of real-world graphs are heterophilic, and this leads to much lower classification accuracy using standard GNNs. In this work, we design a novel GNN which is effective for both heterophilic and homophilic graphs. Our work is based on three main observations. First, we show that node features and graph topology provide different amounts of informativeness in different graphs, and therefore they should be encoded independently and prioritized in an adaptive manner. Second, we show that allowing negative attention weights when propagating graph topology information improves accuracy. Finally, we show that asymmetric attention weights between nodes are helpful. We design a GNN which makes use of these observations through a novel self-attention mechanism. We evaluate our algorithm on real-world graphs containing thousands to millions of nodes and show that we achieve state-of-the-art results compared to existing GNNs. We also analyze the effectiveness of the main components of our design on different graphs.Comment: 9 pages, 15 figure

Holocene temperature trends in the Northern Hemisphere extratropics

As the latest epoch of the Earth’s history, the Holocene is commonly defined as the last 11.7 ka BP (hereafter referred to as ka) and represents a new phase, encompassing the time span of human civilization. The last deglaciation lasted well into the Holocene, implying that the early Holocene was characterized by a large-scale reorganization with transitions in various components of the climate system. Studying the Holocene can provide insights into how the climate system functions, apart from the theoretical contributions to climate history itself. We first conducted sets of simulations with different combinations of climate forcings for 11.5 ka and for the entire Holocene to investigate the response of the climate–ocean system to the main climate forcings. In particular, two possible freshwater flux (FWF) scenarios were further tested considering the relatively large uncertainty in reconstructed ice-sheet melting. Moreover, we compared four Holocene simulations performed with the LOVECLIM, CCSM3, FAMOUS and HadCM3 models by identifying the regions where the multi-model simulations are consistent and where they are not, and analysing the reasons at the two levels (of the models’ variables and of the model principles and physics) where mismatches were found. After this, these multi-model simulations were systematically compared with data-based reconstructions in five regions of the Northern Hemisphere (NH) extratropics, namely Fennoscandia, Greenland, North Canada, Alaska and high-latitude Siberia. Potential uncertainty sources were also analysed in both model simulations and proxy data, and the most probable climate histories were identified with the aid of additional evidence when available. Additionally, the contribution of climate change, together with forest fires and human population size, to the variation in Holocene vegetation cover in Fennoscandia was assessed by employing the variation partitioning method. With effects of climate forcings, including variations in orbital-scale insolation (ORB), melting of the ice sheets and changes in greenhouse gas (GHG) concentrations, the climate shows spatial heterogeneity both at 11.5 ka and over the course of the Holocene. At 11.5 ka, the positive summer ORB forcing overwhelms the minor negative GHG anomaly and causes a higher summer temperatures of 2–4 °C in the extratropical continents than at 0 ka. The ice-sheet forcings primarily induce climatic cooling, and the underlying mechanisms include enhanced surface albedo over ice sheets, anomalous atmospheric circulation, reduced the Atlantic Meridional Overturning Circulation (AMOC) and relevant feedbacks. In particular, the most distinct feature is a thermally contrasting pattern over North America, with simulated temperatures being around 2 °C higher than those at 0 ka for Alaska, whereas over most of Canada, temperatures are more than 3 °C lower. The geographical variability of simulated temperatures is also reflected in Holocene temperature evolution, especially during the early Holocene, as constant Holocene cooling in Alaska contrasts with strong early-Holocene warming (warming rate over 1 °C kyr-1) in northern Canada. The early-Holocene climate is sensitive to the FWF forcings and a brief comparison with proxy records suggests that our updated FWF (FWF-v2, with a larger FWF release from the Greenland ice sheet and a faster FWF from the Fennoscandian Ice sheet (FIS)) represents a more realistic Holocene temperature scenario regarding the early-Holocene warming and Holocene temperature maximum (HTM). Comparison of multiple simulations suggests that the multi-model differences are spatially heterogeneous, despite overall consistent temperatures in the NH extratropics as a whole. On the one hand, reasonably consistent temperature trends (a temporal pattern with the early-Holocene warming, following a warm period and a gradual decrease toward 0 ka) are found over the regions where the climate is strongly influenced by the ice sheets, including Greenland, N Canada, N Europe and central-West Siberia. On the other hand, large inter-model variation exists in the regions over which the ice sheet effects on the climate were relatively weak via indirect influences, such as in Alaska, the Arctic, and E Siberia. In these three regions, the signals of multi-model simulations during the early Holocene are incompatible, especially in winter, when both positive and negative early-Holocene anomalies are suggested by different models. These divergent temperatures can be attributed to inconsistent responses of model variables. Southerly winds, surface albedo and sea ice can result in divergent temperature trends across models in Alaska, Siberia and the Arctic. Further comparisons reveal that divergent responses in these climate variables across the models can be partially caused by model differences (e.g. different model physics and resolution). For instance, the newly adopted formulation of the turbulent transfer coefficient in CCSM3 causes an overestimated albedo over Siberia at 0 ka, which leads to a stronger early-Holocene warmth than in other models. Moreover, the relatively simplified sea ice representation in FAMOUS probably leads to overestimated sea ice cover in the Arctic Ocean. The coarse vertical resolution in LOVECLIM might also introduce strong responses in atmospheric circulation over Alaska. From the perspective of climate features, the transient feature of the early-Holocene climate driven by the retreating ice sheets also influences the inter-model comparisons, as this transient feature induces a large degree of uncertainty into the FWF forcing. Comparisons of multiple model results with compiled proxy data at the sub-continental scale of NH high latitudes (i.e. Fennoscandia, Greenland, north Canada, Alaska and Siberia) reveal regionally-dependent consistencies in Holocene temperatures. In Fennoscandia, simulations and pollen data suggest a summer warming of 2 °C by 8 ka, although this is less expressed in chironomid data. In Canada, an early-Holocene warming of 4 °C in summer is suggested by both the simulations and pollen results. In Greenland, the magnitude of early-Holocene warming of annual mean ranges from 6 °C in simulations to 8 °C in δ18O-based temperatures. By contrast, simulated and reconstructed summer temperatures are mismatched in Alaska. Pollen data suggest 4 °C early-Holocene warming, while the simulations indicate 2 °C Holocene cooling, and chironomid data show a stable trend. Meanwhile, a high frequency of Alaskan peatland initiation before 9 ka can either reflect a high temperature, high soil moisture content or large seasonality. In high-latitude Siberia, simulations and proxy data depict high Holocene temperatures, although these signals are noisy owing to a large spread in the simulations and to a difference between pollen and chironomid results. On the whole, these comparisons of multi-model simulations with proxy reconstructions further confirm the Holocene climate evolution patterns in Fennoscandia, Greenland and North Canada. This implies that the Holocene temperatures in these regions have been relatively well established, with a reasonable representation of Holocene climate in the multiple simulations and a plausible explanation for the underlying mechanisms. However, the Holocene climate history and underlying mechanisms in the regions of Siberia and Alaska remain inconclusive. Variation partitioning revealed that climate was the main driver of vegetation dynamics in Fennoscandia during the Holocene as a whole and before the onset of farming. Forest fires and population size had relatively small contributions to vegetation change. However, the size of the human population became a more important driver of variation in vegetation composition than climate during the agricultural period, which can be estimated to have begun at 7–6 ka in Sweden and 4–3 ka in Finland. There is a clear region-dependent pattern of change caused by the human population: the impact of human activities on vegetation dynamics was notably higher in south Sweden and southwest Finland, where land use was more intensive, in comparison with central Sweden and southeast Finland. This thesis investigates the climate responses to the main forcings during the Holocene through various approaches, which has potential implications for the interactions between ice sheets and the climate, the Holocene climate history and current global change. The atmosphere-ocean system was sensitive to the FWF forcing during the early Holocene, implying that existing uncertainties in reconstructions of ice-sheet dynamics can be constrained by applying different freshwater scenarios via a comparison with proxy data. The Holocene climate history in most of the Northern Hemisphere extratropics is relatively well established, especially in regions that were strongly influenced by ice sheets. The implications of our investigation (on the transient early-Holocene) for the current global change are twofold. First, regional heterogeneity of the climate responses implies that regional differences should be taken into account when adapting to the current global change. Second, apart from the different scenarios of GHG forcing, inter-model comparison would be a good option to reduce model-dependency in estimation of the future climate

Activated Vibrational Modes and Fermi Resonance in Tip-Enhanced Raman Spectroscopy

Using p-aminothiophenol (PATP) molecules on a gold substrate as prototypical examples and high vacuum tip-enhanced Raman spectroscopy (HV-TERS), we show that the vibrational spectra of those molecules are distinctly different from those in typical surface-enhanced Raman spectroscopy. Detailed first-principles calculations help to assign the Raman peaks in the TERS measurements as Raman active and infrared (IR) active vibrational modes of dimercaptoazobenzene (DMAB), thus providing strong spectroscopic evidence for the conversion of PATP dimerization to DMAB. The activation of the IR active modes is due to enhanced electromagnetic field gradient effects within the gap region of the highly asymmetric tip-surface geometry. Our TERS measurements also realize splitting of certain vibrational modes due to Fermi resonance between a fundamental mode and the overtone of a different mode or a combinational mode. These findings help to broaden the versatility of TERS as a promising technique for ultrasensitive molecular spectroscopy

Complementary Fusion of Deep Network and Tree Model for ETA Prediction

Estimated time of arrival (ETA) is a very important factor in the transportation system. It has attracted increasing attentions and has been widely used as a basic service in navigation systems and intelligent transportation systems. In this paper, we propose a novel solution to the ETA estimation problem, which is an ensemble on tree models and neural networks. We proved the accuracy and robustness of the solution on the A/B list and finally won first place in the SIGSPATIAL 2021 GISCUP competition

Propagating Surface Plasmon Polaritons: Towards Applications for Remote-Excitation Surface Catalytic Reactions

Plasmonics is a well-established field, exploiting the interaction of light and metals at the nanoscale; with the help of surface plasmon polaritons, remote-excitation can also be observed by using silver or gold plasmonic waveguides. Recently, plasmonic catalysis was established as a new exciting platform for heterogeneous catalytic reactions. Recent reports present remote-excitation surface catalytic reactions as a route to enhance the rate of chemical reactions, and offer a pathway to control surface catalytic reactions. In this review, we focus on recent advanced reports on silver plasmonic waveguide for remote-excitation surface catalytic reactions. First, the synthesis methods and characterization techniques of sivelr nanowire plasmonic waveguides are summarized, and the properties and physical mechanisms of plasmonic waveguides are presented in detail. Then, the applications of plasmonic waveguides including remote excitation fluorescence and SERS are introduced, and we focus on the field of remote-excitation surface catalytic reactions. Finally, forecasts are made for possible future applications for the remote-excitation surface catalysis by plasmonic waveguides in living cells

S-NeRF++: Autonomous Driving Simulation via Neural Reconstruction and Generation

Autonomous driving simulation system plays a crucial role in enhancing self-driving data and simulating complex and rare traffic scenarios, ensuring navigation safety. However, traditional simulation systems, which often heavily rely on manual modeling and 2D image editing, struggled with scaling to extensive scenes and generating realistic simulation data. In this study, we present S-NeRF++, an innovative autonomous driving simulation system based on neural reconstruction. Trained on widely-used self-driving datasets such as nuScenes and Waymo, S-NeRF++ can generate a large number of realistic street scenes and foreground objects with high rendering quality as well as offering considerable flexibility in manipulation and simulation. Specifically, S-NeRF++ is an enhanced neural radiance field for synthesizing large-scale scenes and moving vehicles, with improved scene parameterization and camera pose learning. The system effectively utilizes noisy and sparse LiDAR data to refine training and address depth outliers, ensuring high quality reconstruction and novel-view rendering. It also provides a diverse foreground asset bank through reconstructing and generating different foreground vehicles to support comprehensive scenario creation. Moreover, we have developed an advanced foreground-background fusion pipeline that skillfully integrates illumination and shadow effects, further enhancing the realism of our simulations. With the high-quality simulated data provided by our S-NeRF++, we found the perception methods enjoy performance boost on several autonomous driving downstream tasks, which further demonstrate the effectiveness of our proposed simulator

Spatial contrasts of the Holocene hydroclimate trend between North and East Asia

The hydroclimate over Asia has undergone important changes over the Holocene with spatially asynchronous trends. Proxy-based evidence shows that North Asia was markedly drier than today during the early Holocene, whereas East Asia, influenced by the monsoon system, was substantially wetter. Yet, the causes behind this contrast are only partly understood due to a lack of overview of the most important factors. Here we explore a combination of climate proxies and multiple climate-model simulations to show that the strong contrast between the dry North Asia and wet (mid-latitude) East Asia is explained by a complex interplay between the effects of remnant ice sheets and orbital forcing. In North Asia, the climate was dry due a weakening of the westerlies and reduced atmospheric humidity, linked to the ice sheets in North America and Fennoscandia. In East Asia, contrarily, the orbitally-forced enhancement of the summer monsoons caused the early Holocene climate to be much wetter than during the presentday. These results indicate that the sensitivity of the hydroclimate in Asia to climate-forcings is spatially different, with important implications for the interpretation of past and future climate changes in this region. (C) 2019 Elsevier Ltd. All rights reserved.Peer reviewe