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In the past few years, Artificial Intelligence (AI)-based weather forecasting methods have widely demonstrated strong competitiveness among the weather forecasting systems. However, these methods are insufficient for high-spatial-resolution short-term nowcasting within 6 hours, which is crucial for warning short-duration, mesoscale and small-scale weather events. Geostationary satellite remote sensing provides detailed, high spatio-temporal and all-day observations, which can address the above limitations of existing methods. Therefore, this paper proposed an advanced data-driven thermal infrared cloud images forecasting model, "DaYu." Unlike existing data-driven weather forecasting models, DaYu is specifically designed for geostationary satellite observations, with a temporal resolution of 0.5 hours and a spatial resolution of ${0.05}^\circ$ $\times$ ${0.05}^\circ$. DaYu is based on a large-scale transformer architecture, which enables it to capture fine-grained cloud structures and learn fast-changing spatio-temporal evolution features effectively. Moreover, its attention mechanism design achieves a balance in computational complexity, making it practical for applications. DaYu not only achieves accurate forecasts up to 3 hours with a correlation coefficient higher than 0.9, 6 hours higher than 0.8, and 12 hours higher than 0.7, but also detects short-duration, mesoscale, and small-scale weather events with enhanced detail, effectively addressing the shortcomings of existing methods in providing detailed short-term nowcasting within 6 hours. Furthermore, DaYu has significant potential in short-term climate disaster prevention and mitigation.

In the realm of event prediction, temporal knowledge graph forecasting (TKGF) stands as a pivotal technique. Previous approaches face the challenges of not utilizing experience during testing and relying on a single short-term history, which limits adaptation to evolving data. In this paper, we introduce the Online Neural-Symbolic Event Prediction (ONSEP) framework, which innovates by integrating dynamic causal rule mining (DCRM) and dual history augmented generation (DHAG). DCRM dynamically constructs causal rules from real-time data, allowing for swift adaptation to new causal relationships. In parallel, DHAG merges short-term and long-term historical contexts, leveraging a bi-branch approach to enrich event prediction. Our framework demonstrates notable performance enhancements across diverse datasets, with significant Hit@k (k=1,3,10) improvements, showcasing its ability to augment large language models (LLMs) for event prediction without necessitating extensive retraining. The ONSEP framework not only advances the field of TKGF but also underscores the potential of neural-symbolic approaches in adapting to dynamic data environments., Comment: 16 pages, ACL 2024 Findings

The Lyman-alpha Solar Telescope (LST) on board the Advanced Space-based Solar Observatory (ASO-S) is the first payload to image the full solar disk and the solar corona in both white-light (WL) and ultraviolet (UV) H I Lya, extending up to 2.5 solar radii (Rs). Since the launch of the ASO-S on 9 October 2022, LST has captured various significant solar activities including flares, prominences, coronal mass ejections (CMEs). LST covers different passbands of 121.6 nm, 360 nm and 700 nm. The Lya Solar Disk Imager (SDI) has a field of view (FOV) of 38.4 arcmin and a spatial resolution of around 9.5 arcsec, while the White-Light Solar Telescope (WST) has a FOV of 38.43 arcmin and a spatial resolution of around 3.0 arcsec. The FOV of the Lya Solar Corona Imager (SCI) reaches 81.1 arcmin and its spatial resolution is 4.3 arcsec. The stray-light level in the 700 nm waveband is about 7.8e-6 MSB (mean solar brightness) at 1.1 Rs and 7.6e-7 MSB at 2.5 Rs, and in the Lya waveband it is around 4.3e-3 MSB at 1.1 Rs and 4.1e-4 MSB at 2.5 Rs. This article will detail the results from on-orbit tests and calibrations., Comment: Solar Physics (ASO-S mission topical collection), accepted

UWB ranging systems have been adopted in many critical and security sensitive applications due to its precise positioning and secure ranging capabilities. We present a practical jamming attack, namely UWBAD, against commercial UWB ranging systems, which exploits the vulnerability of the adoption of the normalized cross-correlation process in UWB ranging and can selectively and quickly block ranging sessions without prior knowledge of the configurations of the victim devices, potentially leading to severe consequences such as property loss, unauthorized access, or vehicle theft. UWBAD achieves more effective and less imperceptible jamming due to: (i) it efficiently blocks every ranging session by leveraging the field-level jamming, thereby exerting a tangible impact on commercial UWB ranging systems, and (ii) the compact, reactive, and selective system design based on COTS UWB chips, making it affordable and less imperceptible. We successfully conducted real attacks against commercial UWB ranging systems from the three largest UWB chip vendors on the market, e.g., Apple, NXP, and Qorvo. We reported our findings to Apple, related Original Equipment Manufacturers (OEM), and the Automotive Security Research Group, triggering internal security incident response procedures at Volkswagen, Audi, Bosch, and NXP. As of the writing of this paper, the related OEM has acknowledged this vulnerability in their automotive systems and has offered a $5,000 reward as a bounty., Comment: Proceedings of the 2024 ACM SIGSAC Conference on Computer and Communications Security

Sympathetic eruptions of solar prominences have been studied for decades, however, it is usually difficult to identify their causal links. Here we present two failed prominence eruptions on 26 October 2022 and explore their connections. Using stereoscopic observations, the south prominence (PRO-S) erupts with untwisting motions, flare ribbons occur underneath, and new connections are formed during the eruption. The north prominence (PRO-N) rises up along with PRO-S, and its upper part disappears due to catastrophic mass draining along an elongated structure after PRO-S failed eruption. We suggest that the eruption of PRO-S initiates due to a kink instability, further rises up, and fails to erupt due to reconnection with surrounding fields. The elongated structure connecting PRO-N overlies PRO-S, which causes the rising up of PRO-N along with PRO-S and mass drainage after PRO-S eruption. This study suggests that a prominence may end its life through mass drainage forced by an eruption underneath., Comment: 15 pages, 7 figures, has been accepted by Solar Physics

Quasicrystals represent a category of rarely structured solids that challenge traditional periodicity in crystal materials. Recent advancements in the synthesis of two-dimensional (2D) van der Waals materials have paved the way for exploring the unique physical properties of these systems. Here, we report on the synthesis of 2D quasicrystals featuring 30{\deg} alternating twist angles between multiple graphene layers, using chemical vapor deposition (CVD). Strikingly, we observed periodic Moir\'e patterns in the quasicrystal, a finding that has not been previously reported in traditional alloy-based quasicrystals. The Moir\'e periodicity, varying with the parity of the constituent layers, aligns with the theoretical predictions that suggest a stress cancellation mechanism in force. The emergence of Moir\'e fringes is attributed to the spontaneous mismatched lattice constant in the oriented graphene layers, proving the existence of atomic relaxation. This phenomenon, which has been largely understudied in graphene systems with large twist angles, has now been validated through our use of scanning transmission electron microscopy (STEM). Our CVD-grown Moir\'e quasicrystal provides an ideal platform for exploring the unusual physical properties that arise from Moir\'e periodicity within quasicrystals.

Identifying whether an artwork was used to train a diffusion model is an important research topic, given the rising popularity of AI-generated art and the associated copyright concerns. The work approaches this problem from the membership inference attack (MIA) perspective. We first identify the limitations of applying existing MIA methods for copyright protection: the required access of internal U-nets and the choice of non-member datasets for evaluation. To address the above problems, we introduce a novel black-box membership inference attack method that operates without needing access to the model's internal U-net. We then construct a DALL-E generated dataset for a more comprehensive evaluation. We validate our method across various setups, and our experimental results outperform previous works.

Solar white-light flares are characterized by an enhancement in the optical continuum, which are usually large flares (say X- and M-class flares). Here we report a small C2.3 white-light flare (SOL2022-12-20T04:10) observed by the \emph{Advanced Space-based Solar Observatory} and the \emph{Chinese H$\alpha$ Solar Explorer}. This flare exhibits an increase of $\approx$6.4\% in the photospheric Fe \textsc{i} line at 6569.2\,\AA\ and {$\approx$3.2\%} in the nearby continuum. The continuum at 3600\,\AA\ also shows an enhancement of $\approx$4.7\%. The white-light brightening kernels are mainly located at the flare ribbons and co-spatial with nonthermal hard X-ray sources, which implies that the enhanced white-light emissions are related to nonthermal electron-beam heating. At the brightening kernels, the Fe \textsc{i} line displays an absorption profile that has a good Gaussian shape, with a redshift up to $\approx$1.7 km s$^{-1}$, while the H$\alpha$ line shows an emission profile though having a central reversal. The H$\alpha$ line profile also shows a red or blue asymmetry caused by plasma flows with a velocity of several to tens of km s$^{-1}$. It is interesting to find that the H$\alpha$ asymmetry is opposite at the conjugate footpoints. It is also found that the CHASE continuum increase seems to be related to the change of photospheric magnetic field. Our study provides comprehensive characteristics of a small white-light flare that help understand the energy release process of white-light flares., Comment: 23 pages, 6 figures, accepted by Solar Physics

Recently tellurium (Te) has attracted resurgent interests due to its p-type characteristics and outstanding ambient environmental stability. Here we present a substrate engineering based physical vapor deposition method to synthesize high-quality Te nanoflakes and achieved a field-effect hole mobility of 1500 cm2/Vs, which is, to the best of our knowledge, the highest among the existing synthesized van der Waals p-type semiconductors. The high mobility Te enables the fabrication of Te/MoS2 pn diodes with highly gate-tunable electronic and optoelectronic characteristics. The Te/MoS2 heterostructure can be used as a visible range photodetector with a current responsivity up to 630 A/W, which is about one order of magnitude higher than the one achieved using p-type Si-MoS2 PN photodiodes. The photo response of the Te/MoS2 heterojunction also exhibits strong gate tunability due to their ultrathin thickness and unique band structures. The successful synthesis of high mobility Te and the enabled Te/MoS2 photodiodes show promise for the development of highly tunable and ultrathin photodetectors.

Satellite remote sensing serves as a crucial means to acquire cloud physical parameters. However, existing official cloud products derived from the advanced geostationary radiation imager (AGRI) onboard the Fengyun-4A geostationary satellite suffer from limitations in computational precision and efficiency. In this study, an image-based transfer learning model (ITLM) was developed to realize all-day and high-precision retrieval of cloud physical parameters using AGRI thermal infrared measurements and auxiliary data. Combining the observation advantages of geostationary and polar-orbiting satellites, ITLM was pre-trained and transfer-trained with official cloud products from advanced Himawari imager (AHI) and Moderate Resolution Imaging Spectroradiometer (MODIS), respectively. Taking official MODIS products as the benchmarks, ITLM achieved an overall accuracy of 79.93% for identifying cloud phase and root mean squared errors of 1.85 km, 6.72 um, and 12.79 for estimating cloud top height, cloud effective radius, and cloud optical thickness, outperforming the precision of official AGRI and AHI products. Compared to the pixel-based random forest model, ITLM utilized the spatial information of clouds to significantly improve the retrieval performance and achieve more than a 6-fold increase in speed for a single full-disk retrieval. Moreover, the AGRI ITLM products with spatiotemporal continuity and high precision were used to accurately describe the spatial distribution characteristics of cloud fractions and cloud properties over the Tibetan Plateau (TP) during both daytime and nighttime, and for the first time provide insights into the diurnal variation of cloud cover and cloud properties for total clouds and deep convective clouds across different seasons.

A soliton microcomb can play a crucial role in narrow-grid optical communications by replacing many independently operated lasers in wavelength-division multiplexing systems. In this work, we designed and demonstrated power-efficient soliton microcombs with 100-GHz free spectral range in an integrated 4H-SiC platform for the first time. The combination of enabling technologies, including efficient fiber coupling (3 dB insertion loss), high-quality-factor microrings (intrinsic quality factors up to 5.7 million), and the employment of the Raman effect for adiabatic accessing of the soliton state, has enabled the demonstration of soliton pump power as low as 6 mW while supporting comb powers above -20 dBm per line near the pump wavelength.

In this work, we study the cost efficient data versioning problem, where the goal is to optimize the storage and reconstruction (retrieval) costs of data versions, given a graph of datasets as nodes and edges capturing edit/delta information. One central variant we study is MinSum Retrieval (MSR) where the goal is to minimize the total retrieval costs, while keeping the storage costs bounded. This problem (along with its variants) was introduced by Bhattacherjee et al. [VLDB'15]. While such problems are frequently encountered in collaborative tools (e.g., version control systems and data analysis pipelines), to the best of our knowledge, no existing research studies the theoretical aspects of these problems. We establish that the currently best-known heuristic, LMG, can perform arbitrarily badly in a simple worst case. Moreover, we show that it is hard to get $o(n)$-approximation for MSR on general graphs even if we relax the storage constraints by an $O(\log n)$ factor. Similar hardness results are shown for other variants. Meanwhile, we propose poly-time approximation schemes for tree-like graphs, motivated by the fact that the graphs arising in practice from typical edit operations are often not arbitrary. As version graphs typically have low treewidth, we further develop new algorithms for bounded treewidth graphs. Furthermore, we propose two new heuristics and evaluate them empirically. First, we extend LMG by considering more potential ``moves'', to propose a new heuristic LMG-All. LMG-All consistently outperforms LMG while having comparable run time on a wide variety of datasets, i.e., version graphs. Secondly, we apply our tree algorithms on the minimum-storage arborescence of an instance, yielding algorithms that are qualitatively better than all previous heuristics for MSR, as well as for another variant BoundedMin Retrieval (BMR)., Comment: Accepted by IPDPS 2024

The existing silicon-carbide-on-insulator photonic platform utilizes a thin layer of silicon dioxide under silicon carbide to provide optical confinement and mode isolation. Here, we replace the underneath silicon dioxide layer with a 1-$\mu$m-thick aluminum nitride and demonstrate a 4H-silicon-carbide-on-aluminum-nitride integrated photonics platform for the first time. Efficient grating couplers, low-loss waveguides, and compact microring resonators with intrinsic quality factors up to 210,000 are fabricated. In addition, by undercutting the aluminum nitride layer, the intrinsic quality factor of the silicon carbide microring is improved by nearly one order of magnitude (1.8 million). Finally, an optical pump-probe method is developed to measure the thermal conductivity of the aluminum nitride layer, which is estimated to be over 30 times of that of silicon dioxide.

Implementing stimulated Raman scattering in a low-loss microresonator could lead to Raman lasing. Here, we report the demonstration of an efficient Raman laser with $>50 \%$ power efficiency in an integrated silicon carbide platform for the first time. By fine tuning the free spectral range (FSR) of 43-$\mu$m-radius silicon carbide microresonators, the Stokes resonance corresponding to the dominant Raman shift of $777\ \text{cm}^{-1}$ ($23.3$ THz) is aligned to the center of the Raman gain spectrum, resulting in a low power threshold of $2.5$ mW. The peak Raman gain coefficient is estimated to be ($0.75 \pm 0.15) \ \text{cm}/\text{GW}$ in the 1550 nm band, with an approximate full width at half maximum of ($120 \pm 30$) GHz. In addition, the microresonator is designed to exhibit normal dispersion at the pump wavelength near 1550 nm while possessing anomalous dispersion at the first Stokes near 1760 nm. At high enough input powers, a Kerr microcomb is generated by the Stokes signal acting as the secondary pump, which then mixes with the pump laser through four-wave mixing to attain a wider spectral coverage. Furthermore, cascaded Raman lasing and occurrence of multiple Raman shifts, including $204\ \text{cm}^{-1}$ ($6.1$ THz) and $266\ \text{cm}^{-1}$ ($8.0$ THz) transitions, are also observed. Finally, we show that the Stokes Raman could also help broaden the spectrum in a Kerr microcomb which has anomalous dispersion at the pump wavelength. Our example of a 100-GHz-FSR microcomb has a wavelength span from 1200 nm to 1900 nm with 300 mW on-chip power.

In complex reinforcement learning (RL) problems, policies with similar rewards may have substantially different behaviors. It remains a fundamental challenge to optimize rewards while also discovering as many diverse strategies as possible, which can be crucial in many practical applications. Our study examines two design choices for tackling this challenge, i.e., diversity measure and computation framework. First, we find that with existing diversity measures, visually indistinguishable policies can still yield high diversity scores. To accurately capture the behavioral difference, we propose to incorporate the state-space distance information into the diversity measure. In addition, we examine two common computation frameworks for this problem, i.e., population-based training (PBT) and iterative learning (ITR). We show that although PBT is the precise problem formulation, ITR can achieve comparable diversity scores with higher computation efficiency, leading to improved solution quality in practice. Based on our analysis, we further combine ITR with two tractable realizations of the state-distance-based diversity measures and develop a novel diversity-driven RL algorithm, State-based Intrinsic-reward Policy Optimization (SIPO), with provable convergence properties. We empirically examine SIPO across three domains from robot locomotion to multi-agent games. In all of our testing environments, SIPO consistently produces strategically diverse and human-interpretable policies that cannot be discovered by existing baselines.

This paper presents the design of a 6-DOF all-terrain micro aerial vehicle and two control strategies for multimodal flight, which are experimentally validated. The micro aerial vehicle is propelled by four motors and controlled by a single servo for the control of the cycloidal rotors(cyclorotors) speed and lift direction. Despite the addition of the servo, the system remains underactuated. To address the traditional underactuation problem of cycloidal rotor aircraft, we increase the number of control variables. We propose a PID and a nonlinear model predictive control (NMPC) framework to tackle the model's nonlinearities and achieve control of attitude, position, and their derivatives.Experimental results demonstrate the effectiveness of the proposed multimodal control strategy for 6-DOF all-terrain micro aerial vehicles. The vehicle can operate in aerial, terrestrial, and aquatic modes and can adapt to different terrains and environmental conditions. Our approach enhances the vehicle's performance in each mode of operation, and the results show the advantages of the proposed strategy compared to other control strategies.

We study online control for continuous-time linear systems with finite sampling rates, where the objective is to design an online procedure that learns under non-stochastic noise and performs comparably to a fixed optimal linear controller. We present a novel two-level online algorithm, by integrating a higher-level learning strategy and a lower-level feedback control strategy. This method offers a practical and robust solution for online control, which achieves sublinear regret. Our work provides the first nonasymptotic results for controlling continuous-time linear systems with finite number of interactions with the system. Moreover, we examine how to train an agent in domain randomization environments from a non-stochastic control perspective. By applying our method to the SAC (Soft Actor-Critic) algorithm, we achieved improved results in multiple reinforcement learning tasks within domain randomization environments. Our work provides new insights into non-asymptotic analyses of controlling continuous-time systems. Furthermore, our work brings practical intuition into controller learning under non-stochastic environments.

Optical phased arrays (OPA) with high integration, fast speed, low power consumption, and high steering resolution are critical components in the emerging photonic integrated circuit (PIC), LiDAR, free space optical communication, 3D printing, and so on. According to the OPA working principle, its function is generally achieved by independently controlling the phase of the array elements. In practice, this presents a major challenge to overcome critical trade-offs of the element numbers, the control electronics, and the power consumption. Here, we give an alternative OPA solution to overcome this technical limitation, in the form of a cascaded periodically poled electro-optical crystal structure. Compared with the existing OPA scheme, only one control electronics is used to control the entire array elements in the current proposal, regardless of the number of array elements, implying higher integration and lower power consumption. With the help of the fast response properties of electro-optic crystal materials, a high-speed and high-resolution beam steering device is demonstrated. Simulating results show that the angular resolution can be improved by several orders of magnitude when the number of the cascaded-layer increases. An OPA prototype of a 6-layer cascaded periodically poled LiNbO$_3$ (cascaded-PPLN) was designed, fabricated, and characterized. The experiment that observed beam deflection in cascaded-PPLN OPA agrees well with the simulation results. Meantime, by demonstrating dynamic beam steering continually, its capability of continuous scanning and continually active phase tunability has been verified. Therefore, this cascaded periodically poled electro-optical crystal OPA offers a feasible direction of miniaturization and low power consumption for the optical system, such as the PIC system.

Silicon carbide (SiC) recently emerged as a promising photonic and quantum material owing to its unique material properties. Here, we carry out an exploratory investigation of the electro-optic effect in high-quality-factor 4H-SiC microresonators. Our findings confirm the existence of the Pockels effect in 4H-SiC for the first time. The extracted Pockels coefficients show certain variations among 4H-SiC wafers from different manufacturers, with the magnitudes of $r_{13}$ and $r_{33}$ estimated to be in the range of (0.3-0.7) pm/V and (0-0.03) pm/V, respectively.