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Here, we study the controllable optical responses in a two-cavity optomechanical system, especially on the $\mathit{perfect}$ optomechanically induced transparency (OMIT) in the model which has never been studied before. The results show that the perfect OMIT can still occur even with a large mechanical damping rate, and at the perfect transparency window the long-lived slow light can be achieved. In addition, we find that the conversion between the perfect OMIT and optomechanically induced absorption can be easily achieved just by adjusting the driving field strength of the second cavity. We believe that the results can be used to control optical transmission in modern optical networks., Comment: 8 pages, 9 figures

We investigate the gravitational lensing effect around a spherically symmetric black hole, whose metric is obtained from the Einstein field equation with electric charge and perfect-fluid dark matter contributing to its energy-momentum tensor. We do the calculation analytically in the weak field limit and we assume that both the charge and the dark matter are much less abundant (only give rise to the next-leading-order contribution) in comparison to the black hole mass. In particular, we derive the light deflection angle and the size of the Einstein ring, where approximations up to the next-leading order are done with extra care, especially for the logarithmic term from perfect-fluid dark matter. We expect our results will be useful in the future to relate the theoretical model of perfect fluid dark matter with observations of celestial bodies immersed in thin dark matter., Comment: 14 pages, 3 figures; v2: adding some references

Drone-based quantum link has the potential to realize mobile quantum network, and entanglement distribution has been demonstrated using one and two drones. Here we report the first drone-based quantum key distribution (QKD), with average secure key rate larger than 8 kHz using decoy-state BB84 protocol with polarization coding. Compact acquisition, pointing, and tracking (APT) system and QKD modules are developed and loaded on a home-made octocopter, within takeoff weight of 30 kg. A robust link is established between the flying octocopter and a ground station separated 200 meters away and real-time QKD is performed for 400 seconds. This work shows potential of drone-based quantum communication for the future mobile quantum networks.

Revealing the structural properties and understanding the evolutionary mechanisms of the urban heavy truck mobility network (UHTMN) provide insights in assessment of freight policies to manage and regulate the urban freight system, and are of vital importance for improving the livability and sustainability of cities. Although massive urban heavy truck mobility data become available in recent years, in-depth studies on the structure and evolution of UHTMN are still lacking. Here we use massive urban heavy truck GPS data in China to construct the UHTMN and reveal its a wide range of structure properties. We further develop an evolving network model that simultaneously considers weight, space and system element duplication. Our model reproduces the observed structure properties of UHTMN and helps us understand its underlying evolutionary mechanisms. Our model also provides new perspectives for modeling the evolution of many other real-world networks, such as protein interaction networks, citation networks and air transportation networks., Comment: 18 pages, 6 figures

Phase change under reduced environmental pressures is key to understanding liquid discharge and propulsion processes for aerospace applications. A representative case is the sessile water droplets exposed to high vacuum, which experience complex phase change and transport phenomena that behave so differently than that under the atmosphere. Here, we demonstrate a previously unexplored aspect of the mechanism governing icing droplet self-launching from superhydrophobic surfaces when exposed to low pressures (~100 Pa). In contrast to the previously reported recalescence-induced local overpressure underneath the droplet that propels icing droplet self-jumping, we show that the progressive recalescence over the free surface plays a significant role in droplet icing and jumping. The joint contribution of the top-down vaporization momentum and bottom-up local overpressure momentum leads to vaporization-compression-detaching dynamics of the freezing droplets. We delineate the jumping velocity of the icing droplet by analyzing droplet vaporization mediated by freezing and substrate structuring, and reveal jumping direction coupled with the spatially probabilistic ice nucleation. Our study provides new insights into phase change of supercooled droplets at extreme conditions seen in aerospace and vacuum industries., Comment: 21 pages, 5 figures

While many systems have been developed to train Graph Neural Networks (GNNs), efficient model inference and evaluation remain to be addressed. For instance, using the widely adopted node-wise approach, model evaluation can account for up to 94% of the time in the end-to-end training process due to neighbor explosion, which means that a node accesses its multi-hop neighbors. On the other hand, layer-wise inference avoids the neighbor explosion problem by conducting inference layer by layer such that the nodes only need their one-hop neighbors in each layer. However, implementing layer-wise inference requires substantial engineering efforts because users need to manually decompose a GNN model into layers for computation and split workload into batches to fit into device memory. In this paper, we develop Deep Graph Inference (DGI) -- a system for easy and efficient GNN model inference, which automatically translates the training code of a GNN model for layer-wise execution. DGI is general for various GNN models and different kinds of inference requests, and supports out-of-core execution on large graphs that cannot fit in CPU memory. Experimental results show that DGI consistently outperforms layer-wise inference across different datasets and hardware settings, and the speedup can be over 1,000x., Comment: 10 pages, 10 figures

Controlling the spin transport at the single-molecule level, especially without the use of ferromagnetic contacts, becomes a focus of research in spintronics. Inspired by the progress on atomic-level molecular synthesis, through first-principles calculations, we investigate the spin-dependent electronic transport of graphene nanoflakes with side-bonded functional groups, contacted by atomic carbon chain electrodes. It is found that, by rotating the functional group, the spin polarization of the transmission at the Fermi level could be switched between completely polarized and unpolarized states. Moreover, the transition between spin-up and spin-down polarized states can also be achieved, operating as a dual-spin filter. Further analysis shows that, it is the spin-dependent shift of density of states, caused by the rotation, that triggers the shift of transmission peaks, and then results in the variation of spin polarization. Such a feature is found to be robust to the of the nanoflake and the electrode material, showing great application potential. Those findings may throw light on the development of spintronic devices.

For large-scale still image coding tasks, the processing platform needs to ensure that the coded images meet the quality requirement. Therefore, the quality control algorithms that generate adaptive QP towards a target quality level for image coding are of significant research value. However, the existing quality control methods are limited by low accuracy, excessive computational cost, or temporal information dependence. In this paper, we propose a concise {\lambda} domain linear distortion model and an accurate model parameters estimation method based on the original data. Since the model parameters are obtained from the original data, the proposed method is decoupled from the RDO process and can be applied to different image encoders. Experiments show that the proposed quality control algorithm achieves the highest control accuracy and the lowest delay in the literature at the same time. The application of Alibaba's e-commerce platform also shows that the proposed algorithm can significantly reduce the overall bitrate while greatly reducing the bad case ratio.

Two-dimensional materials support deeply confined and tunable plasmonic modes, which have great potential for achieving device miniaturization and flexible manipulation. In this paper, we propose a diffraction-unlimited system composed of borophene layer and perovskite grating to investigate the strong coupling between the borophene guiding plasmon (BGP) and perovskite exciton (PE) mode. The resonant energy of BGP mode could be electrically tuned to match the energy of PE mode, and a remarkable Rabi splitting is attained under zero-detuning condition. The splitting energy could reach 230 meV due to the strong field enhancement provided by BGP mode. Consequently, an active reflective phase modulation with 1.76{\pi} range is achieved by dynamically manipulating the detuning. Furthermore, by increasing the distance between the borophene layer and perovskite grating, a parity-time symmetry breaking could be observed with the vanished energy splitting. Our results deepen the understanding of light-matter interaction at the sub-wavelength scale and provide a guideline for designing active plasmonic devices., Comment: 9 pages, 4 figures

With the development of learning-based embedding models, embedding vectors are widely used for analyzing and searching unstructured data. As vector collections exceed billion-scale, fully managed and horizontally scalable vector databases are necessary. In the past three years, through interaction with our 1200+ industry users, we have sketched a vision for the features that next-generation vector databases should have, which include long-term evolvability, tunable consistency, good elasticity, and high performance. We present Manu, a cloud native vector database that implements these features. It is difficult to integrate all these features if we follow traditional DBMS design rules. As most vector data applications do not require complex data models and strong data consistency, our design philosophy is to relax the data model and consistency constraints in exchange for the aforementioned features. Specifically, Manu firstly exposes the write-ahead log (WAL) and binlog as backbone services. Secondly, write components are designed as log publishers while all read-only analytic and search components are designed as independent subscribers to the log services. Finally, we utilize multi-version concurrency control (MVCC) and a delta consistency model to simplify the communication and cooperation among the system components. These designs achieve a low coupling among the system components, which is essential for elasticity and evolution. We also extensively optimize Manu for performance and usability with hardware-aware implementations and support for complex search semantics., Comment: 14 pages, 13 figures

Large-photon-number quantum state is a fundamental but non-resolved request for practical quantum information applications. Here we propose an N-photon state generation scheme that is feasible and scalable, using lithium niobate on insulator circuits. Such scheme is based on the integration of a common building block called photon-number doubling unit (PDU), for deterministic single-photon parametric down-conversion and up-conversion. The PDU relies on 10^7-optical-quality-factor resonator and mW-level on-chip power, which is within the current fabrication and experiment limits. N-photon state generation schemes, with cluster and GHZ state as examples, are shown for different quantum tasks.

The coherent superposition of position states in a quantum walk (QW) can be precisely engineered towards the desired distributions to meet the need of quantum information applications. The coherent distribution can make full use of quantum parallel in computation and simulation. Particularly, the uniform superposition provides the robust non-locality, which has wide applications such as the generation of genuine multi-bit random numbers without post-processing. We experimentally demonstrate that the rich dynamics featured with arbitrary coherent distributions can be obtained by introducing different sets of the time- and position-dependent operations. Such a QW is realized by a resource-constant and flexible optical circuit, in which the variable operation is executed based on a Sagnac interferometer in an intrinsically stable and precisely controlled way. Our results contribute to the practical realization of quantum-walk-based quantum computation, quantum simulations and quantum information protocols., Comment: 8 pages, 4 figures, 2 tables

We report the position-inhomogeneous quantum walk (IQW) can be utilized to produce the maximal high dimensional entanglement while maintaining the quadratic speedup spread of the wave-function. Our calculations show that the maximal coin-walker entanglement can be generated in any odd steps or asymptotically in even steps, and the nearly maximal entanglement can be obtained in even steps after $2$. We implement the IQW by a stable resource-saving time-bin optical network, in which a polarization Sagnac loop is employed to realize the precisely tunable phase shift. Our approach opens up an efficient way for high-dimensional entanglement engineering as well as promotes investigations on the role of coin-walker interactions in QW based applications., Comment: 7 pages, 6 figures, 1 table

How to accurately solve time-dependent Schr\"odinger equation is an interesting and important problem. Here, we propose a novel method to obtain the exact Floquet solutions of the Schr\"odinger equation for periodically driven systems by using Floquet theorem and a time-dependent unitary transformation. Using the method, we give out the exact Floquet solutions of wave function for three interesting physical models -- linear potential model, harmonic oscillator model, and the coupled harmonic oscillator model in the presence of a periodic driving. In addition to the quasienergy, we also give out the analytic expression of Berry phase for the harmonic oscillator model. Moreover, the idea presented in this paper can be used in mathematics to solve partial differential equations.

The New Vacuum Solar Telescope (NVST) has been releasing its novel winged Ha data (WHD) since April 2021, namely the Ha imaging spectroscopic data. Compared with the prior released version, the new data are further co-aligned among the off-band images and packaged into a standard solar physics community format. In this study, we illustrate the alignment algorithm used by the novel WHD, which is mainly based on the optical flow method to obtain the translation offset between the winged images. To quantitatively evaluate the alignment results of two images with different similarities, we calculate the alignment accuracies between the images of different off-band and line center, respectively. The result shows that our alignment algorithm could reach up to the accuracy of about 0.1 "when the off-band of winged image is lower than 0.6 \.A. In addition, we introduce the final product of the WHD in detail, which can provide convenience for the solar physicists to use high-resolution H{\alpha} imaging spectroscopic data of NVST., Comment: 11 pages, 5 figures