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Spatial, momentum and energy separation of electronic spins in condensed matter systems guides the development of novel devices where spin-polarized current is generated and manipulated. Recent attention on a set of previously overlooked symmetry operations in magnetic materials leads to the emergence of a new type of spin splitting, enabling giant and momentum-dependent spin polarization of energy bands on selected antiferromagnets. Despite the ever-growing theoretical predictions, the direct spectroscopic proof of such spin splitting is still lacking. Here, we provide solid spectroscopic and computational evidence for the existence of such materials. In the noncoplanar antiferromagnet MnTe$_2$, the in-plane components of spin are found to be antisymmetric about the high-symmetry planes of the Brillouin zone, comprising a plaid-like spin texture in the antiferromagnetic (AFM) ground state. Such an unconventional spin pattern, further found to diminish at the high-temperature paramagnetic state, stems from the intrinsic AFM order instead of spin-orbit coupling (SOC). Our finding demonstrates a new type of quadratic spin texture induced by time-reversal breaking, placing AFM spintronics on a firm basis and paving the way for studying exotic quantum phenomena in related materials., Comment: Version 3, 49 pages, 4 main figures, 13 extended data figures and 2 extended data tables. Nature in press (2024)

We observed the classical interacting galaxy M51 with FAST and obtain high sensitivity HI image with column density down to 3.8 $\times$ 10$^{18}$ cm$^{-2}$. In the image we can see a diffuse extended envelope around the system and several new tidal features. We also get a deeper look at M51b's probable gas, which has an approximated velocity range of 560 to 740 km s$^{-1}$ and a flux of 7.5 Jy km s$^{-1}$. Compared to the VLA image, we observe more complete structures of the Southeast Tail, Northeast Cloud and Northwest Plume, as well as new features of the Northwest Cloud and Southwest Plume. M51's most prominent tidal feature, the Southeast Tail, looks very long and broad, in addition with two small detached clouds at the periphery. Due to the presence of optical and simulated counterparts, the Northwest cloud appears to be the tail of M51a, while the Northwest Plume is more likely a tidal tail of M51b. The large mass of the Northwest Plume suggests that M51b may have been as gas-rich as M51a before the interaction. In addition, the formation process of the Northeast Cloud and Southwest Plume is obscured by the lack of optical and simulated counterparts. These novel tidal features, together with M51b's probable gas, will inspire future simulations and provide a deeper understanding of the evolution of this interacting system., Comment: 11 pages, 9 figures, accepted for publication in MNRAS

Based on a new HI survey using the Five-hundred-meter Aperture Spherical radio Telescope (FAST), combined with the Pan-STARRS1 images, we identified an isolated HI cloud without any optical counterpart, named FAST J0139+4328. The newly discovered HI cloud appears to be a typical disk galaxy since it has a double-peak shape in the global HI profile and an S-like rotation structure in the velocity-position diagram. Moreover, this disk galaxy has an extremely low absolute magnitude (M_B>-10.0 mag) and stellar mass (<6.9*10^5 Msun). Furthermore, we obtained that the HI mass of this galaxy is 8.3*10^7 Msun, and the dynamical mass to total baryonic mass ratio is 47+-27, implying that dark matter dominates over baryons in FAST J0139+4328. These findings provide observational evidence that FAST J0139+4328 is an isolated dark dwarf galaxy with a redshift of z=0.0083. This is the first time that an isolated dark galaxy has been detected in the nearby universe., Comment: 13 pages, 3 figures, Accepted for publication in the ApJ Letters

Smart traffic lights in intelligent transportation systems (ITSs) are envisioned to greatly increase traffic efficiency and reduce congestion. Deep reinforcement learning (DRL) is a promising approach to adaptively control traffic lights based on the real-time traffic situation in a road network. However, conventional methods may suffer from poor scalability. In this paper, we investigate deep reinforcement learning to control traffic lights, and both theoretical analysis and numerical experiments show that the intelligent behavior ``greenwave" (i.e., a vehicle will see a progressive cascade of green lights, and not have to brake at any intersection) emerges naturally a grid road network, which is proved to be the optimal policy in an avenue with multiple cross streets. As a first step, we use two DRL algorithms for the traffic light control problems in two scenarios. In a single road intersection, we verify that the deep Q-network (DQN) algorithm delivers a thresholding policy; and in a grid road network, we adopt the deep deterministic policy gradient (DDPG) algorithm. Secondly, numerical experiments show that the DQN algorithm delivers the optimal control, and the DDPG algorithm with passive observations has the capability to produce on its own a high-level intelligent behavior in a grid road network, namely, the ``greenwave" policy emerges. We also verify the ``greenwave" patterns in a $5 \times 10$ grid road network. Thirdly, the ``greenwave" patterns demonstrate that DRL algorithms produce favorable solutions since the ``greenwave" policy shown in experiment results is proved to be optimal in a specified traffic model (an avenue with multiple cross streets). The delivered policies both in a single road intersection and a grid road network demonstrate the scalability of DRL algorithms., Comment: 17 pages

BERTScore is an effective and robust automatic metric for referencebased machine translation evaluation. In this paper, we incorporate multilingual knowledge graph into BERTScore and propose a metric named KG-BERTScore, which linearly combines the results of BERTScore and bilingual named entity matching for reference-free machine translation evaluation. From the experimental results on WMT19 QE as a metric without references shared tasks, our metric KG-BERTScore gets higher overall correlation with human judgements than the current state-of-the-art metrics for reference-free machine translation evaluation.1 Moreover, the pre-trained multilingual model used by KG-BERTScore and the parameter for linear combination are also studied in this paper., Comment: 5 pages

We use the single-dish radio telescope FAST to map the HI in the tidally interacting NGC 4631 group with a resolution of 3.24$'$ (7 kpc), reaching a 5-$\sigma$ column density limit of $10^{17.9}$ cm$^{-2}$ assuming a line width of 20 km s$^{-1}$. Taking the existing interferometric HI image from the HALOGAS project of WSRT as reference, we are able to identify and characterize a significant excess of large-scale, low-density, and diffuse HI in the group. This diffuse HI extends for more than 120 kpc across, and accounts for more than one fourth of the total HI detected by FAST in and around the galaxy NGC 4631. In the region of the tidal tails, the diffuse HI has a typical column density above $10^{19.5}$ cm$^{-2}$, and is highly turbulent with a velocity dispersion around 50 km s$^{-1}$. It increases in column density with the dense HI, and tends to be associated with the kinematically ``hotter'' part of the dense HI. Through simple modeling, we find that the majority of the diffuse HI in the tail region is likely to induce cooling out of the hot IGM instead of evaporating or being radiatively ionized. Given these relations of gas in different phases, the diffuse HI may represent a condensing phase of the IGM. Active tidal interactions on-going and in the past may have produced the wide-spreading HI distribution, and triggered the gas accretion to NGC 4631 through the phase of the diffuse HI., Comment: 35 pages, 24 figures. Accepted for publication at ApJ. FEASTS site: http://kavli.pku.edu.cn/~jwang/FEASTS

We present the study of arcsecond scale radio continuum and OH line emission of a sample of known OH megamaser galaxies with $z \geq$ 0.15 using archival Very Large Array (VLA) data. And also the results of our pilot Five hundred meter aperture spherical radio telescope (FAST) observations of 12 of these OHM galaxies. The arcsecond-scale resolution images show that the OH emission is distributed in one compact structure and spatially associated with radio continuum emission. Furthermore, nearly all the fitted components are likely smaller than the beam size ($\sim$ 1.4"), which indicates that the broad OH line profiles of these sources originated from one masing region or that more components are distributed in sub-arcsec scales. The radio parameters, including brightness temperature, spectral index, and q-index, show no significant differences with the low-redshift OHM galaxies, which have significantly lower OH line luminosities. Because these parameters are indicators of the central power sources (AGN, starburst, or both), our results indicate that the presence of radio AGN in the nuclei may not be essential for the formation of OH emission. Over 1/3 of OHMs in this sample (6/17) show possible variable features likely caused by interstellar scintillation due to small angular sizes. We might underestimate this value because these sources are associated with this sample's highest OH line flux densities. Those with low OH line flux densities might need higher sensitivity observations to study the variabilities. These results support the compact nature of OH maser emission and a starburst origin for the OHMs in our selected sample., Comment: 25 pages,7 figures,accepted by A&A

Finance is a particularly difficult playground for deep reinforcement learning. However, establishing high-quality market environments and benchmarks for financial reinforcement learning is challenging due to three major factors, namely, low signal-to-noise ratio of financial data, survivorship bias of historical data, and model overfitting in the backtesting stage. In this paper, we present an openly accessible FinRL-Meta library that has been actively maintained by the AI4Finance community. First, following a DataOps paradigm, we will provide hundreds of market environments through an automatic pipeline that collects dynamic datasets from real-world markets and processes them into gym-style market environments. Second, we reproduce popular papers as stepping stones for users to design new trading strategies. We also deploy the library on cloud platforms so that users can visualize their own results and assess the relative performance via community-wise competitions. Third, FinRL-Meta provides tens of Jupyter/Python demos organized into a curriculum and a documentation website to serve the rapidly growing community. FinRL-Meta is available at: https://github.com/AI4Finance-Foundation/FinRL-Meta, Comment: NeurIPS 2022 Datasets and Benchmarks. 36th Conference on Neural Information Processing Systems Datasets and Benchmarks Track

Compact groups have high galaxy densities and low velocity dispersions, and their group members have experienced numerous and frequent interactions during their lifetimes. They provide a unique environment to study the evolution of galaxies. We examined the galaxies types and HI contents in groups to make a study on the galaxy evolution in compact groups. We used the group crossing time as an age indicator for galaxy groups. Our sample is derived from the Hickson Compact Group catalog. We obtained group morphology data from the Hyper-Leda database and the IR classification based on Wide-Field Infrared Survey Explorer (WISE) fluxes from Zucker et al. (2016). By cross-matching the latest released ALFALFA 100% HI source catalog and supplemented by data found in literature, we obtained 40 galaxy groups with HI data available. We confirmed that the weak correlation between HI mass fraction and group crossing time found by Ai & Zhu (2018) in SDSS groups also exists in compact groups. We also found that the group spiral galaxy fraction is correlated with the group crossing time, but the actively star-forming galaxy fraction is not correlated with the group crossing time. These results seem to fit with the hypothesis that the sequential acquisition of neighbors from surrounding larger-scale structures has affected the morphology transition and star formation efficiency in compact groups., Comment: 20pages, 6figures. Res. Astron. Astrophys (2022)

We report successful growth of millimeter-sized high quality single crystals of V$_3$S$_4$, a candidate topological semimetal belonging to a low-symmetry space group and consisting of only low atomic number elements. Using density functional theory calculations and angle-resolved photoemission spectroscopy, we show that the nonmagnetic phase of monoclinic V$_3$S$_4$ hosts type-II Dirac-like quasiparticles which opens a sizable gap due to spin orbit coupling, as well as theoretical multiple nodal lines that are eliminated also by spin orbit coupling. These results suggest that relativistic effects give rise to profound modifications of the topological properties even in compounds with low-weight elements., Comment: 19 Pages, 3 Figures. To be published in Journal of Alloys and Compounds

The challenge to fully exploit the potential of existing and upcoming scientific instruments like large single-dish radio telescopes is to process the collected massive data effectively and efficiently. As a "quasi 2D stencil computation" with the "Moore neighborhood pattern," gridding is the most computationally intensive step in data reduction pipeline for radio astronomy studies, enabling astronomers to create correct sky images for further analysis. However, the existing gridding frameworks can either only run on multi-core CPU architecture or do not support high-concurrency, multi-channel data gridding. Their performance is then limited, and there are emerging needs for innovative gridding frameworks to process data from large single-dish radio telescopes like the Five-hundred-meter Aperture Spherical Telescope (FAST). To address those challenges, we developed a High Efficient Gridding framework, HEGrid, by overcoming the above limitations. Specifically, we propose and construct the gridding pipeline in heterogeneous computing environments and achieve multi-pipeline concurrency for high performance multi-channel processing. Furthermore, we propose pipeline-based co-optimization to alleviate the potential negative performance impact of possible intra- and inter-pipeline low computation and I/O utilization, including component share-based redundancy elimination, thread-level data reuse and overlapping I/O and computation. Our experiments are based on both simulated datasets and actual FAST observational datasets. The results show that HEGrid outperforms other state-of-the-art gridding frameworks by up to 5.5x and has robust hardware portability, including AMD Radeon Instinct GPU and NVIDIA GPU., Comment: 12 pages, 17 figures

Recent advances in machine learning have significantly improved the understanding of source code data and achieved good performance on a number of downstream tasks. Open source repositories like GitHub enable this process with rich unlabeled code data. However, the lack of high quality labeled data has largely hindered the progress of several code related tasks, such as program translation, summarization, synthesis, and code search. This paper introduces XLCoST, Cross-Lingual Code SnippeT dataset, a new benchmark dataset for cross-lingual code intelligence. Our dataset contains fine-grained parallel data from 8 languages (7 commonly used programming languages and English), and supports 10 cross-lingual code tasks. To the best of our knowledge, it is the largest parallel dataset for source code both in terms of size and the number of languages. We also provide the performance of several state-of-the-art baseline models for each task. We believe this new dataset can be a valuable asset for the research community and facilitate the development and validation of new methods for cross-lingual code intelligence., Comment: 20 pages, 11 tables, 2 figures

There has been a recent surge of interest in automating software engineering tasks using deep learning. This paper addresses the problem of code generation, where the goal is to generate target code given source code in a different language or a natural language description. Most state-of-the-art deep learning models for code generation use training strategies primarily designed for natural language. However, understanding and generating code requires a more rigorous comprehension of the code syntax and semantics. With this motivation, we develop an encoder-decoder Transformer model where both the encoder and decoder are explicitly trained to recognize the syntax and data flow in the source and target codes, respectively. We not only make the encoder structure-aware by leveraging the source code's syntax tree and data flow graph, but we also support the decoder in preserving the syntax and data flow of the target code by introducing two novel auxiliary tasks: AST (Abstract Syntax Tree) paths prediction and data flow prediction. To the best of our knowledge, this is the first work to introduce a structure-aware Transformer decoder that models both syntax and data flow to enhance the quality of generated code. The proposed StructCoder model achieves state-of-the-art performance on code translation and text-to-code generation tasks in the CodeXGLUE benchmark, and improves over baselines of similar size on the APPS code generation benchmark. Our code is publicly available at https://github.com/reddy-lab-code-research/StructCoder/.

As first data release of a pilot extragalactic HI survey with Five-hundred-meter Aperture Spherical radio Telescope (FAST),we extracted 544 extragalaxies from three-dimensional(3D) spectral data to perform interactive searching and computing, yielding global parameters for these detections, extending redshift ranges of HI 21cm line up to z = 0.04 ,which covers part of the sky region in right ascension(R.A. or $\alpha$) and declination(Dec or $\delta$) range $00^{\rm h} 47^{\rm m}< \rm R.A.(J2000)<23^{\rm h}22^{\rm m}$ and $+24^{\circ}<\rm Dec.(J2000) <+43^{\circ}$ . The S/N of 544 HI detections are greater than 5 flagged with code 1 to 4 based on baseline qualities or RFI contamination. Besides, we find 16 of which without any counterparts in the existing galaxy catalogs. The catalog can give a guidence for the future HI observation with FAST., Comment: 23 pages,17 figures, 4 tables. Accepted for publication in the Research in Astronomy and Astrophysics