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Autonomous agents powered by large language models (LLMs) have attracted significant research interest. However, the open-source community faces many challenges in developing specialized models for agent tasks, driven by the scarcity of high-quality agent datasets and the absence of standard protocols in this area. We introduce and publicly release xLAM, a series of large action models designed for AI agent tasks. The xLAM series includes five models with both dense and mixture-of-expert architectures, ranging from 1B to 8x22B parameters, trained using a scalable, flexible pipeline that unifies, augments, and synthesizes diverse datasets to enhance AI agents' generalizability and performance across varied environments. Our experimental results demonstrate that xLAM consistently delivers exceptional performance across multiple agent ability benchmarks, notably securing the 1st position on the Berkeley Function-Calling Leaderboard, outperforming GPT-4, Claude-3, and many other models in terms of tool use. By releasing the xLAM series, we aim to advance the performance of open-source LLMs for autonomous AI agents, potentially accelerating progress and democratizing access to high-performance models for agent tasks. Models are available at https://huggingface.co/collections/Salesforce/xlam-models-65f00e2a0a63bbcd1c2dade4, Comment: Technical report for the Salesforce xLAM model series

We present a deep HI survey at L-band conducted with the Five-hundred-meter Aperture Spherical radio Telescope (FAST) over the COSMOS field. This survey is strategically designed to overlap with the MIGHTEE COSMOS field, aiming to combine the sensitivity of the FAST and high-resolution of the MeerKAT. We observed the field with FAST for approximately 11 hours covering $\sim$2 square degrees, and reduced the raw data to HI spectral cubes over the frequency range 1310-1420 MHz. The FAST-HI data reach a median 3$\sigma$ column density of $N_{\rm HI}\sim2\times10^{17}$ cm$^{-2}$ over a 5 km s$^{-1}$ channel width, allowing for studies of the distribution of HI gas in various environments, such as in galaxies, the Circum-Galactic Medium (CGM) and Intergalactic Medium (IGM). We visually searched the spectral cubes for HI sources, and found a total of 80 HI detections, of which 56 have been cross-matched with the MIGHTEE-HI catalogue. With the cross-matched sources, we compare their HI masses and find that the total HI mass fraction in the IGM and CGM surrounding the galaxy pairs is statistically higher than the HI fraction surrounding the isolated galaxies by a difference of 13$\pm$4%, indicating that the CGM and IGM associated with interacting systems are richer in neutral hydrogen compared to those around isolated galaxies in the local Universe. We also describe several FAST-MeerKAT synergy projects, highlighting the full potential of exploiting both single-dish and interferometric observations to study the distribution and evolution of the diffuse HI gas., Comment: 13 pages, 14 figures; Accepted for publication in MNRAS; Minor corrections made at proof stage

We analyze the properties of a rare population, the strongly bulge-dominated early-type galaxies (referred to as sBDEs) with significant HI gas, using the databases from the FAST All Sky HI survey (FASHI) and the Arecibo Legacy Fast ALFA (ALFALFA) survey. We select the sBDEs from the Sloan Digital Sky Survey (SDSS) and cross-match with the FASHI-ALFALFA combined HI sample, resulting in 104 HI-rich sBDEs. These sBDEs tend to have extremely high HI reservoirs, which is rare in previous studies such as ATLAS$^{3D}$. 70% of the selected sBDEs are classified as quiescent galaxies, even though they have a large HI reservoir. We study the properties of these sBDEs from five main aspects: stellar population, gas-phase metallicity, stacked HI spectra, environment, and spatially resolved MaNGA data. The majority of HI-rich sBDEs appear to show lower gas-phase metallicity and are located in significantly lower-density environments, suggesting an external origin for their HI gas. We find that star-forming sBDEs exhibit statistically higher star formation efficiency and slightly older stellar populations compared to normal star-forming galaxies, suggesting a recent star formation on Gyr-timescale. They also show narrower and more concentrated HI profiles compared to control star-forming galaxies, which may explain their higher star formation efficiency., Comment: 18 pages, 14 figures, 1 table. Accepted for publication in ApJ

We report on high-sensitivity neutral hydrogen observations toward the gas-rich interacting galaxies NGC 3395/3396 with the Five-hundred-meter Aperture Spherical radio Telescope (FAST). Compared to previous observations carried out by the Very Large Array (VLA) and the Westerbork Synthesis Radio Telescope (WSRT), a more extended HI envelope around this system has been detected. The total HI gas mass of the NGC 3395/3396 system is estimated to be 7.8 x 109 M. This value is 2.7 times more than that reported based on the VLA interferometric maps. Previous observations found a large HI tail extending to the south-west and a minor tail emerging from the north of this peculiar galaxy pair. Based on the high-sensitivity observations of FAST, an extended HI plume to the north-west and a gas plume to the north-east have been detected for the first time. Neutral hydrogen of the two smaller galaxies IC 2604 and IC 2608 on the south of the system have also been detected. We discuss the origins of these extra gas and possible tidal interactions between these galaxies. NGC 3395/3396's most prominent tidal feature, the south-west tail combined with the new detected north-west plume behaves like a large ring. We suggest the ring might be formed by the previous fly-by interaction between NGC 3395 and NGC 3396 which happened 500 Myr ago. Our study shows that high-sensitivity HI observations are important in revealing low column density gas, which is crucial to a deeper understanding of this interacting system.

The FAST All Sky HI survey (FASHI) is broader in frequency band and deeper in detection sensitivity than most of previous HI surveys. FASHI is designed to cover the entire sky observable by the Five-hundred-meter Aperture Spherical radio Telescope (FAST). Based on the FASHI data, we perform a blind survey of 21cm HI absorption galaxies at redshift $z<0.09$ over an area of about 10000 square degrees. We detected 51 HI absorbers, including 21 previously known and 30 new ones, with 8 sources having no optical spectroscopic redshift. The probability of occurrence for HI absorbers in all HI galaxies is 1/1078. The radio flux densities of the FASHI absorbers are mainly concentrated in the range of $S_{\rm 1.4GHz}=10\sim100$ mJy, but even as low as $2.6\pm0.4$mJy. The number of redshifted absorbers is slightly higher than the number of blueshifted absorbers. Such results would provide some important clues for future flux-selected HI absorber surveys. Therefore, FAST has significantly improved the capabilities and performance for HI absorption observations and provided a true blind survey of 21cm HI absorption galaxies for such studies., Comment: 32 pages, 7 figures, 2 tables, submitted to ApJS in 05/24/2024, Comments are welcome

We present an extragalactic HI 21-cm absorption lines catalog from a blind search at z $\leq$ 0.35, using drift-scan data collected in 1616.9 hours by the ongoing Commensal Radio Astronomy FasT Survey (CRAFTS) and FAST All Sky HI Survey (FASHI), which spans a sky area of 7456.8 deg$^{2}$ and covers 84,533 radio sources with a flux density greater than 12 mJy. 14 previously identified HI absorbers and 20 newly discovered HI absorbers were detected, comprising 14 associated systems, 11 intervening systems, and 9 systems with undetermined classifications. We fit HI profiles with multi-component Gaussian functions and calculate the redshift, width, flux density, optical depth, and HI column densities for each source. Through spectral stacking, the mean peak optical path, mean velocity-integrated optical path $\langle \tau\rangle$, mean FWHM and mean HI column density $\langle$ N$_{HI}\rangle$ are measured to be 0.46 and 0.34; 25.85 km/s and 4.62 km/s; 39.80 km/s and 8.95 km/s; 0.470 and 0.085 T$_{s} \times$ 10$^{20}$cm$^{-2}$K$^{-1}$, for the associated and intervening samples, respectively. Statistical analysis also reveals that associated systems tend to be hosted by red (g$-$r$>$0.7) galaxies at lower redshifts, whereas galaxies hosting intervening HI absorption are typically found at higher redshifts and are of a bluer (g$-$r$\leq$0.7) type. Additionally, it has been demonstrated that associated HI 21-cm absorptions connected to compact radio sources display higher N$_{HI}$ values compared to those linked with extended radio sources., Comment: 28 pages, 39 figures, 5 tables

The advancement of function-calling agent models requires diverse, reliable, and high-quality datasets. This paper presents APIGen, an automated data generation pipeline designed to synthesize verifiable high-quality datasets for function-calling applications. We leverage APIGen and collect 3,673 executable APIs across 21 different categories to generate diverse function-calling datasets in a scalable and structured manner. Each data in our dataset is verified through three hierarchical stages: format checking, actual function executions, and semantic verification, ensuring its reliability and correctness. We demonstrate that models trained with our curated datasets, even with only 7B parameters, can achieve state-of-the-art performance on the Berkeley Function-Calling Benchmark, outperforming multiple GPT-4 models. Moreover, our 1B model achieves exceptional performance, surpassing GPT-3.5-Turbo and Claude-3 Haiku. We release a dataset containing 60,000 high-quality entries, aiming to advance the field of function-calling agent domains. The dataset is available on Huggingface: https://huggingface.co/datasets/Salesforce/xlam-function-calling-60k and the project homepage: https://apigen-pipeline.github.io/

The deployment of Large Language Models (LLMs) and Large Multimodal Models (LMMs) on mobile devices has gained significant attention due to the benefits of enhanced privacy, stability, and personalization. However, the hardware constraints of mobile devices necessitate the use of models with fewer parameters and model compression techniques like quantization. Currently, there is limited understanding of quantization's impact on various task performances, including LLM tasks, LMM tasks, and, critically, trust and safety. There is a lack of adequate tools for systematically testing these models on mobile devices. To address these gaps, we introduce MobileAIBench, a comprehensive benchmarking framework for evaluating mobile-optimized LLMs and LMMs. MobileAIBench assesses models across different sizes, quantization levels, and tasks, measuring latency and resource consumption on real devices. Our two-part open-source framework includes a library for running evaluations on desktops and an iOS app for on-device latency and hardware utilization measurements. Our thorough analysis aims to accelerate mobile AI research and deployment by providing insights into the performance and feasibility of deploying LLMs and LMMs on mobile platforms.

Obstructed atomic insulator is recently proposed as an unconventional material, in which electric charge centers localized at sites away from the atoms. A half-filling surface state would emerge at specific interfaces cutting through these charge centers and avoid intersecting any atoms. In this article, we utilized angle-resolved photoemission spectroscopy and density functional theory calculations to study one of the obstructed atomic insulator candidates, NiP$_2$. A floating surface state with large effective mass that is isolated from all bulk states is resolved on the (100) cleavage plane, distinct from previously reported surface states in obstructed atomic insulators that are merged into bulk bands. Density functional theory calculation results elucidate that this floating surface state is originated from the obstructed Wannier charge centers, albeit underwent surface reconstruction that splits the half-filled obstructed surface state. Our findings not only shed lights on the spectroscopy study of obstructed atomic insulators and obstructed surface states, but also provide possible route for development of new catalysts., Comment: 21 pages, 5 figures

The scarcity of non-English data limits the development of non-English large language models (LLMs). Transforming English-centric LLMs to non-English has been identified as an effective and resource-efficient method. Previous works start from base LLMs and perform knowledge distillation (KD) with data generated by stronger LLMs, e.g. GPT-4. Compared to base LLMs, chat LLMs are further optimized for advanced abilities, e.g. multi-turn conversation and human preference alignment, and thus more powerful in both helpfulness and safety. However, transforming a chat LLM involves two critical issues: (1) How can we effectively transfer advanced abilities without their supervised data? (2) How can we prevent the original knowledge from catastrophic forgetting during transformation? We target these issues by introducing a simple framework called TransLLM. For the first issue, TransLLM divides the transfer problem into some common sub-tasks with the translation chain-of-thought, which uses the translation as the bridge between English and non-English step-by-step. We further enhance the performance of sub-tasks with publicly available data. For the second issue, we propose a method comprising two synergistic components: low-rank adaptation for training to maintain the original LLM parameters, and recovery KD, which utilizes data generated by the chat LLM itself to recover the original knowledge from the frozen parameters. In the experiments, we transform the LLaMA-2-chat-7B to the Thai language. Our method, using only single-turn data, outperforms strong baselines and ChatGPT on multi-turn benchmark MT-bench. Furthermore, our method, without safety data, rejects more harmful queries of safety benchmark AdvBench than both ChatGPT and GPT-4.

Recently, unconventional antiferromagnets that enable the splitting of electronic spins have been theoretically proposed and experimentally realized, where the magnetic sublattices containing moments pointing at different directions are connected by a novel set of symmetries. Such spin splitting (SS) is substantial, $k$-dependent, and independent of the spin-orbit coupling strength, making these magnets promising materials for antiferromagnetic spintronics. Here, combined with angle-resolved photoemission spectroscopy (ARPES) and density functional theory (DFT) calculations, we perform a systematic study on CrSb, a metallic spin-split antiferromagnet candidate with $T_N$ = 703 K. Our data reveals the electronic structure of CrSb along both out-of-plane and in-plane momentum directions, which renders anisotropic $k$-dependent SS and agrees well with the calculational results. The magnitude of such SS reaches up to at least 0.8 eV at non-high-symmetry momentum points, which is significantly higher than the largest known SOC-induced SS. This compound expands the choice of materials in the field of antiferromagnetic spintronics and is likely to stimulate subsequent investigations of high-efficiency spintronic devices that are functional at room temperature., Comment: 14 pages, 4 figures

We report the discovery of eight optical counterparts of ALFALFA extragalactic objects from DECaLS, five of which are discovered for the first time. These objects were flagged as HI emission sources with no optical counterparts in SDSS before. Multi-band data reveal their unusual physical properties. They are faint and blue ($g-r=-0.35\sim0.55$), with quite low surface brightness ($\mu_{\rm g,peak}=24.88\sim26.41\,{\rm mag}/{\rm arcsec}^2$), irregular morphologies, low stellar masses ($log_{10}(M_{*}/M_\odot)=5.27\sim7.15$), low star formation rates ($SFR=0.21\sim9.24\times10^{-3}\,{M_\odot}\,{\rm yr}^{-1}$), and remarkably high HI-to-stellar mass ratios ($log_{10}(M_{\rm HI}/M_{*}) = 1.72\sim3.22$, except AGC\,215415). They deviate from the scaling relations between HI and optical properties defined by the ALFALFA sample and the baryonic Tully-Fisher relation. They agree well with the main sequence of star-forming galaxies but exhibit low star-forming efficiency. Based on their physical properties and environments, we speculate that six of these objects may have originated from tidal processes, while the remaining two appear to have isolated origins. They may have had a relatively calm evolutionary history and only begun to form stars recently., Comment: 32 pages, 11 figures, accepted by the Astrophysical Journal

The Five-hundred-meter Aperture Spherical radio Telescope (FAST) has the largest aperture and a 19-beam L-band receiver, making it powerful for investigating the neutral hydrogen atomic gas (HI) in the universe. We present HiFAST (https://hifast.readthedocs.io), a dedicated, modular, and self-contained calibration and imaging pipeline for processing the HI data of FAST. The pipeline consists of frequency-dependent noise diode calibration, baseline fitting, standing wave removal using an FFT-based method, flux density calibration, stray radiation correction, and gridding to produce data cubes. These modules can be combined as needed to process the data from most FAST observation modes: tracking, drift scanning, On-The-Fly mapping, and most of their variants. With HiFAST, the RMS noises of the calibrated spectra from all 19 beams were only slightly (~ 5%) higher than the theoretical expectation. The results for the extended source M33 and the point sources are consistent with the results from Arecibo. The moment maps (0,1 and 2) of M33 agree well with the results from the Arecibo Galaxy Environment Survey (AGES) with a fractional difference of less than 10%. For a common sample of 221 sources with signal-to-noise ratio S/N >10 from the Arecibo Legacy Fast ALFA (ALFALFA) survey, the mean value of fractional difference in the integrated flux density, $S_{\mathrm{int}}$, between the two datasets is approximately 0.005 %, with a dispersion of 15.4%. Further checks on the integrated flux density of 23 sources with seven observations indicate that the variance in the flux density of the source with luminous objects ($S_\mathrm{int}$ $ > 2.5$ Jy km s$^{-1}$) is less than 5%. Our tests suggest that the FAST telescope, with the efficient, precise, and user-friendly pipeline HiFAST, will yield numerous significant scientific findings in the investigation of the HI in the universe., Comment: Accepted by SCPMA. 21 pages, 14 figures. The pipeline is accessible at https://hifast.readthedocs.io

The FAST All Sky HI survey (FASHI) is broader in frequency band and sky volume, and deeper in detection sensitivity than the Arecibo Legacy Fast ALFA survey (ALFALFA). To efficiently expand the sample of OH megamasers (OHMs), whose strongest line has a rest frequency of 1667.35903 MHz, we directly matched the IRAS Point Source Catalog Redshift (PSCz) catalog with the corresponding FASHI data cube. From 145 PSCz sources already covered by FASHI, we obtained 27 OHMs with a detection rate of 18.6%, including 9 previously known and 18 new ones, within a redshift range of $0.14314\lesssim z_{\rm OH} \lesssim0.27656$. We also measured the hyperfine ratio of nine OHMs between the 1667 and 1665 MHz lines. The ratio ranges from 1.32 to 15.22, with an average of $R_{1667:1665}=4.74$. In a fit to the $L_{\rm OH}$ vs. $L_{\rm FIR}$ relation, we have ${\rm log}L_{\rm OH}= (1.57\pm0.10){\rm log}L_{\rm FIR}-(15.80\pm1.19)$, which is almost the same as derived from previous observations. As expected, since the OHM sample was selected by cross-correlation with the IRAS-selected PSCz, our detected OHMs are [ultra]luminous infrared galaxies ([U]LIRGs). However, not all [U]LIRGs have detectable OH emission, suggesting that the OH emission may be triggered within a specific stage of the merger or can only be seen in specific orientations. In general, FAST, with its 19-beam array and UWB receiver, will be a powerful tool for observing more OHMs and unraveling their mystery in the future., Comment: 21 pages, 6 figures. Comments are welcome

In this paper, we introduce InfiAgent-DABench, the first benchmark specifically designed to evaluate LLM-based agents on data analysis tasks. These tasks require agents to end-to-end solving complex tasks by interacting with an execution environment. This benchmark contains DAEval, a dataset consisting of 257 data analysis questions derived from 52 CSV files, and an agent framework which incorporates LLMs to serve as data analysis agents for both serving and evaluation. Since data analysis questions are often open-ended and hard to evaluate without human supervision, we adopt a format-prompting technique to convert each question into a closed-form format so that they can be automatically evaluated. Our extensive benchmarking of 34 LLMs uncovers the current challenges encountered in data analysis tasks. In addition, building on top of our agent framework, we develop a specialized agent, DAAgent, which surpasses GPT-3.5 by 3.9% on DABench. Evaluation datasets and toolkits for InfiAgent-DABench are released at https://github.com/InfiAgent/InfiAgent ., Comment: 27 pages, 7 figures, work in progress

Instruction tuning is crucial for enabling Language Learning Models (LLMs) in responding to human instructions. The quality of instruction pairs used for tuning greatly affects the performance of LLMs. However, the manual creation of high-quality instruction datasets is costly, leading to the adoption of automatic generation of instruction pairs by LLMs as a popular alternative. To ensure the high quality of LLM-generated instruction datasets, several approaches have been proposed. Nevertheless, existing methods either compromise dataset integrity by filtering a large proportion of samples, or are unsuitable for industrial applications. In this paper, instead of discarding low-quality samples, we propose CoachLM, a novel approach to enhance the quality of instruction datasets through automatic revisions on samples in the dataset. CoachLM is trained from the samples revised by human experts and significantly increases the proportion of high-quality samples in the dataset from 17.7% to 78.9%. The effectiveness of CoachLM is further assessed on various real-world instruction test sets. The results show that CoachLM improves the instruction-following capabilities of the instruction-tuned LLM by an average of 29.9%, which even surpasses larger LLMs with nearly twice the number of parameters. Furthermore, CoachLM is successfully deployed in a data management system for LLMs at Huawei, resulting in an efficiency improvement of up to 20% in the cleaning of 40k real-world instruction pairs. We release various assets of CoachLM, including the training data, code and test set (https://github.com/lunyiliu/CoachLM)., Comment: Accepted by ICDE 2024

Based on the atomic-hydrogen (HI) observations using the Five-hundred-meter Aperture Spherical radio Telescope (FAST), we present a detailed study of the gas-rich massive S0 galaxy NGC 1023 in a nearby galaxy group. The presence of an HI extended warped disk in NGC 1023 indicates that this S0 galaxy originated from a spiral galaxy. The data also suggest that NGC 1023 is interacting with four dwarf galaxies. In particular, one of the largest dwarf galaxies has fallen into the gas disk of NGC 1023, forming a rare bright-dark galaxy pair with a large gas clump. This clump shows the signature of a galaxy but has no optical counterpart, implying that it is a newly formed starless galaxy. Our results firstly suggest that a massive S0 galaxy in a galaxy group can form via the morphological transformation from a spiral under the joint action of multiple tidal interactions., Comment: 13 pages, 8 figures, Accepted for publication in the ApJ Letters

Amid growing global mental health concerns, particularly among vulnerable groups, natural language processing offers a tremendous potential for early detection and intervention of people's mental disorders via analyzing their postings and discussions on social media platforms. However, ultra-sparse training data, often due to vast vocabularies and low-frequency words, hinders the analysis accuracy. Multi-labeling and Co-occurrences of symptoms may also blur the boundaries in distinguishing similar/co-related disorders. To address these issues, we propose a novel semantic feature preprocessing technique with a three-folded structure: 1) mitigating the feature sparsity with a weak classifier, 2) adaptive feature dimension with modulus loops, and 3) deep-mining and extending features among the contexts. With enhanced semantic features, we train a machine learning model to predict and classify mental disorders. We utilize the Reddit Mental Health Dataset 2022 to examine conditions such as Anxiety, Borderline Personality Disorder (BPD), and Bipolar-Disorder (BD) and present solutions to the data sparsity challenge, highlighted by 99.81% non-zero elements. After applying our preprocessing technique, the feature sparsity decreases to 85.4%. Overall, our methods, when compared to seven benchmark models, demonstrate significant performance improvements: 8.0% in accuracy, 0.069 in precision, 0.093 in recall, 0.102 in F1 score, and 0.059 in AUC. This research provides foundational insights for mental health prediction and monitoring, providing innovative solutions to navigate challenges associated with ultra-sparse data feature and intricate multi-label classification in the domain of mental health analysis.

In this letter, we report the discovery of a fast neutral hydrogen outflow in SDSS J145239.38+062738.0, a merging radio galaxy containing an optical type I active galactic nuclei (AGN). This discovery was made through observations conducted by the Five-hundred-meter Aperture Spherical radio Telescope (FAST) using redshifted 21-cm absorption. The outflow exhibits a blueshifted velocity likely up to $\sim-1000\,\rm km\,s^{-1}$ with respect to the systemic velocity of the host galaxy with an absorption strength of $\sim -0.6\,\rm mJy\,beam^{-1}$ corresponding to an optical depth of 0.002 at $v=-500\,\rm km\,s^{-1}$. The mass outflow rate ranges between $2.8\times10^{-2}$ and $3.6\, \rm M_\odot \, yr^{-1}$, implying an energy outflow rate ranging between $4.2\times10^{39}$ and $9.7\times10^{40}\rm\,erg\,s^{-1}$, assuming 100 K $

This study presents results on detecting neutral atomic hydrogen (HI) 21cm absorption in the spectrum of PKS1413+135 at redshift $z=0.24670041$. The observation was conducted by FAST, with a spectral resolution of 10 Hz, using 10 minutes of observing time. The global spectral profile is examined by modeling the absorption line using a single Gaussian function with a resolution of 10 kHz within a 2 MHz bandwidth. The goal is to determine the rate of the latest cosmic acceleration by directly measuring redshift evolution of H I 21 cm absorption line with Hubble flow towards a same background Quasar over a decade or longer time span. This will serve as a detectable signal generated by the accelerated expansion of the Universe at redshift $z < 1$, referred to as redshift drift $\dot{z}$ or the SL effect. The measured HI gas column density in this DLA system is approximately equivalent to the initial observation value, considering uncertainties of the spin temperature of a spiral host galaxy. The high signal-to-noise ratio of 57, obtained at a 10 kHz resolution, strongly supports the feasibility of using the H I 21 cm absorption line in DLA systems to accurately measure the redshift drift rate at a precision level of around $10^{-10}$ per decade., Comment: 16 pages,6 figures, 2 tables, Accepted for publication by RAA

We report the first high-sensitivity HI observation toward the spiral galaxy M94 with the Five-hundred-meter Aperture Spherical radio Telescope (FAST). From these observations, we discovered that M94 has a very extended HI disk, twice larger than that observed by THINGS, which is accompanied by an HI filament and seven HVCs (high velocity clouds) at different distances. The projected distances of these clouds and filament are less than 50 kpc from the galactic center. We measured a total integrated flux (including all clouds/filament) of 127.3 ($\pm$1) Jy km s$^{-1}$, corresponding to a H I mass of (6.51$\pm$0.06)$\times$10$^{8}$M$_{\odot}$, which is 63.0% more than that observed by THINGS. By comparing numerical simulations with the HI maps and the optical morphology of M94, we suggest that M94 is likely a remnant of a major merger of two galaxies, and the HVCs and HI filament could be the tidal features originated from the first collision of the merger happened about 5 Gyr ago. Furthermore, we found a seemingly isolated HI cloud at a projection distance of 109 kpc without any optical counterpart detected. We discussed the possibilities of the origin of this cloud, such as dark dwarf galaxy and RELHIC (REionization-Limited HI Cloud). Our results demonstrate that high-sensitivity and wide-field HI imaging is important in revealing the diffuse cold gas structures and tidal debris which is crucial to understanding the dynamical evolution of galaxies., Comment: 14 pages, 8 figures

We have obtained the polarization data cube of the VRO 42.05.01 supernova remnant at 1240 MHz using the Five-hundred-meter Aperture Spherical radio Telescope (FAST). Three-dimensional Faraday Synthesis is applied to the FAST data to derive the Faraday depth spectrum. The peak Faraday depth map shows a large area of enhanced foreground RM of ~60 rad m-2 extending along the remnant's "wing" section, which coincides with a large-scale HI shell at -20 km/s. The two depolarization patches within the "wing" region with RM of 97 rad m-2 and 55 rad m-2 coincide with two HI structures in the HI shell. Faraday screen model fitting on the Canadian Galactic Plane Survey (CGPS) 1420 MHz full-scale polarization data reveals a distance of 0.7-0.8d_{SNR} in front of the SNR with enhanced regular magnetic field there. The highly piled-up magnetic field indicates that the HI shell at -20 km/s could originate from an old evolved SNR., Comment: 9 pages, 8 figures, accepted by ApJ

We report the discovery of a 100 kpc HI tail in the merging galaxy pair NGC 4490/85 detected by the Five-Hundred-meter Aperture Spherical radio Telescope (FAST). The tidal tails extended in both the south and north directions, and they are much longer than that reported previously based on the VLA interferometric maps. The NGC 4490/85 is surrounded by a large gas envelope, and a starburst low metallicity dwarf galaxy MAPS 1231+42 is found to be connected with the gas envelope, indicating that galaxy interaction trigged the intense star formation in it. Based on the fact that the metallicity in MAPS 1231+42 is one order of magnitude lower than that in the two disks of NGC 4490 and NGC 4485, we speculate that the gas near this galaxy should be primordial and could be due to gas inflow from the circum-galactic medium (CGM). We also found a collimated gas component pointing at a nearby dwarf galaxy KK 149, suggesting that this galaxy might also be interacting with the NGC 4490 pair. We discuss the possible origin of the long tidal tails and the extended gas envelope in this merging system based on the new data from FAST., Comment: 10 pages, 8 figures, 1 table.Accepted by MNRAS. The raw data used in the article will be published on the FAST website: https://fast.bao.ac.cn. The PID is N2021_4. Please contact the author (liuyao@nao.cas.cn, mz@nao.cas.cn) for processed data

The financial market is a particularly challenging playground for deep reinforcement learning due to its unique feature of dynamic datasets. Building high-quality market environments for training financial reinforcement learning (FinRL) agents is difficult due to major factors such as the low signal-to-noise ratio of financial data, survivorship bias of historical data, and model overfitting. In this paper, we present FinRL-Meta, a data-centric and openly accessible library that processes dynamic datasets from real-world markets into gym-style market environments and has been actively maintained by the AI4Finance community. First, following a DataOps paradigm, we provide hundreds of market environments through an automatic data curation pipeline. Second, we provide homegrown examples and reproduce popular research 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, we provide dozens of Jupyter/Python demos organized into a curriculum and a documentation website to serve the rapidly growing community. The open-source codes for the data curation pipeline are available at https://github.com/AI4Finance-Foundation/FinRL-Meta, Comment: 49 pages, 15 figures. arXiv admin note: substantial text overlap with arXiv:2211.03107

The Five-hundred-meter Aperture Spherical radio Telescope (FAST) has been running for several years. A new Ultra-Wide Bandwidth (UWB) receiver, simultaneously covering 500-3300 MHz, has been mounted in the FAST feed cabin and passed a series of observational tests. The whole UWB band is separated into four independent bands. Each band has 1048576 channels in total, resulted in a spectral resolution of 1 kHz. At 500-3300 MHz, the antenna gain is around 14.3-7.7 K/Jy, the aperture efficiency is around 0.56-0.30, the system temperature is around 88-130 K, and the HPBW is around 7.6-1.6 arcmin. The measured standard deviation of pointing accuracy is better than ~7.9 arcsec, when zenith angle (ZA) is within 26.4deg. The sensitivity and stability of the UWB receiver are confirmed to satisfy expectation by spectral observations, e.g., HI and OH. The FAST UWB receiver already has a good performance for taking sensitive observations in various scientific goals., Comment: 11 pages, 7 figures, 2 tables, published in Research in Astronomy and Astrophysics

We investigate external and internal dynamics of a two-level atom strongly coupled to a weakly pumped nanophotonic cavity. We calculate the dipole force, friction force, and stochastic force due to the cavity pump field, and show that a three-dimensional cooling region exists near the surface of a cavity. Using a two-color evanescent field trap as an example, we perform three-dimensional Monte-Carlo simulations to demonstrate efficient loading of single atoms into a trap by momentum diffusion, and the stability of cavity cooling near the trap center. Our analyses show that cavity cooling can be a promising method for directly loading cold atoms from free-space into a surface micro-trap. We further discuss the impact of pump intensity on atom trapping and loading efficiency., Comment: 14 pages, 11 figures, 1 table