arXiv subjects

Chao Liu

Publications and source records attributed to Chao Liu.

At least 325 records · Page 18Linked to original sources

arXiv2020

Coherent Optical Memory Baesd on A Laser-written On-chip Waveguide

Quantum memory is the core device for the construction of large-scale quantum networks. For scalable and convenient practical applications, integrated optical memories, especially on-chip optical memories, are crucial requirements because they can be easily integrated with other on-chip devices. Here, we report the coherent optical memory based on a type-IV waveguide fabricated on the surface of a rare-earth ion-doped crystal (i.e. $\mathrm{Eu^{3+}}$:$\mathrm{Y_2SiO_5}$). The properties of the optical transition ($\mathrm{{^7}F{_0}\rightarrow{^5}D{_0}}$) of the $\mathrm{Eu^{3+}}$ ions inside the surface waveguide are well preserved compared to those of the bulk crystal. Spin-wave atomic frequency comb storage is demonstrated inside the type-IV waveguide. The reliability of this device is confirmed by the high interference visibility of ${97\pm 1\%}$ between the retrieval pulse and the reference pulse. The developed on-chip optical memory paves the way towards integrated quantum nodes.

quant-ph↗

arXiv2020

Understanding the velocity distribution of the Galactic Bulge with APOGEE and Gaia

We revisit the stellar velocity distribution in the Galactic bulge/bar region with APOGEE DR16 and {\it Gaia} DR2, focusing in particular on the possible high-velocity (HV) peaks and their physical origin. We fit the velocity distributions with two different models, namely with Gauss-Hermite polynomial and Gaussian mixture model (GMM). The result of the fit using Gauss-Hermite polynomials reveals a positive correlation between the mean velocity ($\bar{V}$) and the "skewness" ($h_{3}$) of the velocity distribution, possibly caused by the Galactic bar. The $n=2$ GMM fitting reveals a symmetric longitudinal trend of $|μ_{2}|$ and $σ_{2}$ (the mean velocity and the standard deviation of the secondary component), which is inconsistent to the $x_{2}$ orbital family predictions. Cold secondary peaks could be seen at $|l|\sim6^\circ$. However, with the additional tangential information from {\it Gaia}, we find that the HV stars in the bulge show similar patterns in the radial-tangential velocity distribution ($V_{\rm R}-V_{\rm T}$), regardless of the existence of a distinct cold HV peak. The observed $V_{\rm R}-V_{\rm T}$ (or $V_{\rm GSR}-μ_{l}$) distributions are consistent with the predictions of a simple MW bar model. The chemical abundances and ages inferred from ASPCAP and CANNON suggest that the HV stars in the bulge/bar are generally as old as, if not older than, the other stars in the bulge/bar region.

astro-ph.GA↗

arXiv2020

Characterising the Performance of High-Speed Data Converters for RFSoC-based Radio Astronomy Receivers

RF system-on-chip (RFSoC) devices provide the potential for implementing a complete radio astronomy receiver on a single board, but performance of the integrated analogue-to-digital converters is critical. We have evaluated the performance of the data converters in the Xilinx ZU28DR RFSoC, which are 12-bit, 8-fold interleaved converters with a maximum sample speed of 4.096 Giga-sample per second (GSPS). We measured the spurious-free dynamic range (SFDR), signal-to-noise and distortion (SINAD), effective number of bits (ENOB), intermodulation distortion (IMD) and cross-talk between adjacent channels over the bandwidth of 2.048 GHz. We both captured data for off-line analysis with floating-point arithmetic, and implemented a real-time integer arithmetic spectrometer on the RFSoC. The performance of the ADCs is sufficient for radio astronomy applications and close to the vendor specifications in most of the scenarios. We have carried out spectral integrations of up to 100 s and stability tests over tens of hours and find thermal noise-limited performance over these timescales.

astro-ph.IM↗

arXiv2020

Opportunities and Challenges in Code Search Tools

Code search is a core software engineering task. Effective code search tools can help developers substantially improve their software development efficiency and effectiveness. In recent years, many code search studies have leveraged different techniques, such as deep learning and information retrieval approaches, to retrieve expected code from a large-scale codebase. However, there is a lack of a comprehensive comparative summary of existing code search approaches. To understand the research trends in existing code search studies, we systematically reviewed 81 relevant studies. We investigated the publication trends of code search studies, analyzed key components, such as codebase, query, and modeling technique used to build code search tools, and classified existing tools into focusing on supporting seven different search tasks. Based on our findings, we identified a set of outstanding challenges in existing studies and a research roadmap for future code search research.

cs.SE↗

arXiv2020

FeatherTTS: Robust and Efficient attention based Neural TTS

Attention based neural TTS is elegant speech synthesis pipeline and has shown a powerful ability to generate natural speech. However, it is still not robust enough to meet the stability requirements for industrial products. Besides, it suffers from slow inference speed owning to the autoregressive generation process. In this work, we propose FeatherTTS, a robust and efficient attention-based neural TTS system. Firstly, we propose a novel Gaussian attention which utilizes interpretability of Gaussian attention and the strict monotonic property in TTS. By this method, we replace the commonly used stop token prediction architecture with attentive stop prediction. Secondly, we apply block sparsity on the autoregressive decoder to speed up speech synthesis. The experimental results show that our proposed FeatherTTS not only nearly eliminates the problem of word skipping, repeating in particularly hard texts and keep the naturalness of generated speech, but also speeds up acoustic feature generation by 3.5 times over Tacotron. Overall, the proposed FeatherTTS can be $35$x faster than real-time on a single CPU.

eess.AS↗

arXiv2020

Detection of the LMC-induced sloshing of the Galactic halo

A wealth of recent studies have shown that the LMC is likely massive, with a halo mass $>10^{11} M_\odot$. One consequence of having such a nearby and massive neighbour is that the inner Milky Way is expected to be accelerated with respect to our Galaxy's outskirts (beyond $\sim 30$ kpc). In this work we compile a sample of $\sim 500$ stars with radial velocities in the distant stellar halo, $r_{\rm GC}> 50$ kpc, to test this hypothesis. These stars span a large fraction of the sky and thus give a global view of the stellar halo. We find that stars in the Southern hemisphere are on average blueshifted, while stars in the North are redshifted, consistent with the expected, mostly downwards acceleration of the inner halo due to the LMC. We compare these results with simulations and find the signal is consistent with the infall of a $1.5\times10^{11} M_\odot$ LMC. We cross-match our stellar sample with \textit{Gaia} DR2 and find that the mean proper motions are not yet precise enough to discern the LMC's effect. Our results show that the outer Milky Way is significantly out of equilibrium and that the LMC has a substantial effect on our Galaxy.

astro-ph.GA↗

arXiv2020

A QP-adaptive Mechanism for CNN-based Filter in Video Coding

Convolutional neural network (CNN)-based filters have achieved great success in video coding. However, in most previous works, individual models are needed for each quantization parameter (QP) band. This paper presents a generic method to help an arbitrary CNN-filter handle different quantization noise. We model the quantization noise problem and implement a feasible solution on CNN, which introduces the quantization step (Qstep) into the convolution. When the quantization noise increases, the ability of the CNN-filter to suppress noise improves accordingly. This method can be used directly to replace the (vanilla) convolution layer in any existing CNN-filters. By using only 25% of the parameters, the proposed method achieves better performance than using multiple models with VTM-6.3 anchor. Besides, an additional BD-rate reduction of 0.2% is achieved by our proposed method for chroma components.

eess.IV↗

arXiv2020

A Convolutional Neural Network-Based Low Complexity Filter

Convolutional Neural Network (CNN)-based filters have achieved significant performance in video artifacts reduction. However, the high complexity of existing methods makes it difficult to be applied in real usage. In this paper, a CNN-based low complexity filter is proposed. We utilize depth separable convolution (DSC) merged with the batch normalization (BN) as the backbone of our proposed CNN-based network. Besides, a weight initialization method is proposed to enhance the training performance. To solve the well known over smoothing problem for the inter frames, a frame-level residual mapping (RM) is presented. We analyze some of the mainstream methods like frame-level and block-level based filters quantitatively and build our CNN-based filter with frame-level control to avoid the extra complexity and artificial boundaries caused by block-level control. In addition, a novel module called RM is designed to restore the distortion from the learned residuals. As a result, we can effectively improve the generalization ability of the learning-based filter and reach an adaptive filtering effect. Moreover, this module is flexible and can be combined with other learning-based filters. The experimental results show that our proposed method achieves significant BD-rate reduction than H.265/HEVC. It achieves about 1.2% BD-rate reduction and 79.1% decrease in FLOPs than VR-CNN. Finally, the measurement on H.266/VVC and ablation studies are also conducted to ensure the effectiveness of the proposed method.

eess.IV↗

arXiv2020

Reverse-engineering Bar Charts Using Neural Networks

Reverse-engineering bar charts extracts textual and numeric information from the visual representations of bar charts to support application scenarios that require the underlying information. In this paper, we propose a neural network-based method for reverse-engineering bar charts. We adopt a neural network-based object detection model to simultaneously localize and classify textual information. This approach improves the efficiency of textual information extraction. We design an encoder-decoder framework that integrates convolutional and recurrent neural networks to extract numeric information. We further introduce an attention mechanism into the framework to achieve high accuracy and robustness. Synthetic and real-world datasets are used to evaluate the effectiveness of the method. To the best of our knowledge, this work takes the lead in constructing a complete neural network-based method of reverse-engineering bar charts.

cs.CV↗

arXiv2020

The extended Gaia-PS1-SDSS (GPS1+) proper motion catalog

The GPS1 catalog was released in 2017. It delivered precise proper motions for around 350 million sources across three-fourths of the sky down to a magnitude of $r\sim20$\,mag. In this study, we present GPS1+ the extension GPS1 catalog down to $r\sim22.5$\,mag, based on {\it Gaia} DR2, PS1, SDSS and 2MASS astrometry. The GPS1+ totally provides proper motions for $\sim$400 million sources with a characteristic systematic error of less than 0.1\masyr. This catalog is divided into two sub-samples, i.e., the primary and secondary parts. The primary $\sim$264 million sources have either or both of the {\it Gaia} and SDSS astrometry, with a typical precision of 2.0-5.0 \masyr. In this part, $\sim$160 million sources have {\it Gaia} proper motions, we provide another new proper motion for each of them by building a Bayesian model. Relative to {\it Gaia}'s values, the precision is improved by $\sim$0.1\,dex on average at the faint end; $\sim$50 million sources are the objects whose proper motions are missing in {\it Gaia} DR2, we provide their proper motion with a precision of $\sim$4.5\masyr; the remaining $\sim$54 million faint sources are beyond {\it Gaia} detecting capability, we provide their proper motions for the first time with a precision of 7.0 \masyr. However, the secondary $\sim$136 million sources only have PS1 astrometry, the average precision is worse than 15.0 \masyr. All the proper motions have been validated using QSOs and the existing {\it Gaia} proper motions. The catalog will be released on-line and available via the VO-TAP Service, or via the National Astronomical Data Center serviced by China-VO: https://nadc.china-vo.org/data/data/gps1p/f.

astro-ph.GA↗

arXiv2020

On the radial velocity calibrations in the LAMOST Medium-Resolution Spectroscopic Survey of Nebulae

Accurate radial velocity determinations of optical emission lines (i.e. [NII]$λλ$6548,6584, H$α$, and [SII]$λλ$6717,6731) are very important for investigating the kinematics and dynamics properties of nebulae. The second stage survey program of Large sky Area Multi-Object fiber Spectroscopic Telescope (LAMOST) has started a sub-survey of nebulae (MRS-N) which will spectroscopically observe the optical emission lines of a large sample of nebulae near the Galactic plane. Until now, 15 MRS-N plates have been observed from 2017 September to 2019 June. Based on fitting the sky emission lines in the red band spectra of MRS-N, we investigate the precision of wavelength calibration and find there are systematic deviations of radial velocities (RVs) from $\sim$0.2 to 4 km/s for different plates. Especially for the plates obtained in 2018 March, the systematic deviations of RVs can be as large as $\sim$4 km/s, which then go down to $\sim$0.2-0.5 km/s at the end of 2018 and January 2019. A RVs calibration function is proposed for these MRS-N plates, which can simultaneously and successfully calibration the systematic deviations and improve the precision of RVs.

astro-ph.SR↗

arXiv2020

Anisotropy of the Milky Way's stellar halo using K giants from LAMOST and $Gaia$

The anisotropy parameter $β$ characterizes the extent to which orbits in stellar systems are predominantly radial or tangential, and is likely to constrain, for the stellar halo of the Milky Way, scenarios for its formation and evolution. We have measured the anisotropy $β$ as a function of Galactocentric radius from $5-100$ kpc for over 8600 metal poor ([Fe/H] $<-1.3$) halo K giants from the LAMOST catalog with line-of-sight velocities and distances, matched to proper motions from the second $Gaia$ data release. We construct full 6-D positions and velocities for the K giants to directly measure the 3 components of the velocity dispersion $(σ_r, σ_θ, σ_ϕ)$ (in spherical coordinates). We find that the orbits in the halo are radial over our full Galactocentric distance range reaching over 100 kpc. The anisotropy remains remarkably unchanged with Galactocentric radius from approximately 5 to 25 kpc, with an amplitude that depends on the metallicity of the stars, dropping from $β\approx 0.9$ for $-1.8 \leq$ [Fe/H] $< -1.3$ (for the bulk of the stars) to $β\approx 0.6$ for the lowest metallicities ([Fe/H] $< -1.8$). Considering our sample as a whole, $β\approx0.8$ and, beyond 25 kpc, the orbits gradually become less radial and anisotropy decreases to $β<0.3$ past 100 kpc. Within 8 kpc, $β<0.8$. The measurement of anisotropy is affected by substructure and streams, particularly beyond a Galactocentric distance of approximately 25 kpc, where the Sagittarius stream is prominent in the data. These results are complimentary to recent analysis of simulations by Loebman et al. and of SDSS/$Gaia$ DR1 data by Belokurov et al.

astro-ph.GA↗

arXiv2020

Differential rotation of the halo traced by the K-giant stars

We use K-giant stars selected from the LAMOST DR5 to study the variation of the rotational velocity of the galactic halo at different space positions. Modelling the rotational velocity distribution with both the halo and disk components, we find that the rotational velocity of the halo population decreases almost linearly with increasing vertical distance to the galactic disk plane, $Z$, at fixed galactocentric radius, $R$. The samples are separated into two parts with $6<R<12$ kpc and $12<R<20$ kpc. We derive that the decreasing rates along $Z$ for the two subsamples are $-3.07\pm0.63$ and $-1.89\pm0.37$ km s$^{-1}$ kpc$^{-1}$, respectively. Compared with the TNG simulations, we suggest that this trend is probably caused by the interaction between the disk and halo. The results from the simulations show that only the oblate halo can provide a decreasing rotational velocity with an increasing $Z$. This indicates that the Galactic halo is oblate with galactocentric radius $R<20$ kpc. On the other hand, the flaring of the disk component (mainly the thick disk) is clearly traced by this study, with $R$ between 12 and 20 kpc, the disk can vertically extend to $6\sim10$ kpc above the disk plane. What is more interesting is that, we find the Gaia-Enceladus-Sausage (GES) component has a significant contribution only in the halo with $R<12$ kpc, i.e. a fraction of 23$-$47\%. While in the outer subsample, the contribution is too low to be well constrained.

astro-ph.GA↗

arXiv2020

On the Replicability and Reproducibility of Deep Learning in Software Engineering

Deep learning (DL) techniques have gained significant popularity among software engineering (SE) researchers in recent years. This is because they can often solve many SE challenges without enormous manual feature engineering effort and complex domain knowledge. Although many DL studies have reported substantial advantages over other state-of-the-art models on effectiveness, they often ignore two factors: (1) replicability - whether the reported experimental result can be approximately reproduced in high probability with the same DL model and the same data; and (2) reproducibility - whether one reported experimental findings can be reproduced by new experiments with the same experimental protocol and DL model, but different sampled real-world data. Unlike traditional machine learning (ML) models, DL studies commonly overlook these two factors and declare them as minor threats or leave them for future work. This is mainly due to high model complexity with many manually set parameters and the time-consuming optimization process. In this study, we conducted a literature review on 93 DL studies recently published in twenty SE journals or conferences. Our statistics show the urgency of investigating these two factors in SE. Moreover, we re-ran four representative DL models in SE. Experimental results show the importance of replicability and reproducibility, where the reported performance of a DL model could not be replicated for an unstable optimization process. Reproducibility could be substantially compromised if the model training is not convergent, or if performance is sensitive to the size of vocabulary and testing data. It is therefore urgent for the SE community to provide a long-lasting link to a replication package, enhance DL-based solution stability and convergence, and avoid performance sensitivity on different sampled data.

cs.SE↗

arXiv2020

Measuring the local dark matter density with LAMOST DR5 and Gaia DR2

We apply the vertical Jeans equation to the kinematics of Milky Way stars in the solar neighbourhood to measure the local dark matter density. More than 90,000 G- and K-type dwarf stars are selected from the cross-matched sample of LAMOST DR5 and Gaia DR2 for our analyses. The mass models applied consist of a single exponential stellar disc, a razor thin gas disc and a constant dark matter density. We first consider the simplified vertical Jeans equation which ignores the tilt term and assumes a flat rotation curve. Under a Gaussian prior on the total stellar surface density, the local dark matter density inferred from Markov Chain Monte Carlo simulations is $0.0133_{-0.0022}^{+0.0024}\ {\rm M}_{\odot}\,{\rm pc}^{-3}$. The local dark matter densities for subsamples in an azimuthal angle range of $-10^{\circ} < ϕ< 5^{\circ}$ are consistent within their 1$σ$ errors. However, the northern and southern subsamples show a large discrepancy due to plateaux in the northern and southern vertical velocity dispersion profiles. These plateaux may be the cause of the different estimates of the dark matter density between the north and south. Taking the tilt term into account has little effect on the parameter estimations and does not explain the north and south asymmetry. Taking half of the difference of $σ_{z}$ profiles as unknown systematic errors, we then obtain consistent measurements for the northern and southern subsamples. We discuss the influence of the vertical data range, the scale height of the tracer population, the vertical distribution of stars and the sample size on the uncertainty of the determination of the local dark matter density.

astro-ph.GA↗

arXiv2020

LAMOST Medium-Resolution Spectroscopic Survey (LAMOST-MRS): Scientific goals and survey plan

Since September 2018, LAMOST starts a new 5-year medium-resolution spectroscopic survey (MRS) using bright/gray nights. We present the scientific goals of LAMOST-MRS and propose a near optimistic strategy of the survey. A complete footprint is also provided. Not only the regular medium-resolution survey, but also a time-domain spectroscopic survey is being conducted since 2018 and will be end in 2023. According to the detailed survey plan, we expect that LAMOST-MRS can observe about 2 million stellar spectra with ~7500 and limiting magnitude of around G=15 mag. Moreover, it will also provide about 200 thousand stars with averagely 60-epoch observations and limiting magnitude of G~14 mag. These high quality spectra will give around 20 elemental abundances, rotational velocities, emission line profiles as well as precise radial velocity with uncertainty less than 1 km/s. With these data, we expect that LAMOST can effectively leverage sciences on stellar physics, e.g. exotic binary stars, detailed observation of many types of variable stars etc., planet host stars, emission nebulae, open clusters, young pre-main-sequence stars etc.

astro-ph.SR↗

arXiv2020

Three New Late-type Hypervelocity Star Candidates from Gaia DR2 with Refined Selection Criteria

Several dozen hypervelocity star (HVS) candidates have been reported based on the second data release of Gaia (Gaia DR2). However, it has been proven that the radial velocities of some Gaia HVS candidates are not reliable. In this paper, we employ refined astrometric criteria to re-examine Gaia DR2, arriving at a more reliable sample of HVS and high velocity star candidates than those found by previous authors.We develop a method called Binary Escape Probability Analysis to identify some HVS candidates. This method allows us to work with stars having only two epochs of measured radial velocity. These stars were usually discarded in previous similar studies. A scrutiny of our final results sheds light on selection effects present in our studies, which we propose to be the focus of future studies. In total, we find three late-type (2 G-type and 1 K-type) HVS and 21 high velocity star candidates, 3 and 11 of which are new, respectively. Judging by their historical trajectories, which we calculate, all three HVS candidates could not have had Galactic center origins. Further monitoring is required to confirm their status.

astro-ph.SR↗

arXiv2020

Discovery of two nearby post-T Tauri stellar associations

In this work we report the discovery of 2 new stellar associations in close vicinity of the Sun at roughly 180 and 150 pc. These two associations, named as u Tau assoc and e Tau assoc, were detected based on their clustering in a multi-dimensional parameter space including $α$, $δ$, $μ_α$ , $μ_δ$ and $π$ of Gaia. The fitting of pre-main-sequence model isochrones in their color-magnitude diagrams suggests that the two associations are of about 50 Myr old and the group members lower than ${\sim}$0.8 $M_{\odot}$ are at the stage of post-T Tauri.

astro-ph.SR↗