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Qi Guo

Publications and source records attributed to Qi Guo.

At least 235 records · Page 13Linked to original sources
arXiv2021

L-GALAXIES 2020: The evolution of radial metallicity profiles and global metallicities in disc galaxies

We present a modified version of the L-GALAXIES 2020 semi-analytic model of galaxy evolution, which includes significantly increased direct metal enrichment of the circumgalactic medium (CGM) by supernovae (SNe). These more metal-rich outflows do not require increased mass-loading factors, in contrast to some other galaxy evolution models. This modified L-GALAXIES 2020 model is able to simultaneously reproduce the gas-phase metallicity $(Z_{\rm g})$ and stellar metallicity $(Z_{*})$ radial profiles observed in nearby disc galaxies by MaNGA and MUSE, as well as the observed mass - metallicity relations for gas and stars at $z=0$ and their evolution back to $z\sim{}2-3$. A direct CGM enrichment fraction of $\sim{}90\%$ for SNe-II is preferred. We find that massive disc galaxies have slightly flatter $Z_{\rm g}$ profiles than their lower-mass counterparts in L-GALAXIES 2020, due to more efficient enrichment of their outskirts via inside-out growth and metal-rich accretion. Such a weak, positive correlation between stellar mass and $Z_{\rm g}$ profile slope is also seen in our MaNGA-DR15 sample of 571 star-forming disc galaxies. Although, below ${\rm log}(M_{*}/{\rm M}_{\odot})\sim{}10.0$ this observational result is strongly dependent on the metallicity diagnostic and morphological selection chosen. In addition, a lowered maximum SN-II progenitor mass of $25{\rm M}_{\odot}$, reflecting recent theoretical and observational estimates, can also provide a good match to observed metallicity profiles at $z=0$ in L-GALAXIES 2020. However, this model version fails to reproduce an evolution in $Z_{\rm g}$ at fixed mass over cosmic time, or the magnesium abundances observed in the intracluster medium (ICM).

astro-ph.GA↗
arXiv2021

PanGu-$α$: Large-scale Autoregressive Pretrained Chinese Language Models with Auto-parallel Computation

Large-scale Pretrained Language Models (PLMs) have become the new paradigm for Natural Language Processing (NLP). PLMs with hundreds of billions parameters such as GPT-3 have demonstrated strong performances on natural language understanding and generation with \textit{few-shot in-context} learning. In this work, we present our practice on training large-scale autoregressive language models named PanGu-$α$, with up to 200 billion parameters. PanGu-$α$ is developed under the MindSpore and trained on a cluster of 2048 Ascend 910 AI processors. The training parallelism strategy is implemented based on MindSpore Auto-parallel, which composes five parallelism dimensions to scale the training task to 2048 processors efficiently, including data parallelism, op-level model parallelism, pipeline model parallelism, optimizer model parallelism and rematerialization. To enhance the generalization ability of PanGu-$α$, we collect 1.1TB high-quality Chinese data from a wide range of domains to pretrain the model. We empirically test the generation ability of PanGu-$α$ in various scenarios including text summarization, question answering, dialogue generation, etc. Moreover, we investigate the effect of model scales on the few-shot performances across a broad range of Chinese NLP tasks. The experimental results demonstrate the superior capabilities of PanGu-$α$ in performing various tasks under few-shot or zero-shot settings.

cs.CL↗
arXiv2021

Mass and Environment as Drivers of Galaxy Evolution. IV. On the Quenching of Massive Central Disk Galaxies in The Local Universe

The phenomenological study of evolving galaxy populations has shown that star forming galaxies can be quenched by two distinct processes: mass quenching and environment quenching (Peng et al. 2010). To explore the mass quenching process in local galaxies, we study the massive central disk galaxies with stellar mass above the Schechter characteristic mass. In Zhang et al. (2019), we showed that during the quenching of the massive central disk galaxies as their star formation rate (SFR) decreases, their molecular gas mass and star formation efficiency drop rapidly, but their HI gas mass remains surprisingly constant. To identify the underlying physical mechanisms, in this work we analyze the change during quenching of various structure parameters, bar frequency, and active galactic nucleus (AGN) activity. We find three closely related facts. On average, as SFR decreases in these galaxies: (1) they become progressively more compact, indicated by their significantly increasing concentration index, bulge-to-total mass ratio, and central velocity dispersion, which are mainly driven by the growth and compaction of their bulge component; (2) the frequency of barred galaxies increases dramatically, and at a given concentration index the barred galaxies have a significantly higher quiescent fraction than unbarred galaxies, implying that the galactic bar may play an important role in mass quenching; and (3) the "AGN" frequency increases dramatically from 10% on the main sequence to almost 100% for the most quiescent galaxies, which is mainly driven by the sharp increase of LINERs. These observational results lead to a self-consistent picture of how mass quenching operates.

astro-ph.GA↗
arXiv2021

Modified quantum delayed-choice experiment without quantum control

Wheeler's delayed-choice experiment delays the decision to observe either the wave or particle behavior of a photon until after it has entered the interferometer, and the quantum delayed-choice experiment provides the possibility of observing the wave and particle behavior simultaneously by introducing quantum control device. We here propose a modified quantum delayed-choice experiment without quantum control or entanglement assistance, in which a photon can be prepared in a wave-particle superposition state and the morphing behavior of wave-to-particle transition can be observed easily. It is demonstrated that the presented scheme can allow us to rule out classical hidden variable models in a device-independent manner via violating dimension witness. We also extend the scheme to the situation of two degrees of freedom, first constructing a hybrid quantum delayed-choice experiment which enables simultaneous observation of a photon's wave and particle behaviors in different degrees of freedom, and then proposing a scheme to prepare the single-photon wave-particle entanglement. This study is not only meaningful to explore the wave and particle properties of photons, but also provides potential for the research of the single-particle nonlocality from the perspective of the wave-particle degree of freedom.

quant-ph↗
arXiv2020

Galaxy properties in the cosmic web of EAGLE simulation

We investigate the dependence of the galaxy properties on cosmic web environments using the most up-to-date hydrodynamic simulation: Evolution and Assembly of Galaxies and their Environments (EAGLE). The baryon fractions in haloes and the amplitudes of the galaxy luminosity function decrease going from knots to filaments to sheets to voids. Interestingly, the value of L$^*$ varies dramatically in different cosmic web environments. At z = 0, we find a characteristic halo mass of $10^{12} h^{-1}\rm M_{\odot}$, below which the stellar-to-halo mass ratio is higher in knots while above which it reverses. This particular halo mass corresponds to a characteristic stellar mass of $1.8\times 10^{10} h^{-1}\rm M_{\odot}$. Below the characteristic stellar mass central galaxies have redder colors, lower sSFRs and higher metallicities in knots than those in filaments, sheets and voids, while above this characteristic stellar mass, the cosmic web environmental dependences either reverse or vanish. Such dependences can be attributed to the fact that the active galaxy fraction decreases along voids, sheets, filaments and knots. The cosmic web dependences get weaker towards higher redshifts for most of the explored galaxy properties and scaling relations, except for the gas metallicity vs. stellar mass relation.

astro-ph.GA↗
arXiv2020

DeText: A Deep Text Ranking Framework with BERT

Ranking is the most important component in a search system. Mostsearch systems deal with large amounts of natural language data,hence an effective ranking system requires a deep understandingof text semantics. Recently, deep learning based natural languageprocessing (deep NLP) models have generated promising results onranking systems. BERT is one of the most successful models thatlearn contextual embedding, which has been applied to capturecomplex query-document relations for search ranking. However,this is generally done by exhaustively interacting each query wordwith each document word, which is inefficient for online servingin search product systems. In this paper, we investigate how tobuild an efficient BERT-based ranking model for industry use cases.The solution is further extended to a general ranking framework,DeText, that is open sourced and can be applied to various rankingproductions. Offline and online experiments of DeText on threereal-world search systems present significant improvement overstate-of-the-art approaches.

cs.IR↗
arXiv2020

Multivariate General Compound Point Processes in Limit Order Books

In this paper, we focus on a new generalization of multivariate general compound Hawkes process (MGCHP), which we referred to as the multivariate general compound point process (MGCPP). Namely, we applied a multivariate point process to model the order flow instead of the Hawkes process. Law of large numbers (LLN) and two functional central limit theorems (FCLTs) for the MGCPP were proved in this work. Applications of the MGCPP in the limit order market were also considered. We provided numerical simulations and comparisons for the MGCPP and MGCHP by applying Google, Apple, Microsoft, Amazon, and Intel trading data.

q-fin.MF↗
arXiv2020

The Luminosity Distribution of Short Gamma-Ray Bursts under a Structured Jet Scenario

Luminosity of GRB 170817A is much lower than that of other sGRBs. The measurement of the superluminal movement of the radio afterglow emission confirms the presence of the relativistic jet, and the emission features can be well explained by the structured jet model. In this paper, we calculate the luminosity distribution of sGRBs and its evolution with redshift based on the structured (Gaussian) jet model, and find that the typical luminosity increase with redshift, for nearby sGRBs (such as for luminosity distance less than 200 Mpc) the typical gamma-ray luminosity is just around 10^47-10^48 erg s-1, which naturally explains the very low radiation luminosity of GRB 170817A. We derived the detection probability of sGRBs by Fermi-GBM and found that the expected detection rate of sGRBs is only about 1 yr-1 within the distance of several hundred Mpc. We explored the effect of the power-law index α of the merger time distribution on the observed characteristics and found that it had little effect on the observed luminosity and viewing-angle distributions. However, it is very interesting that, for different values of α, the distributions of the number of observed sGRBs are quite different, so it is possible to determine the value of α through observed distributions of the number of sGRBs. We used the Bayesian method to make a quantitative analysis and found that the value of α may be identified when the number of observed sGRBs with known redshifts is more than 200. Finally, we compare our results of gamma-ray luminosity distribution with sGRBs with known redshifts, and found that our results are consistent with the observation, which implies that our simulation results can reproduce the observed luminosity distribution well.

astro-ph.HE↗
arXiv2020

Discovery of a Universal Correlation For Long and Short GRBs and Its Application on the Study of Luminosity Function and Formation Rate

Gamma-ray bursts (GRBs) are known to be the most violent explosions in the universe, and a variety of correlations between observable GRB properties have been proposed in literature, but none of these correlations is valid for both long GRBs and short GRBs. In this paper we report the discovery of a universal correlation which is suitable for both long and short GRBs using three prompt emission properties of GRBs, i.e. the isotropic peak luminosity $L_{\rm iso}$, the peak energy of the time-integtated prompt emission spectrum $E_{\rm peak}$, and the "high signal" timescale $T_{\rm 0.45}$, $L_{\rm iso} \propto E_{\rm peak}^{1.94} T_{0.45}^{0.37}$. This universal correlation just involves properties of GRB prompt emission and does not require any information of afterglow phase, which can be used as a relatively unbiased redshift estimator. Here we use this correlation to estimate the pseudo-redshifts for short Gamma Ray Bursts and then use Lynden-Bell method to obtain a non-parametric estimate of their luminosity function and formation rate. The luminosity function is $ψ(L_0)\propto{L_0^{-0.63\pm{0.07}}}$ for dim SGRBs and $ψ(L_0)\propto{L_0^{-1.96\pm{0.28}}}$ for bright SGRBs, with the break point $6.95_{-0.76}^{+0.84}\times10^{50} erg/s$. The local formation rate of SGRBs is about 15 events $\rm Gpc^{-3}yr^{-1}$ . This universal correlation may have important implications for GRB physics, implying that the long and short GRBs should share similar radiation processes.

astro-ph.HE↗
arXiv2020

MOTS: Multiple Object Tracking for General Categories Based On Few-Shot Method

Most modern Multi-Object Tracking (MOT) systems typically apply REID-based paradigm to hold a balance between computational efficiency and performance. In the past few years, numerous attempts have been made to perfect the systems. Although they presented favorable performance, they were constrained to track specified category. Drawing on the ideas of few shot method, we pioneered a new multi-target tracking system, named MOTS, which is based on metrics but not limited to track specific category. It contains two stages in series: In the first stage, we design the self-Adaptive-matching module to perform simple targets matching, which can complete 88.76% assignments without sacrificing performance on MOT16 training set. In the second stage, a Fine-match Network was carefully designed for unmatched targets. With a newly built TRACK-REID data-set, the Fine-match Network can perform matching of 31 category targets, even generalizes to unseen categories.

cs.CV↗
arXiv2020

NMR and NQR studies on transition-metal arsenide superconductors LaRu2As2, KCa2Fe4As4F2, and A2Cr3As3

We report 75As-nuclear magnetic resonance (NMR) and nuclear quadrupole resonance (NQR) measurements on transition-metal arsenides LaRu2As2, KCa2Fe4As4F2, and A2Cr3As3. In the superconducting state of LaRu2As2, a Hebel- Slichter coherence peak is found in the temperature dependence of the spin-lattice relaxation rate-1/T1 just below Tc, which indicates that LaRu2As2 is a full-gap superperconducor. For KCa2Fe4As4F2, antiferromagnetic spin fluctuations are observed in the normal state. We further find that the anisotropy rate RAF = Tc1/Tab1 is small and temperature independent, implying that the low energy spin fluctuations are isotropic in spin space. Our results indicate that KCa2Fe4As4F2 is a moderately overdoped iron-arsenide high-temperature superconductor with a stoichiometric composition. For A2Cr3As3, we calculate the electric field gradient by first-principle method and assign the 75As-NQR peaks with two crystallographically different As sites, paving the way for further NMR investigation.

cond-mat.supr-con↗
arXiv2020

A Hybrid Lagrangian/Eulerian Collocated Advection and Projection Method for Fluid Simulation

We present a hybrid particle/grid approach for simulating incompressible fluids on collocated velocity grids. We interchangeably use particle and grid representations of transported quantities to balance efficiency and accuracy. A novel Backward Semi-Lagrangian method is derived to improve accuracy of grid based advection. Our approach utilizes the implicit formula associated with solutions of Burgers' equation. We solve this equation using Newton's method enabled by $C^1$ continuous grid interpolation. We enforce incompressibility over collocated, rather than staggered grids. Our projection technique is variational and designed for B-spline interpolation over regular grids where multiquadratic interpolation is used for velocity and multilinear interpolation for pressure. Despite our use of regular grids, we extend the variational technique to allow for cut-cell definition of irregular flow domains for both Dirichlet and free surface boundary conditions.

cs.GR↗
arXiv2020

L-GALAXIES 2020: Spatially resolved cold gas phases, star formation and chemical enrichment in galactic discs

We have updated the Munich galaxy formation model, L-Galaxies, to follow the radial distributions of stars and atomic and molecular gas in galaxy discs. We include an H2-based star-formation law, as well as a detailed chemical-enrichment model with explicit mass-dependent delay times for SN-II, SN-Ia and AGB stars. Information about the star formation, feedback and chemical-enrichment histories of discs is stored in 12 concentric rings. The new model retains the success of its predecessor in reproducing the observed evolution of the galaxy population, in particular, stellar mass functions and passive fractions over the redshift range 0<=z<=3 and mass range 8<=log(M_*/Msun)<=12, the black hole-bulge mass relation at z=0, galaxy morphology as a function of stellar mass and the mass-metallicity relations of both stellar and gas components. In addition, its detailed modelling of the radial structure of discs allows qualitatively new comparisons with observation, most notably with the relative sizes and masses of the stellar, atomic and molecular components in discs. Good agreement is found with recent data. Comparison of results obtained for simulations differing in mass resolution by more than two orders of magnitude shows that all important distributions are numerically well converged even for this more detailed model. An examination of metallicity and surface-density gradients in the stars and gas indicates that our new model, with star formation, chemical enrichment and feedback calculated self-consistently on local disc scales, reproduces some but not all of the trends seen in recent many-galaxy IFU surveys.

astro-ph.GA↗
arXiv2020

DWM: A Decomposable Winograd Method for Convolution Acceleration

Winograd's minimal filtering algorithm has been widely used in Convolutional Neural Networks (CNNs) to reduce the number of multiplications for faster processing. However, it is only effective on convolutions with kernel size as 3x3 and stride as 1, because it suffers from significantly increased FLOPs and numerical accuracy problem for kernel size larger than 3x3 and fails on convolution with stride larger than 1. In this paper, we propose a novel Decomposable Winograd Method (DWM), which breaks through the limitation of original Winograd's minimal filtering algorithm to a wide and general convolutions. DWM decomposes kernels with large size or large stride to several small kernels with stride as 1 for further applying Winograd method, so that DWM can reduce the number of multiplications while keeping the numerical accuracy. It enables the fast exploring of larger kernel size and larger stride value in CNNs for high performance and accuracy and even the potential for new CNNs. Comparing against the original Winograd, the proposed DWM is able to support all kinds of convolutions with a speedup of ~2, without affecting the numerical accuracy.

cs.LG↗
arXiv2020

Local Group Analogs in $Λ$CDM cosmological simulations

We use semi-analytic galaxy catalogs based on two high-resolution cosmological $N$-body simulations, Millennium-WMAP7 and Millennium-II, to investigate the formation of the Local Group (LG) analogs. Unlike previous studies, we use the observed stellar masses to select the LG member (Milky Way (MW) and M31) analogs, and then impose constrains using the observed separation, isolation, and kinematics of the two main member galaxies. By comparing radial and low-ellipticity orbits between the MW and M31, we find higher tangential velocity results in higher total mass, which are 4.4$^{+2.4}_{-1.5}\times$10$^{12}\rm M_{\odot}$ and 6.6$^{+2.7}_{-1.5}\times$10$^{12}\rm M_{\odot}$ for radial and low-ellipticity orbits. The orbits also influence the individual mass distribution of MW and M31 analogs. For radial orbits, the typical host halo masses of the MW and M31 are 1.5$^{+1.4}_{-0.7}\times$10$^{12}\rm M_{\odot}$ and 2.5$^{+1.3}_{-1.1}\times$10$^{12}\rm M_{\odot}$; for low-ellipticity orbits, the masses are 2.5$^{+2.2}_{-1.4}\times$10$^{12}\rm M_{\odot}$ and 3.8$^{+2.8}_{-1.8}\times$10$^{12} \rm M_{\odot}$. The LG is located primarily in filaments with tails extending toward higher densities up to $δ\sim4.5$. The dark matter velocity anisotropy parameters $β$ of both the MW and M31 analogs are close to zero in the center, increasing to 0.2--0.3 at 50--80 kpc and decreasing slowly outward. The slope is much flatter than computed from the MW satellites, and the amplitude is smaller than traced by halo stars. Values of $β$ from different tracers agree at $\sim$120 kpc where $β\sim$ 0.2. We also find that model predictions agree broadly with observations in the radial distribution and luminosity function of satellites around the MW and M31.

astro-ph.GA↗
arXiv2019

Further evidence for a population of dark-matter-deficient dwarf galaxies

In the standard cosmological model, dark matter drives the structure formation and constructs potential wells within which galaxies may form. The baryon fraction in dark halos can reach the universal value (15.7%) in massive clusters and decreases rapidly as the mass of the system decreases. The formation of dwarf galaxies is sensitive both to baryonic processes and the properties of dark matter owing to the shallow potential wells in which they form. In dwarf galaxies in the Local Group, dark matter dominates the mass content even within their optical-light half-radii (r_e ~ 1 kpc). However, recently it has been argued that not all dwarf galaxies are dominated by dark matter. Here we report 19 dwarf galaxies that could consist mainly of baryons up to radii well beyond r_e, at which point they are expected to be dominated by dark matter. Of these, 14 are isolated dwarf galaxies, free from the influence of nearby bright galaxies and high dense environments. This result provides observational evidence that could challenge the formation theory of low-mass galaxies within the framework of standard cosmology. Further observations, in particular deep imaging and spatially-resolved kinematics, are needed to constrain the baryon fraction better in such galaxies.

astro-ph.GA↗
arXiv2019

Ultra-diffuse galaxies in the Auriga simulations

We investigate the formation of ultra-diffuse galaxies (UDGs) using the Auriga high-resolution cosmological magneto-hydrodynamical simulations of Milky Way-sized galaxies. We identify a sample of $92$ UDGs in the simulations that match a wide range of observables such as sizes, central surface brightness, Sérsic indices, colors, spatial distribution and abundance. Auriga UDGs have dynamical masses similar to normal dwarfs. In the field, the key to their origin is a strong correlation present in low-mass dark matter haloes between galaxy size and halo spin parameter. Field UDGs form in dark matter haloes with larger spins compared to normal dwarfs in the field, in agreement with previous semi-analytical models. Satellite UDGs, on the other hand, have two different origins: $\sim 55\%$ of them formed as field UDGs before they were accreted; the remaining $\sim 45\%$ were normal field dwarfs that subsequently turned into UDGs as a result of tidal interactions.

astro-ph.GA↗