arXiv subjects

Youcai Zhang

Publications and source records attributed to Youcai Zhang.

At least 37 records · Page 2Linked to original sources

arXiv2022

Galaxy-halo size relation from Sloan Digital Sky Survey Data Release 7 and the ELUCID simulation

Based on galaxies in the Sloan Digital Sky Survey Data Release 7 (SDSS DR7) and dark matter haloes in the dark matter only, cosmological and constrained ELUCID simulation, we investigate the relation between the observed radii of central galaxies with stellar mass $\gtrsim 10^{8} h^{-2}{\rm M}_\odot$ and the virial radii of their host dark matter haloes with virial mass $\gtrsim 10^{10.5} h^{-1}{\rm M}_\odot$, and the dependence of galaxy-halo size relation on the halo spin and concentration. Galaxies in observation are matched to dark matter (sub-)haloes in the ELUCID simulation using a novel neighborhood subhalo abundance matching method. For galaxy 2D half-light radii $R_{50}$, we find that early- and late-type galaxies have the same power-law index 0.55 with $R_{50} \propto R_{\rm vir}^{0.55}$, although early-type galaxies have smaller 2D half-light radii than late-type galaxies at fixed halo virial radii. When converting the 2D half-light radii $R_{50}$ to 3D half-mass radii $r_{1/2}$, both early- and late-type galaxies display similar galaxy-halo size relations with $\log r_{1/2} = 0.55 \log (R_{\rm vir}/210 h^{-1}{\rm kpc}) + 0.39$. We find that the galaxy-halo size ratio $r_{1/2}/ R_{\rm vir}$ decreases with increasing halo mass. At fixed halo mass, there is no significant dependence of galaxy-halo size ratio on the halo spin or concentration.

astro-ph.GA↗

arXiv2022

Elucidating Galaxy Assembly Bias in SDSS

We investigate the level of galaxy assembly bias in the Sloan Digital Sky Survey (SDSS) main galaxy sample using ELUCID, a state-of-the-art constrained simulation that accurately reconstructed the initial density perturbations within the SDSS volume. On top of the ELUCID haloes, we develop an extended HOD model that includes the assembly bias of central and satellite galaxies, parameterized as $\mathcal{Q}_\mathrm{cen}$ and $\mathcal{Q}_\mathrm{sat}$, respectively, to predict a suite of one- and two-point observables. In particular, our fiducial constraint employs the probability distribution of the galaxy number counts measured on $8\,\mathrm{Mpc}\,h^{-1}$ scales $N_8^g$ and the projected cross-correlation functions of quintiles of galaxies selected by $N_8^g$ with our entire galaxy sample. We perform extensive tests of the efficacy of our method by fitting the same observables to mock data using both constrained and non-constrained simulations. We discover that in many cases the level of cosmic variance between the two simulations can produce biased constraints that lead to an erroneous detection of galaxy assembly bias if the non-constrained simulation is used. When applying our method to the SDSS data, the ELUCID reconstruction effectively removes an otherwise strong degeneracy between cosmic variance and galaxy assembly bias in SDSS, enabling us to derive an accurate and stringent constraint on the latter. Our fiducial ELUCID constraint, for galaxies above a stellar mass threshold $M_*{=}10^{10.2}\,h^{-2}\,M_\odot$, is $\mathcal{Q}_\mathrm{cen}{=}{-}0.09\pm{0.05}$ and $\mathcal{Q}_\mathrm{sat}{=}0.09\pm{0.10}$, indicating no evidence for a significant~($>2σ$) galaxy assembly bias in the local Universe probed by SDSS. Finally, our method provides a promising path to the robust modelling of the galaxy-halo connection within future surveys like DESI and PFS.

astro-ph.CO↗

arXiv2022

IDEA: Increasing Text Diversity via Online Multi-Label Recognition for Vision-Language Pre-training

Vision-Language Pre-training (VLP) with large-scale image-text pairs has demonstrated superior performance in various fields. However, the image-text pairs co-occurrent on the Internet typically lack explicit alignment information, which is suboptimal for VLP. Existing methods proposed to adopt an off-the-shelf object detector to utilize additional image tag information. However, the object detector is time-consuming and can only identify the pre-defined object categories, limiting the model capacity. Inspired by the observation that the texts incorporate incomplete fine-grained image information, we introduce IDEA, which stands for increasing text diversity via online multi-label recognition for VLP. IDEA shows that multi-label learning with image tags extracted from the texts can be jointly optimized during VLP. Moreover, IDEA can identify valuable image tags online to provide more explicit textual supervision. Comprehensive experiments demonstrate that IDEA can significantly boost the performance on multiple downstream datasets with a small extra computational cost.

cs.CV↗

arXiv2022

An Extended Halo-based Group/Cluster finder: application to the DESI legacy imaging surveys DR8

We extend the halo-based group finder developed by \citet[][]{Yang2005a} to use data {\it simultaneously} with either photometric or spectroscopic redshifts. A mock galaxy redshift survey constructed from a high-resolution N-body simulation is used to evaluate the performance of this extended group finder. For galaxies with magnitude ${\rm z\le 21}$ and redshift $0<z\le 1.0$ in the DESI legacy imaging surveys (the Legacy Surveys), our group finder successfully identifies more than 60\% of the members in about $90\%$ of halos with mass $\ga 10^{12.5}\msunh$. Detected groups with mass $\ga 10^{12.0}\msunh$ have a purity (the fraction of true groups) greater than 90\%. The halo mass assigned to each group has an uncertainty of about 0.2 dex at the high mass end $\ga 10^{13.5}\msunh$ and 0.40 dex at the low mass end. Groups with more than 10 members have a redshift accuracy of $\sim 0.008$. We apply this group finder to the Legacy Surveys DR8 and find 5.2 Million groups with at least 3 members. About 387,000 of these groups have at least 10 members. The resulting catalog containing 3D coordinates, richness, halo masses, and total group luminosities, is made publicly available.

astro-ph.GA↗

arXiv2022

Towards Communication-Efficient and Privacy-Preserving Federated Representation Learning

This paper investigates the feasibility of federated representation learning under the constraints of communication cost and privacy protection. Existing works either conduct annotation-guided local training which requires frequent communication or aggregates the client models via weight averaging which has potential risks of privacy exposure. To tackle the above problems, we first identify that self-supervised contrastive local training is robust against the non-identically distributed data, which provides the feasibility of longer local training and thus reduces the communication cost. Then based on the aforementioned robustness, we propose a novel Federated representation Learning framework with Ensemble Similarity Distillation~(FLESD) that utilizes this robustness. At each round of communication, the server first gathers a fraction of the clients' inferred similarity matrices on a public dataset. Then it ensembles the similarity matrices and train the global model via similarity distillation. We verify the effectiveness of FLESD by a series of empirical experiments and show that, despite stricter constraints, it achieves comparable results under multiple settings on multiple datasets.

cs.LG↗

arXiv2021

Simple and Robust Loss Design for Multi-Label Learning with Missing Labels

Multi-label learning in the presence of missing labels (MLML) is a challenging problem. Existing methods mainly focus on the design of network structures or training schemes, which increase the complexity of implementation. This work seeks to fulfill the potential of loss function in MLML without increasing the procedure and complexity. Toward this end, we propose two simple yet effective methods via robust loss design based on an observation that a model can identify missing labels during training with a high precision. The first is a novel robust loss for negatives, namely the Hill loss, which re-weights negatives in the shape of a hill to alleviate the effect of false negatives. The second is a self-paced loss correction (SPLC) method, which uses a loss derived from the maximum likelihood criterion under an approximate distribution of missing labels. Comprehensive experiments on a vast range of multi-label image classification datasets demonstrate that our methods can remarkably boost the performance of MLML and achieve new state-of-the-art loss functions in MLML.

cs.LG↗

arXiv2021

On the Efficacy of Small Self-Supervised Contrastive Models without Distillation Signals

It is a consensus that small models perform quite poorly under the paradigm of self-supervised contrastive learning. Existing methods usually adopt a large off-the-shelf model to transfer knowledge to the small one via distillation. Despite their effectiveness, distillation-based methods may not be suitable for some resource-restricted scenarios due to the huge computational expenses of deploying a large model. In this paper, we study the issue of training self-supervised small models without distillation signals. We first evaluate the representation spaces of the small models and make two non-negligible observations: (i) the small models can complete the pretext task without overfitting despite their limited capacity and (ii) they universally suffer the problem of over clustering. Then we verify multiple assumptions that are considered to alleviate the over-clustering phenomenon. Finally, we combine the validated techniques and improve the baseline performances of five small architectures with considerable margins, which indicates that training small self-supervised contrastive models is feasible even without distillation signals. The code is available at \textit{https://github.com/WOWNICE/ssl-small}.

cs.LG↗

arXiv2021

Connections between galaxy properties and halo formation time in the cosmic web

By linking galaxies in Sloan Digital Sky Survey (SDSS) to subhaloes in the ELUCID simulation, we investigate the relation between subhalo formation time and the galaxy properties, and the dependence of galaxy properties on the cosmic web environment. We find that central and satellite subhaloes have different formation time, where satellite subhaloes are older than central subhaloes at fixed mass. At fixed mass, the galaxy stellar-to-subhalo mass ratio is a good proxy of the subhalo formation time, and increases with the subhalo formation redshifts, especially for massive galaxies. The subhalo formation time is dependent on the cosmic web environment. For central subhaloes, there is a characteristic subhalo mass of $\sim 10^{12} \msun$, below which subhaloes in knots are older than subhaloes of the same mass in filaments, sheets, or voids, while above which it reverses. The cosmic web environmental dependence of stellar-to-subhalo mass ratio is similar to that of the subhalo formation time. For centrals, there is a characteristic subhalo mass of $\sim 10^{12} \msun$, below which the stellar-to-subhalo mass ratio is higher in knots than in filaments, sheets and voids, above which it reverses. Galaxies in knots have redder colors below $10^{12} \msun$, while above $10^{12} \msun$, the environmental dependence vanishes. Satellite fraction is strongly dependent on the cosmic web environment, and decreases from knots to filaments to sheets to voids, especially for low-mass galaxies.

astro-ph.GA↗

arXiv2021

MAHGIC: A Model Adapter for the Halo-Galaxy Inter-Connection

We develop a model to establish the interconnection between galaxies and their dark matter halos. We use Principal Component Analysis (PCA) to reduce the dimensionality of both the mass assembly histories of halos/subhalos and the star formation histories of galaxies, and Gradient Boosted Decision Trees (GBDT) to transform halo/subhalo properties into galaxy properties. We use two sets of hydrodynamic simulations to motivate our model architecture and to train the transformation. We then apply the two sets of trained models to dark matter only (DMO) simulations to show that the transformation is reliable and statistically accurate. The model trained by a high-resolution hydrodynamic simulation, or by a set of such simulations implementing the same physics of galaxy formation, can thus be applied to large DMO simulations to make "mock" copies of the hydrodynamic simulation. The model is both flexible and interpretable, which paves the way for future applications in which we will constrain the model using observations at different redshifts simultaneously and explore how galaxies form and evolve in dark matter halos empirically.

astro-ph.GA↗

arXiv2020

Prime-Aware Adaptive Distillation

Knowledge distillation(KD) aims to improve the performance of a student network by mimicing the knowledge from a powerful teacher network. Existing methods focus on studying what knowledge should be transferred and treat all samples equally during training. This paper introduces the adaptive sample weighting to KD. We discover that previous effective hard mining methods are not appropriate for distillation. Furthermore, we propose Prime-Aware Adaptive Distillation (PAD) by the incorporation of uncertainty learning. PAD perceives the prime samples in distillation and then emphasizes their effect adaptively. PAD is fundamentally different from and would refine existing methods with the innovative view of unequal training. For this reason, PAD is versatile and has been applied in various tasks including classification, metric learning, and object detection. With ten teacher-student combinations on six datasets, PAD promotes the performance of existing distillation methods and outperforms recent state-of-the-art methods.

cs.CV↗

arXiv2020

Galaxy-group (halo) alignments from SDSS DR7 and the ELUCID simulation

Based on galaxies from the Sloan Digital Sky Survey (SDSS) and subhalos in the corresponding reconstructed region from the constrained simulation of ELUCID, we study the alignment of central galaxies relative to their host groups in the group catalog, as well as the alignment relative to the corresponding subhalos in the ELUCID simulation. Galaxies in observation are matched to dark matter subhalos in the ELUCID simulation using a novel neighborhood abundance matching method. In observation, the major axes of galaxies are found to be preferentially aligned to the major axes of their host groups. There is a color dependence of galaxy-group alignment that red centrals have a stronger alignment along the major axes of their host groups than blue centrals. Combining galaxies in observation and subhalos in the ELUCID simulation, we also find that central galaxies have their major axes to be aligned to the major axes of their corresponding subhalos in the ELUCID simulation. We find that the galaxy-group and galaxy-subhalo alignment signals are stronger for galaxies in more massive halos. We find that the alignments between main subhalos and the SDSS matched subhalo systems in simulation are slightly stronger than the galaxy-group alignments in observation.

astro-ph.CO↗

arXiv2020

Relating the structure of dark matter halos to their assembly and environment

We use a large $N$-body simulation to study the relation of the structural properties of dark matter halos to their assembly history and environment. The complexity of individual halo assembly histories can be well described by a small number of principal components (PCs), which, compared to formation times, provide a more complete description of halo assembly histories and have a stronger correlation with halo structural properties. Using decision trees built with the random ensemble method, we find that about $60\%$, $10\%$, and $20\%$ of the variances in halo concentration, axis ratio, and spin, respectively, can be explained by combining four dominating predictors: the first PC of the assembly history, halo mass, and two environment parameters. Halo concentration is dominated by halo assembly. The local environment is found to be important for the axis ratio and spin but is degenerate with halo assembly. The small percentages of the variance in the axis ratio and spin that are explained by known assembly and environmental factors suggest that the variance is produced by many nuanced factors and should be modeled as such. The relations between halo intrinsic properties and environment are weak compared to their variances, with the anisotropy of the local tidal field having the strongest correlation with halo properties. Our method of dimension reduction and regression can help simplify the characterization of the halo population and clarify the degeneracy among halo properties.

astro-ph.GA↗

arXiv2018

ELUCID. VI: Cosmic variance of galaxy distribution in the local Universe

Halo merger trees are constructed from ELUCID, a constrained $N$-body simulation in the Sloan Digital Sky Survey (SDSS) volume. These merger trees are used to populate dark matter halos with galaxies according to an empirical model of galaxy formation. Mock catalogs in the SDSS sky coverage are constructed, which can be used to study the spatial distribution of galaxies in the low-$z$ Universe. These mock catalogs are used to quantify the cosmic variance in the galaxy stellar mass function (GSMF) measured from the SDSS survey. The GSMF estimated from the SDSS magnitude-limited sample can be affected significantly by the presence of the under-dense region at $z<0.03$, so that the low-mass end of the function can be underestimated significantly. Several existing methods designed to deal with the effects of the cosmic variance in the estimate of GSMF are tested, and none is found to be able to fully account for the cosmic variance. We propose a method based on the conditional stellar mass functions in dark matter halos, which can provide an unbiased estimate of the global GSMF. The application of the method to the SDSS data shows that the GSMF has a significant upturn at $M_*< 10^{9.5} h^{-1}{\rm M}_\odot$, which has been missed in many earlier measurements of the local GSMF.

astro-ph.GA↗

arXiv2018

Size distribution of galaxies in SDSS DR7: weak dependence on halo environment

Using a sample of galaxies selected from the Sloan Digital Sky Survey Data Release 7 (SDSS DR7) and a catalog of bulge-disk decompositions, we study how the size distribution of galaxies depends on the intrinsic properties of galaxies, such as concentration, morphology, specific star formation rate (sSFR), and bulge fraction, and on the large-scale environments in the context of central/satellite decomposition, halo environment, the cosmic web: \cluster, \filament, \sheet ~and \void, as well as galaxy number density. We find that there is a strong dependence of the luminosity- or mass-size relation on the galaxy concentration, morphology, sSFR, and bulge fraction. Compared with late-type (spiral) galaxies, there is a clear trend of smaller sizes and steeper slope for early-type (elliptical) galaxies. Similarly, galaxies with high bulge fraction have smaller sizes and steeper slope than those with low bulge fraction. Fitting formula of the average luminosity- and mass-size relations are provided for galaxies of these different intrinsic properties. Examining galaxies in terms of their large scale environments, we find that the mass-size relation has some weak dependence on the halo mass and central/satellite segregation for galaxies within mass range $9.0\le \log M_{\ast} \le 10.5$, where satellites or galaxies in more massive halos have slightly smaller sizes than their counterparts. While the cosmic web and local number density dependence of the mass-size relation is almost negligible.

astro-ph.GA↗

arXiv2018

Mapping the Real Space Distributions of Galaxies in SDSS DR7: II. Measuring the growth rate, clustering amplitude of matter and biases of galaxies at redshift $0.1$

We extend the real-space mapping method developed in Shi et at. (2016) so that it can be applied to flux-limited galaxy samples. We use an ensemble of mock catalogs to demonstrate the reliability of this extension, showing that it allows for an accurate recovery of the real-space correlation functions and galaxy biases. We also demonstrate that, using an iterative method applied to intermediate-scale clustering data, we can obtain an unbiased estimate of the growth rate of structure $fσ_8$, which is related to the clustering amplitude of matter, to an accuracy of $\sim 10\%$. Applying this method to the Sloan Digital Sky Survey (SDSS) Data Release 7 (DR7), we construct a real-space galaxy catalog spanning the redshift range $0.01 \leq z \leq 0.2$, which contains 584,473 galaxies in the north Galactic cap (NGC). Using this data, we infer $\fss$ at a median redshift $z=0.1$, which is consistent with the WMAP9 cosmology at the $1σ$ level. By combining this measurement with the real-space clustering of galaxies and with galaxy-galaxy weak lensing measurements for the same sets of galaxies, we are able to break the degeneracy between $f$, $σ_8$, and $b$. From the SDSS DR7 data alone, we obtain the following cosmological constraints at redshift $z=0.1$: $f=$$0.464^{+0.040}_{-0.040}$, $σ_8=0.769^{+0.121}_{-0.089}$, and $b=1.910^{+0.234}_{-0.268}$, $1.449^{+0.194}_{-0.196}$, $1.301^{+0.170}_{-0.177}$, and $1.196^{+0.159}_{-0.161}~$ for galaxies within different absolute magnitude bins $^{0.1}{\rm M}_r-5\log h=[-23,0, -22.0], [-22,0, -21.0], [-21.0, -20.0]$ and $[-20.0, -19.0]$, respectively.

astro-ph.CO↗

arXiv2018

Full-sky ray-tracing simulation of weak lensing using ELUCID simulations: exploring galaxy intrinsic alignment and cosmic shear correlations

The intrinsic alignment of galaxies is an important systematic effect in weak-lensing surveys, which can affect the derived cosmological parameters. One direct way to distinguish different alignment models and quantify their effects on the measurement is to produce mocked weak-lensing surveys. In this work, we use full-sky ray-tracing technique to produce mock images of galaxies from the ELUCID $N$-body simulation run with the WMAP9 cosmology. In our model we assume that the shape of central elliptical galaxy follows that of the dark matter halo, and spiral galaxy follows the halo spin. Using the mocked galaxy images, a combination of galaxy intrinsic shape and the gravitational shear, we compare the predicted tomographic shear correlations to the results of KiDS and DLS. It is found that our predictions stay between the KiDS and DLS results. We rule out a model in which the satellite galaxies are radially aligned with the center galaxy, otherwise the shear-correlations on small scales are too high. Most important, we find that although the intrinsic alignment of spiral galaxies is very weak, they induce a positive correlation between the gravitational shear signal and the intrinsic galaxy orientation (GI). This is because the spiral galaxy is tangentially aligned with the nearby large-scale overdensity, contrary to the radial alignment of elliptical galaxy. Our results explain the origin of detected positive GI term from the weak-lensing surveys. We conclude that in future analysis, the GI model must include the dependence on galaxy types in more detail.

astro-ph.CO↗

arXiv2018

ELUCID V. Lighting dark matter halos with galaxies

In a recent study, using the distribution of galaxies in the north galactic pole of SDSS DR7 region enclosed in a 500$\mpch$ box, we carried out our ELUCID simulation (Wang et al. 2016, ELUCID III). Here we {\it light} the dark matter halos and subhalos in the reconstructed region in the simulation with galaxies in the SDSS observations using a novel {\it neighborhood} abundance matching method. Before we make use of thus established galaxy-subhalo connections in the ELUCID simulation to evaluate galaxy formation models, we set out to explore the reliability of such a link. For this purpose, we focus on the following a few aspects of galaxies: (1) the central-subhalo luminosity and mass relations; (2) the satellite fraction of galaxies; (3) the conditional luminosity function (CLF) and conditional stellar mass function (CSMF) of galaxies; and (4) the cross correlation functions between galaxies and the dark matter particles, most of which are measured separately for all, red and blue galaxy populations. We find that our neighborhood abundance matching method accurately reproduces the central-subhalo relations, satellite fraction, the CLFs and CSMFs and the biases of galaxies. These features ensure that thus established galaxy-subhalo connections will be very useful in constraining galaxy formation processes. And we provide some suggestions on the three levels of using the galaxy-subhalo pairs for galaxy formation constraints. The galaxy-subhalo links and the subhalo merger trees in the SDSS DR7 region extracted from our ELUCID simulation are available upon request.

astro-ph.GA↗

arXiv2018

Alignment between satellite and central galaxies in the SDSS DR7: dependence on large-scale environment

The alignment between satellites and central galaxies has been studied in detail both in observational and theoretical works. The widely accepted fact is that the satellites preferentially reside along the major axis of their central galaxy. However, the origin and large-scale environment dependence of this alignment are still unknown. In an attempt to figure out those, we use data constructed from SDSS DR7 to investigate the large-scale environmental dependence of this alignment with emphasis on examining the alignments' dependence on the colour of the central galaxy. We find a very strong large-scale environmental dependence of the satellite-central alignment in groups with blue centrals. Satellites of blue centrals in knots are preferentially located perpendicular to the major axis of the centrals, and the alignment angle decreases with environment namely when going from knots to voids. The alignment angle strongly depend on the ${}^{0.1}(g-r)$ colour of centrals. We suggest that the satellite-central alignment is the result of a competition between satellite accretion within large scale-structure and galaxy evolution inside host haloes. For groups containing red central galaxies, the satellite-central alignment is mainly determined by the evolution effect, while for blue central dominated groups, the effect of large-scale structure plays a more important role, especially in knots. Our results provide an explanation for how the satellite-central alignment forms within different large-scale environments. The perpendicular case in groups and knots with blue centrals may also provide insight into understanding similar polar arrangements such the formation of the Milky Way and Centaurus A's satellite system.

astro-ph.GA↗