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Jiaxin Han

Publications and source records attributed to Jiaxin Han.

At least 37 records · Page 2Linked to original sources

DarkAI: Reconstructing the density, velocity and tidal field of dark matter from a DESI-like bright galaxy sample

Reconstructing the mass density, velocity, and tidal (MTV) fields of dark matter from galaxy surveys is essential for advancing our understanding of the LSS of the Universe. In this work, we present a machine learning-based framework using a UNet convolutional neural network to reconstruct the MTV fields from mock samples of the DESI bright galaxy survey within the redshift range $0.1 < z < 0.4$. Our approach accounts for realistic observational effects, including geometric selection, flux-limited data, and redshift space distortion (RSD) effects, thereby improving the fidelity of the reconstructed fields. Testing on mock galaxy catalogs generated from the Jiutian N-body simulation, our method achieves significant accuracy level. The reconstructed density field exhibits strong consistency with the true field, effectively eliminating most RSD effects and achieving a cross-correlation power spectrum coefficient greater than 0.985 on scales with $k < 0.1 \, h \, \mathrm{Mpc}^{-1}$. The velocity field reconstruction accurately captures large-scale coherent flows and small-scale turbulent features, exhibiting slopes of grid-to-grid relationships close to unity and scatter below $\sim$100 $\mathrm{km} \, \mathrm{s}^{-1}$. Additionally, the tidal field is reconstructed without bias, successfully recovering the features of the large-scale cosmic web, including clusters, filaments, sheets, and voids. Our results confirm that the proposed framework effectively captures the large-scale distribution and dynamics of dark matter while addressing key systematic challenges. These advancements provide a reliable and robust tool for analyzing current and future galaxy surveys, paving the way for new insights into cosmic structure formation and evolution.

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Assessing subhalo finders in cosmological hydrodynamical simulations

Cosmological simulations are essential for inferring cosmological and galaxy population properties based on forward-modelling, but this typically requires finding the population of (sub)haloes and galaxies that they contain. The properties of said populations vary depending on the algorithm used to find them, which is concerning as it may bias key statistics. We compare how the predicted (sub)halo mass functions, satellite radial distributions and correlation functions vary across algorithms in the dark-matter-only and hydrodynamical versions of the FLAMINGO simulations. We test three representative approaches to finding subhaloes: grouping particles in configuration- (Subfind), phase- (ROCKSTAR and VELOCIraptor) and history-space (HBT-HERONS). We also present HBT-HERONS, a new version of the HBT+ subhalo finder that improves the tracking of subhaloes. We find 10%-level differences in the $M_{\mathrm{200c}}$ mass function, reflecting different field halo definitions and occasional miscentering. The bound mass functions can differ by 75% at the high mass end, even when using the maximum circular velocity as a mass proxy. The number of well-resolved subhaloes differs by up to 20% near $R_{\mathrm{200c}}$, reflecting differences in the assignment of mass to subhaloes and their identification. The predictions of different subhalo finders increasingly diverge towards the centres of the host haloes. The performance of most subhalo finders does not improve with the resolution of the simulation and is worse for hydrodynamical than for dark-matter-only simulations. We conclude that HBT-HERONS is the preferred choice of subhalo finder due to its low computational cost, self-consistently made and robust merger trees, and robust subhalo identification capabilities.

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The mass of the Milky Way from outer halo stars measured by DESI DR1

As a benchmark for galaxy evolution and dark matter studies, the total mass of the Milky Way is a parameter of cosmological significance, and its value at large radii from the Galactic center remains highly uncertain. Following a hierarchical Bayesian inference approach, we measure the cumulative mass of the Milky Way using full 6D phase-space information of stars from the first data release of the Dark Energy Spectroscopic Instrument (DESI). We employ 330 blue horizontal-branch stars (BHBs) and 110 RR Lyrae stars (RRLs) in DESI covering Galactocentric distances in the range $\sim$50--100 kpc. Within 100 kpc from the Galactic center, we report an enclosed mass of $M(<100\ {\rm kpc}) = 0.57^{+0.08}_{-0.07}\times10^{12}$ M$_\odot$ and $M(<100\ {\rm kpc}) = 0.55^{+0.12}_{-0.10}\times10^{12}$ M$_\odot$ when using BHBs and RRLs, respectively. Extrapolating our mass profiles beyond the extent of our data, we find the virial mass of the Galaxy to be $M_{200}=0.85^{+0.16}_{-0.14}\times10^{12}$ M$_\odot$ and $M_{200}=0.78^{+0.19}_{-0.15}\times10^{12}$ M$_\odot$, respectively. We validate the effectiveness and limitations of our method using mock BHBs and RRLs from two AuriDESI halos. These tests show that the code recovers the enclosed mass of the mock galaxy with high precision and accuracy between 50 and 200 kpc, independent of the stellar tracer used and their spatial distribution. The tests also suggest an underestimation of the galaxy's cumulative mass at a level of up to $\sim20$\% if stars close to the Galactic center are used in the models. Our mass estimates lay the groundwork for future inference of the Galactic mass with upcoming DESI data releases and spectroscopic surveys mapping the halo.

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Dependence of halo properties on central-satellite magnitude gaps through weak lensing measurements

The magnitude gap between the central and satellite galaxies encodes information about the mass accretion history of a dark matter halo, and serves as a useful observational probe for the mass distribution in a halo. In this work, we perform the first weak lensing test of the connections between the magnitude gap and the halo profile. We measure the halo profiles of isolated central galaxies (ICGs) selected primarily from the SDSS Main Galaxy Sample. Halo mass and concentration are inferred by fitting stacked lensing profiles in bins of central luminosity, $L_\mathrm{c}$, and the central-satellite magnitude gap, $L_\mathrm{gap}$. We detect dependence on the magnitude gap in both halo properties. The dependence is the strongest in the ICG luminosity range of $10^{10.3}<L_\mathrm{c}[h^{-2}L_\odot]\leq 10^{10.7}$, where halos with smaller gaps have higher masses and lower concentrations. When $10^{10.7} <L_c[h^{-2}L_\odot] \leq 10^{11.1}$, however, no significant gap dependence is detected. In the range of $10^{9.9}<L_\mathrm{c}[h^{-2}L_\odot] \leq 10^{10.3}$, a disordering of the gap dependence is marginally observable. We compare the observational results with predictions by two lightcone catalogs built from the Illustris TNG300 and the Millennium simulations. The gap dependence in the two mock samples show overall consistency with observations, but neither matches them in all $L_\mathrm{c}$ bins to a quantitative level. We also compare the significance of the gap dependence on halo mass and concentration and find that our measurement prefers gap dependence in both parameters, while the halo mass dependence is preferred over the concentration if only one of the two dependencies is allowed.

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SpecDis: Value added distance catalogue for 4 million stars from DESI Year-1 data

We present the SpecDis value added stellar distance catalog accompanying DESI DR1. SpecDis trains a feed-forward Neural Network (NN) with Gaia parallaxes and gets the distance estimates. To build up unbiased training sample, we do not apply selections on parallax error or signal-to-noise (S/N) of the stellar spectra, and instead we incorporate parallax error into the loss function. Moreover, we employ Principal Component Analysis (PCA) to reduce the noise and dimensionality of stellar spectra. Validated by independent external samples of member stars with precise distances from globular clusters (GCs), dwarf galaxies, stellar streams, combined with blue horizontal branch (BHB) stars, we demonstrate that our distance measurements show no significant bias up to 100kpc, and are much more precise than Gaia parallax beyond 7kpc. The median distance uncertainties are 23%, 19%, 11% and 7% for S/N $<$ 20, 20 $\leq$ S/N$<$ 60, 60 $\leq$ S/N $<$ 100 and S/N $\geq$ 100. Selecting stars with $\log g<3.8$ and distance uncertainties smaller than 25%, we have more than 74,000 giant candidates within 50kpc to the Galactic center and 1,500 candidates beyond this distance. Additionally, we develop a Gaussian mixture model to identify unresolvable equal-mass binaries by modeling the discrepancy between the NN-predicted and the geometric absolute magnitudes from Gaia parallaxes and identify 120,000 equal-mass binary candidates. Our final catalog provides distances and distance uncertainties for $>$ 4 million stars, offering a valuable resource for Galactic astronomy.

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Self-similar decomposition of the hierarchical merger tree of dark matter halos

In the $Λ$CDM universe, structure formation is generally not a self-similar process, while some self-similarity remains in certain statistics which can greatly simplify our description and understanding of the cosmic structures. In this work, we show that the merger tree of dark matter halos is approximately self-similar by investigating the universality of the subhalo peak mass function (PMF) describing the mass distribution of progenitor halos. Using a set of cosmological simulations and identifying subhalos of different merger levels with HBT+, we verify that the level-1 subhalo PMF is close to universal across halo mass, redshift, and cosmology. This approximate self-similarity allows us to analytically derive the subhalo PMF for subhalos accreted at any level (i.e., for sub-sub...halos) through self-convolutions of the level-1 PMF, and the resulting model shows good agreement with simulation measurements. We further derive a number of analytical properties on the hierarchical origin of subhalos. We show that higher-level subhalos dominate at progressively lower peak mass in the PMF and are more likely to originate from major mergers than lower-level ones. At a given merger mass ratio, the subhalo accretion rates at each level track the growth rate of the host halo. At a fixed final mass ratio, however, subhalos of higher-level, higher-mass-ratio and in more massive haloes tend to be accreted more recently. Matching subhalo peak mass to galaxy mass, these results have direct implications on the hierarchical origin of satellite galaxies.

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CSST Cosmological Emulator I: Matter Power Spectrum Emulation with one percent accuracy to k = 10 h/Mpc

In the near future, the China Space Station Telescope (CSST) will obtain unprecedented imaging and spectroscopic data. The statistical errors in the cosmological parameter constraints will be reduced significantly. The corresponding theoretical tools must meet the percent-level accuracy required to extract as much cosmological information as possible from the observations. We present the CSST Emulator to provide nonlinear power spectrum predictions in the eight cosmological parameter space $Ω_\mathrm{cb},Ω_\mathrm{b},H_{0},n_{s},A_{s},w_{0}, w_{a}$, and $m_ν$. It is constructed based on the Kun simulation suite, consisting of 129 high-resolution simulations with box size $L=1\,h^{-1} {\rm Gpc}$ and evolving $3072^3$ particles. The determinations of parameter ranges, sampling method, and emulation strategy in the whole construction have been optimized exquisitely. This enables our prediction for $k\leq 10\,h {\rm Mpc}^{-1}$ and $z\leq 2.0$ to reach $1\%$ accuracy validated through internal and external simulations. We also compare our results with recent BACCO, EuclidEmulator2, and Mira-Titan IV emulators, which demonstrate the CSST Emulator's excellent performance across a wide cosmological parameter range in the nonlinear regime. CSST Emulator is publicly released at https://github.com/czymh/csstemu, and provides a fundamental theoretical tool for accurate cosmological inference with future CSST observations.

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The Jiutian simulations for the CSST extra-galactic surveys

We provide an overview of the Jiutian simulations, a hybrid simulation suite for the China Space Survey Telescope (CSST) extragalactic surveys. It consists of four complementary modules: the primary runs with high resolutions with the fiducial concordance cosmology, the emulator runs exploring the parameter uncertainties around the fiducial cosmology, the reconstruction runs intended for recovering the observed Universe position by position, and the extension runs employing extended cosmologies beyond the standard model. For the primary runs, two independent pipelines are adopted to construct subhaloes and merger trees. On top of them, four sets of mock galaxy light-cone catalogs are produced from semi-analytical models and subhalo abundance matching, providing a variety of observational properties including galaxy SED, emission lines, lensing distortions, and mock images. The 129 emulator runs are used to train the CSST emulator, achieving one percent accuracy in predicting the matter power spectrum over $k\leq 10h{\rm Mpc}^{-1}$ and $z\leq 2$. The reconstruction runs employ a number of subgrid baryonic models to predict the evolution and galaxy population resembling certain regions in the real Universe with constrained initial conditions, enabling controlled investigation of galaxy formation on top of structure formation. The extension runs cover models with warm dark matter, $f(R)$ gravity, interacting dark energy, and nonzero neutrino masses, revealing differences in the cosmic structure under alternative cosmological models. We introduce the specifications for each run, the data products derived from them, the corresponding pipeline developments, and present some main tests. Using the primary runs, we also show that the subhalo peak mass functions of different levels are approximately universal. These simulations form a comprehensive and open library for CSST surveys and beyond.

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Luminosity and stellar mass functions of faint photometric satellites around spectroscopic central galaxies from DESI Year-1 Bright Galaxy Survey

We measure the luminosity functions (LFs) and stellar mass functions (SMFs) of photometric satellite galaxies around spectroscopically identified isolated central galaxies (ICGs). The photometric satellites are from the DESI Legacy Imaging Surveys (DR9), while the spectroscopic ICGs are selected from the DESI Year-1 BGS sample. We can measure satellite LFs down to $r$-band absolute magnitudes of $M_{r,\mathrm{sat}}\sim-7$, around ICGs as small as $7.1<\log_{10}M_{\ast,\mathrm{ICG}}/\mathrm{M_\odot}<7.8$, with the stellar mass of ICGs measured by the DESI Fastspecfit pipeline. The satellite SMF can be measured down to $\log_{10}M_{\ast,\mathrm{sat}}/\mathrm{M_\odot}\sim 5.5$. Interestingly, we discover that the faint/low-mass end slopes of satellite LFs/SMFs become steeper with the decrease in the stellar masses of host ICGs, with smaller and nearby host ICGs capable of being used to probe their fainter satellites.. The steepest slopes are $-2.298\pm0.656$ and $-$2.888$\pm$0.916 for satellite LF and SMF, respectively. Detailed comparisons are performed between the satellite LFs around ICGs selected from DESI BGS or from the SDSS NYU-VAGC spectroscopic Main galaxies over $7.1<\log_{10}M_{\ast,\mathrm{ICG}}/\mathrm{M_\odot}<11.7$, showing reasonable agreements, but we show that the differences between DESI and SDSS stellar masses for ICGs play a role to affect the results. We also compare measurements based on DESI Fastspecfit and Cigale stellar masses used to bin ICGs, with the latter including the modeling of AGN based on WISE photometry, and we find good agreements in the measured satellite LFs by using either of the DESI stellar mass catalogs.

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Einasto profile as the halo model solution coupled to the depletion radius

We constrain the halo profiles outside the halo boundaries by solving for the matching profiles required by the halo model. In the halo model framework, the matter distribution in the universe can be decomposed into the spatial distribution of halos convolved with their internal structures. This leads to a set of linear equations in Fourier space which uniquely determines the matching halo profiles for any given halo catalog. In this work, we construct three halo catalogs with different boundary definitions, and solve for the matching profiles in each case using measurements of halo-matter and halo-halo power spectra. Our results show that for a given halo field, there is always a set of matching profiles to accurately reconstruct the input statistics of the matter field, even though it might be complex to model the profiles analytically. Comparing the solutions from different halo catalogs, we find their mass distributions inside the inner depletion radii are nearly identical, while they deviate from each other on larger scales, with a larger boundary resulting in a more extended profile. For the depletion radius based catalog, the numerical solution agrees well with the Einasto profile. Coupling the Einasto profile with the depletion catalog, the resulting halo model can simultaneously predict the halo-matter power spectra to $10\%$ and matter-matter power spectrum to $5\%$, improving over conventional models in both the interpretability and versatility. The conditions and limitation of using the Navarro-Frenk-White profile in the halo model are also discussed.

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emPDF: Inferring the Milky Way mass with data-driven distribution function in phase space

We introduce the emPDF (Empirical Distribution Function), a novel dynamical modeling method that infers the gravitational potential from kinematic tracers with optimal statistical efficiency under the minimal assumption of steady state. emPDF determines the best-fit potential by maximizing the similarity between instantaneous kinematics and the time-averaged phase-space distribution function (DF), which is empirically constructed from observation upon the theoretical foundation of oPDF (Han et al. 2016). This approach eliminates the need for presumed functional forms of DFs or orbit libraries required by conventional DF- or orbit-based methods. emPDF stands out for its flexibility, efficiency, and capability in handling observational effects, making it preferable to the popular Jeans equation or other minimal assumption methods, especially for the Milky Way (MW) outer halo where tracers often have limited sample size and poor data quality. We apply emPDF to infer the MW mass profile using Gaia DR3 data of satellite galaxies and globular clusters, obtaining enclosed masses of $M(<r)=26\pm8, 46\pm8, 90\pm13$, and $149\pm40 \times 10^{10}M_\odot$ at r=30, 50, 100, and 200 kpc, respectively. These are consistent with the updated constraints from simulation-informed DF fitting (Li et al. 2020). While the simulation-informed DF offers superior precision owing to the additional information extracted from simulations, emPDF is independent of such supplementary knowledge and applicable to general tracer populations. emPDF is currently implemented for tracers with complete 6D kinematics within spherical potentials, but it can potentially be extended to address more general problems.

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Photometric Objects Around Cosmic Webs (PAC) Delineated in a Spectroscopic Survey. VIII. Revisiting the Lensing is Low Effect

The issue of over-predicting the galaxy-galaxy lensing (GGL) signal using conventional galaxy-halo connection models has become well-known as the ``Lensing is Low'' problem, which has been extensively investigated using the Baryon Oscillation Spectroscopic Survey (BOSS) galaxy samples. This issue is also tightly related to the so-called $S_8$ tension. By applying our Photometric objects Around Cosmic webs (PAC) method to the BOSS survey and the DESI deep photometric survey, we obtained hundreds of cross-correlation measurements to establish an accurate galaxy-halo connection for BOSS galaxies through the halo abundance matching technique (Paper IV). With this galaxy-halo connection, we show in this work that the predicted GGL signals for BOSS galaxies both in the Planck and WMAP Universes actually agree very well with the GGL measurements. We find the best-fitting value $S_8 = 0.8294 \pm 0.0110$, $0.8073 \pm 0.0372$ and $0.8189 \pm 0.0440$ for the CMASS samples with the source galaxies from HSC, DES and KiDS image surveys, respectively. Our work indicates that accurate modeling of the lens population is so critical to interpret the GGL observation. For the scale of $r_p < 0.6\,h^{-1}\rm{Mpc}$, our GGL prediction for LOWZ samples are also in good agreement with the observations of HSC and DES. However, the GGL observation of KiDS is much lower on the small scale. Our results indicate that no significant baryon feedback is needed to suppress the small scale clustering unless the the GGL observation of KiDS on the small scale will be confirmed.

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The mass and redshift dependence of halo star clustering

We adopt the two point correlation function (2PCF) as a statistical tool to quantify the spatial clustering of halo stars, for galaxy systems spanning a wide range in host halo virial mass ($11.25<\log_{10}M_{200c}/\mathrm{M}_\odot<15$) and redshifts ($0<z<1.5$) from the IllustrisTNG simulations. Consistent with a previous study \cite[][Paper I]{2024ApJ...961..223Z}, we identify clear correlations between the strength of the 2PCF signals and galaxy formation redshifts, but over a much wider mass range. We find that such correlations are slightly stronger at higher redshifts, and get weakened with the increase of host halo mass. We demonstrate that the spatial clustering of halo stars is affected by two factors: 1) the clustering gets gradually weakened as time passes (phase mixing); 2) newly accreted stars at more recent times would increase the clustering. For more massive galaxy systems, they assemble late and the newly accreted stars would increase the clustering. The late assembly of massive systems may also help to explain the weaker correlations between the 2PCF signals and the galaxy formation redshifts in massive halos, as their 2PCFs are affected more by recently accreted stars, while formation redshift characterizes mass accretion on a much longer timescale. We find that the orbits of satellite galaxies in more massive halos maintain larger radial anisotropy, reflecting the more active accretion state of their hosts while also contributing to their stronger mass loss rates.

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Why artificial disruption is not a concern for current cosmological simulations

Recent studies suggest that cold dark matter subhalos are hard to disrupt and almost all cases of subhalo disruption observed in numerical simulations are due to numerical effects. However, these findings primarily relied on idealized numerical experiments, which do not fully capture the realistic conditions of subhalo evolution within a hierarchical cosmological context. Based on the Aquarius simulations, we identify clear segregation in the population of surviving and disrupted subhalos, which corresponds to two distinct acquisition channels of subhalos. We find that all of the first-order subhalos accreted after redshift 2 survive to the present time without suffering from artificial disruption. On the other hand, most of the disrupted subhalos are sub-subhalos accreted at high redshift. Unlike the first-order subhalos, sub-subhalos experience pre-processing and many of them are accreted through major mergers at high redshift, resulting in very high mass loss rates. We confirm these high mass loss rates are physical through both numerical experiments and semi-analytical modeling, thus supporting a physical origin for their rapid disappearance in the simulation. Even though we cannot verify whether these subhalos have fully disrupted or not, their extreme mass loss rates dictate that they can at most contribute a negligible fraction to the very low mass end of the subhalo mass function. We thus conclude that current state-of-the-art cosmological simulations have reliably resolved the subhalo population.

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How does the velocity anisotropy of halo stars, dark matter and satellite galaxies depend on host halo properties?

We investigate the mass ($M_{200}$) and concentration ($c_{200}$) dependencies of the velocity anisotropy ($β$) profiles for different components in the dark matter halo, including halo stars, dark matter and subhalos, using systems from the IllustrisTNG simulations. Beyond a critical radius, $β$ becomes more radial with the increase of $M_{200}$, reflecting more prominent radial accretion around massive halos. The critical radius is $r\sim r_s$, $0.3~r_s$ and $r_s$ for halo stars, dark matter and subhalos, with $r_s$ the scale radius of host halos. This dependence on $M_{200}$ is the strongest for subhalos, and the weakest for halo stars. In central regions, $β$ of halo stars and dark matter particles gets more isotropic with the increase of $M_{200}$ in TNG300 due to baryons. By contrast, $β$ of dark matter from the dark matter only TNG300-Dark run shows much weaker dependence on $M_{200}$ within $r_s$. Dark matter in TNG300 is slightly more isotropic than in TNG300-Dark at $0.2~r_s r_s$ as $β_\mathrm{star}-β_\mathrm{DM}=(-0.028 \pm 0.008)\log_{10}M_{200}/M_\odot + (0.690\pm0.010)$.

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PAC.V. The Roles of Mass and Environment in the Quenching of Galaxies

The roles that mass and environment play in the galaxy quenching are still under debate. Leveraging the Photometric objects Around Cosmic webs (PAC) method, we analyze the excess surface distribution $\bar{n}_2w_{\rm{p}}(r_{\rm{p}})$ of photometric galaxies in different color (rest-frame $u-r$) within the stellar mass range of $10^{9.0}M_{\odot}\sim10^{11.0}M_{\odot}$ around spectroscopic massive central galaxies ($10^{10.9}\sim10^{11.7}M_{\odot}$) at the redshift interval $0<z_s<0.7$, utilizing data from the Hyper SuprimeCam Subaru Strategic Program and the spectroscopic samples of Slogan Digital Sky Survey (i.e. Main, LOWZ and CMASS samples). We find that both mass and environment quenching contribute to the evolution of companion galaxies. To isolate the environment effect, we quantify the quenched fraction excess (QFE) of companion galaxies encircling massive central galaxies within $0.01h^{-1}{\rm{Mpc}}<r_{\rm{p}}<20h^{-1}\rm{Mpc}$, representing the surplus quenched fraction relative to the average. We find that the high density halo environment affects the star formation quenching up to about three times of the virial radius, and this effect becomes stronger at lower redshift. We also find that even after being scaled by the virial radius, the environment quenching efficiency is higher for more massive halos or for companion galaxies of higher stellar mass, though the trends are quite weak. We present a fitting formula that comprehensively captures the QFE across central and companion stellar mass bins, halo-centric distance bins, and redshift bins, offering a valuable tool for constraining galaxy formation models. Furthermore, we have made a quantitative comparison with Illustris-TNG that underscores some important differences, particularly in the excessive quenching of low-mass companion galaxies ($<10^{9.5}M_{\odot}$) by TNG.

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Inferring the mass content of galaxy clusters with satellite kinematics and Jeans Anisotropic modeling

Satellite galaxies can be used to indicate the dynamical mass of galaxy groups and clusters. In this study, we apply the axis-symmetric Jeans Anisotropic Multi-Gaussian Expansion JAM modeling to satellite galaxies in 28 galaxy clusters selected from the TNG300-1 simulation with halo mass of $\log_{10}M_{200}/M_\odot>14.3$. If using true bound satellites as tracers, the best constrained total mass within the half-mass radius of satellites, $M(<r_\mathrm{half})$, and the virial mass, $M_{200}$, have average biases of -0.01 and $0.03$~dex, with average scatters of 0.11~dex and 0.15~dex. If selecting companions in redshift space with line-of-sight depth of 2,000~km/s, the biases are -0.06 and $0.01$~dex, while the scatters are 0.12 and 0.18~dex for $M(<r_\mathrm{half})$ and $M_{200}$. By comparing the best-fitting and actual density profiles, we find $\sim$29% of best-fitting density profiles show very good agreement with the truth, $\sim$32% display over or under estimates at most of the radial range with biased $M(<r_\mathrm{half})$, and 39% show under/over estimates in central regions and over/under estimates in the outskirts, with good constraints on $M(<r_\mathrm{half})$, yet most of the best constraints are still consistent with the true profiles within 1-$σ$ statistical uncertainties for the three circumstances. Using a mock DESI Bright Galaxy Survey catalog with the effect of fiber incompleteness, we find DESI fiber assignments and the choice of flux limits barely modify the velocity dispersion profiles and are thus unlikely to affect the dynamical modeling outcomes. Our results show that with current and future deep spectroscopic surveys, JAM can be a powerful tool to constrain the underlying density profiles of individual massive galaxy clusters.

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Cosmological Forecast of the Void Size Function Measurement from the CSST Spectroscopic Survey

Void size function (VSF) contains information of the cosmic large-scale structure (LSS), and can be used to derive the properties of dark energy and dark matter. We predict the VSFs measured from the spectroscopic galaxy survey operated by the China Space Station Telescope (CSST), and study the strength of cosmological constraint. We employ a high-resolution Jiutian simulation to get CSST galaxy mock samples based on an improved semi-analytical model. We identify voids from this galaxy catalog using the watershed algorithm without assuming a spherical shape, and estimate the VSFs at different redshift bins from $z=0.5$ to 1.1. We propose a void selection method based on the ellipticity, and assume the void linear underdensity threshold $δ_{\rm v}$ in the theoretical model is redshift-dependent and set it as a free parameter in each redshift bin. The Markov Chain Monte Carlo (MCMC) method is adopted to implement the constraints on the cosmological and void parameters. We find that the CSST VSF measurement can constrain the cosmological parameters to a few percent level. The best-fit values of $δ_{\rm v}$ are ranging from $\sim-0.4$ to $-0.1$ as the redshift increases from 0.5 to 1.1, which has a distinct difference from the theoretical calculation with $δ_{\rm v}\simeq-2.7$ assuming the spherical evolution and using particles as tracer. Our method can provide a good reference for void identification and selection in the VSF analysis of the spectroscopic galaxy surveys.

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