arXiv subjects

Weiguang Cui

Publications and source records attributed to Weiguang Cui.

At least 55 records · Page 3Linked to original sources

arXiv2024

The Three Hundred project: Estimating the dependence of gas filaments on the mass of galaxy clusters

Galaxy clusters are located in the densest areas of the universe and are intricately connected to larger structures through the filamentary network of the Cosmic Web. In this scenario, matter flows from areas of lower density to higher density. As a result, the properties of galaxy clusters are deeply influenced by the filaments that are attached to them, which are quantified by a parameter known as connectivity. We explore the dependence of gas-traced filaments connected to galaxy clusters on the mass and dynamical state of the cluster. Moreover, we evaluate the effectiveness of the cosmic web extraction procedure from the gas density maps of simulated cluster regions. Using the DisPerSE cosmic web finder, we identify filamentary structures from 3D gas particle distribution in 324 simulated regions of $30 \, h^{-1}$ Mpc side from The Three Hundred hydrodynamical simulation at redshifts z=0, 1, and 2. We estimate the connectivity at various apertures for $\sim3000$ groups and clusters spanning a mass range from $10^{13} \, h^{-1} \, M_{\odot}$ to $10^{15} \, h^{-1} \, M_{\odot}$. Relationships between connectivity and cluster properties like radius, mass, dynamical state and hydrostatic mass bias are explored. We show that the connectivity is strongly correlated with the mass of galaxy clusters, with more massive clusters being on average more connected. This finding aligns with previous studies in literature, both from observational and simulated data sets. Additionally, we observe a dependence of the connectivity on the aperture at which it is estimated. We find that connectivity decreases with cosmic time, while no dependencies on the dynamical state and hydrostatic mass bias of the cluster are found. Lastly, we observe a significant agreement between the connectivity measured from gas-traced and mock-galaxies-traced filaments in the simulation.

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arXiv2024

Galaxy catalogs from the SAGE Semi-Analytic Model calibrated on THE THREE HUNDRED hydrodynamical simulations: A method to push the limits toward lower mass galaxies in dark matter only clusters simulations

The new generation of upcoming deep photometric and spectroscopic surveys will allow us to measure the astrophysical properties of faint galaxies in massive clusters. This would demand to produce simulations of galaxy clusters with better mass resolution than the ones available today if we want to make comparisons between the upcoming observations and predictions of cosmological models. But producing full-physics hydrodynamical simulations of the most massive clusters is not an easy task. This would involve billions of computational elements to reliably resolve low mass galaxies similar to those measured in observations. On the other hand, dark matter only simulations of cluster size halos can be done with much larger mass resolution but at the cost of having to apply a model that populate galaxies within each of the subhalos in these simulations. In this paper we present the results of a new set of dark matter only simulations with different mass resolutions within the THE THREE HUNDRED project. We have generated catalogs of galaxies with stellar and luminosity properties by applying the SAGE Semi-Analytical Model of galaxy formation. To obtain the catalogs consistent with the results from hydrodynamical simulations, the internal physical parameters of SAGE were calibrated with the Particle Swarm Optimization method using a subset of full-physics runs with the same mass resolution than the dark matter only ones.

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arXiv2024

The Three Hundred: The existence of massive dark matter-deficient satellite galaxies in cosmological simulations

The observation of a massive galaxy with an extremely low dark matter content (i.e. NGC 1277) has posed questions about how such objects form and evolve in a hierarchical universe. We here report on the finding of several massive, dark matter-deficient galaxies in a set of 324 galaxy clusters theoretically modelled by means of full-physics hydrodynamical simulations. We first focus on two example galaxies selected amongst the most massive and dark matter-deficient ones. By tracing the evolution of these galaxies, we find that their lack of dark matter is a result of multiple pericentre passages. While orbiting their host halo, tidal interactions gradually strip away dark matter while preserving the stellar component. A statistical analysis of all massive satellite galaxies in the simulated clusters shows that the stellar-to-total mass ratio today is strongly influenced by the number of orbits and the distance at pericentres. Galaxies with more orbits and closer pericentres are more dark matter-deficient. Additionally, we find that massive, dark matter-deficient galaxies at the present day are either the remnants of very massive galaxies at infall or former central galaxies of infalling groups. We conclude that such massive yet dark matter-deficient galaxies exist and are natural by-products of typical cluster galaxy evolution, with no specific requirement for an exotic formation scenario.

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arXiv2024

The Effect of AGN Feedback on the Lyman-α Forest Signature of Galaxy Protoclusters at z~2.3

The intergalactic medium (IGM) in the vicinity of galaxy protoclusters are interesting testbeds to study complex baryonic effects such as gravitational shocks and feedback. Here, we utilize hydrodynamical simulations from the SIMBA and The Three Hundred suites to study the mechanisms influencing large-scale Lyman-$α$ transmission in $2<z<2.5$ protoclusters. We focus on the matter overdensity-Lyman-$α$ transmission relation $(δ_m-δ_F)$ on Megaparsec-scales in these protoclusters, which is hypothesized to be sensitive to the feedback implementations. The lower-density regions represented by the SIMBA-100 cosmological volume trace the power-law $δ_m-δ_F$ relationship often known as the fluctuating Gunn-Peterson approximation. This trend is continued into higher-density regions covered by simulations that implement stellar feedback only. Simulations with AGN thermal and AGN jet feedback , however, exhibit progressively more Lyman-$α$ transmission at fixed matter overdensity. Compared with the 7 protoclusters observed in the COSMOS field, only 2 display the excess absorption expected from protoclusters. The others exhibit deviations: 4 show some increased transparency suggested by AGN X-ray thermal feedback models while the highly transparent COSTCO-I protocluster appears to reflect intense jet feedback. Discrepancies with the stellar-feedback-only model suggests processes at play beyond gravitational heating and/or stellar feedback as the cause of the protocluster transparencies. Some form of AGN feedback is likely at play in the observed protoclusters, and possibly long-ranged AGN jets in the case of COSTCO-I. While more detailed and resolved simulations are required to move forward, our findings open new avenues for probing AGN feedback at Cosmic Noon.

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arXiv2024

The HYENAS project: a prediction for the X-ray undetected galaxy groups

Galaxy groups contain the majority of bound mass with a significant portion of baryons due to the combination of halo mass and abundance (Cui 2024). Hence they serve as a crucial missing piece in the puzzle of galaxy formation and the evolution of large-scale structures in the Universe. In observations, mass-complete group catalogues are normally derived from galaxy redshift surveys detected through various three-dimensional group-finding algorithms. Confirming the reality of such groups, particularly in the X-rays, is critical for ensuring robust studies of galaxy evolution in these environments. Recent works have reported numerous optical groups that are X-ray undetected (see, e.g., Popesso et al. 2024), sparking debates regarding the reasons for the unexpectedly low hot gas fraction in galaxy groups. To address this issue, we utilise zoomed-in simulations of galaxy groups from the novel HYENAS project to explore the range of hot gas fractions within galaxy groups and investigate the intrinsic factors behind the observed variability in X-ray emission. We find that the halo formation time can play a critical role -- we see that groups in halos that formed earlier exhibit up to an order of magnitude brighter X-ray luminosities compared to those formed later. This suggests that undetected X-ray groups are preferentially late-formed halos and highlights the connection between gas fraction and halo formation time in galaxy groups. Accounting for these biases in galaxy group identification is essential for advancing our understanding of galaxy formation and achieving precision in cosmological studies.

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arXiv2024

Reconsidering the dynamical states of galaxy clusters using PCA and UMAP

Numerous metrics exist to quantify the dynamical state of galaxy clusters, both observationally and within simulations. Many of these correlate strongly with one another, but it is not clear whether all of these measures probe the same intrinsic properties. In this work, we use two different statistical approaches -- principal component analysis (PCA) and uniform manifold approximation and projection (UMAP) -- to investigate which dynamical properties of a cluster are in fact the best descriptors of its dynamical state. We use measurements taken directly from The Three Hundred suite of galaxy cluster simulations, as well as morphological properties calculated using mock X-ray and SZ maps of the same simulated clusters. We find that four descriptions of dynamical state naturally arise, and although correlations exist between these, a given cluster can be "dynamically relaxed" according to all, none, or some of these four descriptions. These results demonstrate that it is highly important for future observational and theoretical studies to consider in which sense clusters are dynamically relaxed. Cluster dynamical states are complex and multi-dimensional, and so it is not meaningful to classify them simply as "relaxed" and "unrelaxed" based on a single linear scale.

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arXiv2024

\texttt{Simba}-\texttt{C}: the evolution of the thermal and chemical properties in the intragroup medium

The newly updated \texttt{GIZMO} and \texttt{Simba} based simulation, \texttt{Simba-C}, with its new stellar feedback, chemical enrichment, and recalibrated AGN feedback, allows for a detailed study of the intragroup medium X-ray properties. We discuss the impact of various physical mechanisms, e.g. stellar and AGN feedback, and chemical enrichment, on the composition and the global scaling relations of nearby galaxy groups. We also study the evolution ($z=2$ to $0$) of the global properties for the $1\,\mathrm{keV}$ temperature groups. \texttt{Simba-C} shows improved consistent matching with the observations of all X-ray scaling relations compared to \texttt{Simba}. It is well known that AGN feedback has a significant influence on $L_{X,0.5-2.0}-T_{spec,corr}$, $S_{500/2500}-T_{spec,corr}$, and gas mass fractions, with our \texttt{Simba-C} results consistent with it. Our recalibrated AGN feedback strength also showed an additional improvement in gas entropy, which now aligns with CLoGS observations. The updated stellar feedback and chemical enrichment model is shown to play an important role in our understanding of the chemical abundance ratios and their evolution within galaxy groups. In particular, we find that \texttt{Simba-C} produces an increase in the amount of heavier elements (specifically Si and Fe) relative to O, compared to \texttt{Simba}.

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arXiv2024

How much do we know the halo mass function? Predictions beyond resolution

As a common gravitation virialized object in the standard $Λ$CDM cosmology, dark matter halo connects from the large-scale structure all the way down to galaxy and star formation. However, as the nature of dark matter particles is still unclear, the smallest halo that can be formed in the universe is still unknown. Based on some simple assumptions, this paper uses the \textsc{hmf} package to investigate different halo functions used to quantify its number and mass distributions -- the halo mass function and the integrated/differential mass function (IMF/DMF) respectively. The halo mass in this study extends from the galaxy cluster to the dark matter particle mass at the GeV scale. Surprisingly, different fitting functions for the HMF are in remarkable agreement, a scatter within 2 orders of magnitude, down to dark matter particle mass, of which the halo mass spans about 80 orders of magnitude and the HMF covers over 100 orders of magnitude. The DMF reveals an interesting and consistent peak at $\sim 10^{13} \hMsun$, which implies galaxy groups have the highest contribution to the total matter mass. Furthermore, the effects of cosmology parameters on these halo functions are also examined with the most massive halos, or these halo functions at the most massive halo mass end, more sensitive to them. Different behaviours of these halo functions due to the changes in cosmology parameters can be used to break the degeneracy between them.

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arXiv2024

Generating Galaxy Clusters Mass Density Maps from Mock Multiview Images via Deep Learning

Galaxy clusters are composed of dark matter, gas and stars. Their dark matter component, which amounts to around 80\% of the total mass, cannot be directly observed but traced by the distribution of diffused gas and galaxy members. In this work, we aim to infer the cluster's projected total mass distribution from mock observational data, i.e. stars, Sunyaev-Zeldovich, and X-ray, by training deep learning models. To this end, we have created a multiview images dataset from {\sc{The Three Hundred}} simulation that is optimal for training Machine Learning models. We further study deep learning architectures based on the U-Net to account for single-input and multi-input models. We show that the predicted mass distribution agrees well with the true one.

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arXiv2024

Intrinsic mass-richness relation of clusters from THE THREE HUNDRED hydrodynamic simulations

The main systematics in cluster cosmology is the uncertainty in the mass-observable relation. In this paper, we focus on the most direct cluster observable in optical surveys, i.e. richness, and constrain the intrinsic mass-richness (MR) relation of clusters in THE THREE HUNDRED hydrodynamic simulations with two runs: GIZMO-SIMBA and GADGET-X. We find that modeling the richness at fixed halo mass with a skewed Gaussian distribution yields a simpler and smaller scatter compared to the commonly used log-normal distribution. Additionally, we observe that baryon models have a significant impact on the scatter, while exhibiting no influence on the mass dependence and a slight effect on the amplitude in the MR relation. We select member galaxies based on both stellar mass $M_\star$ and absolute magnitude $\mathscr{M}$. We demonstrate that the MR relation obtained from these two selections can be converted to each other by using the $M_\star-\mathscr{M}$ relation. Finally, we provide a 7-parameter fitting result comprehensively capturing the dependence of the MR relation on both stellar mass cutoff and redshift.

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arXiv2024

ELUCID VIII: Simulating the Coma Galaxy Cluster to Calibrate Model and Understand Feedback

We conducted an investigation of the Coma cluster of galaxies by running a series of constrained hydrodynamic simulations with GIZMO-SIMBA and GADGET-3, based on initial conditions reconstructed from the SDSS survey volume in the ELUCID project. We compared simulation predictions and observations for galaxies, ICM and IGM in and around the Coma cluster to constrain galaxy formation physics. Our results demonstrate that this type of constrained investigation allows us to probe in more detail the implemented physical processes, because the comparison between simulations and observations is free of cosmic variance and hence can be conducted in a ''one-to-one'' manner. We found that an increase in the earlier star formation rate and the supernova feedback of the original GIZMO-SIMBA model is needed to match observational data on stellar, ISM and ICM metallicity. The simulations without AGN feedback can well reproduce the observational ICM electron density, temperature, and entropy profiles, ICM substructures, and the IGM temperature-density relation, while the ones with AGN feedback usually fail. However, one requires something like AGN feedback to reproduce a sufficiently large population of quiescent galaxies, particularly in low-density regions. The constrained simulations of the Coma cluster thus provide a test bed to understand processes that drive galaxy formation and evolution.

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arXiv2024

Identifying Galaxy Cluster Mergers with Deep Neural Networks using Idealized Compton-y and X-ray maps

We present a novel approach to identify galaxy clusters that are undergoing a merger using a deep learning approach. This paper uses massive galaxy clusters spanning $0 \leq z \leq 2$ from \textsc{The Three Hundred} project, a suite of hydrodynamic re-simulations of 324 large galaxy clusters. Mock, idealised Compton-{\it y} and X-ray maps were constructed for the sample, capturing them out to a radius of $2R_{200}$. The idealised nature of these maps mean they do not consider observational effects such as foreground or background astrophysical objects, any spatial resolution limits or restriction on X-ray energy bands. Half of the maps belong to a merging population as defined by a mass increase $Δ${\it M/M} $\geq$ 0.75, and the other half serve as a control, relaxed population. We employ a convolutional neural network architecture and train the model to classify clusters into one of the groups. A best-performing model was able to correctly distinguish between the two populations with a balanced accuracy (BA) and recall of 0.77, ROC-AUC of 0.85, PR-AUC of 0.55 and $F_{1}$ score of 0.53. Using a multichannel model relative to a single channel model, we obtain a 3\% improvement in BA score, and a 6\% improvement in $F_{1}$ score. We use a saliency interpretation approach to discern the regions most important to each classification decision. By analysing radially binned saliency values we find a preference to utilise regions out to larger distances for mergers with respect to non-mergers, greater than $\sim1.2 R_{200}$ and $\sim0.7 R_{200}$ for SZ and X-ray respectively.

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arXiv2024

Characterising the intra-cluster light in The Three Hundred simulations

We characterise the intra-cluster light (ICL) in ensembles of full-physics cluster simulations from The Three Hundred project, a suite of 324 hydrodynamical resimulations of cluster-sized halos. We identify the ICL as those stellar particles bound to the potential of the cluster itself, but not to any of its substructures, and separate the brightest cluster galaxy (BCG) by means of a fixed 50 kpc aperture. We find the total BCG+ICL mass to be in agreement with state-of-the-art observations of galaxy clusters. The ICL mass fraction of our clusters is between 30 and 50 per cent of the total stellar mass within $R_{500}$, while the BCG represents around 10 percent. We further find no trend of the ICL fraction with cluster halo mass, at least not in the range $[0.2,3]\cdot10^{15}h^{-1}M_\odot$ considered here. For the dynamical state, characterised both by theoretical estimators and by the recent merging history of the cluster, there is a clear correlation, such that more relaxed clusters and those that have undergone fewer recent mergers have a higher ICL fraction. Finally, we investigate the possibility of using the ICL to explore the dark matter (DM) component of galaxy clusters. We compute the volumetric density profile for the DM and ICL components and show that, up to $R_{500}$, the ratio between the two can be described by a power law. Working with the velocity dispersion profiles instead, we show that the ratio can be fit by a straight line. Providing the parameters of these fits, we show how the ICL can be used to infer DM properties.

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arXiv2024

The Three Hundred Project: Mapping The Matter Distribution in Galaxy Clusters Via Deep Learning from Multiview Simulated Observations

A galaxy cluster as the most massive gravitationally-bound object in the Universe, is dominated by Dark Matter, which unfortunately can only be investigated through its interaction with the luminous baryons with some simplified assumptions that introduce an un-preferred bias. In this work, we, {\it for the first time}, propose a deep learning method based on the U-Net architecture, to directly infer the projected total mass density map from idealised observations of simulated galaxy clusters at multi-wavelengths. The model is trained with a large dataset of simulated images from clusters of {\sc The Three Hundred Project}. Although Machine Learning (ML) models do not depend on the assumptions of the dynamics of the intra-cluster medium, our whole method relies on the choice of the physics implemented in the hydrodynamic simulations, which is a limitation of the method. Through different metrics to assess the fidelity of the inferred density map, we show that the predicted total mass distribution is in very good agreement with the true simulated cluster. Therefore, it is not surprising to see the integrated halo mass is almost unbiased, around 1 per cent for the best result from multiview, and the scatter is also very small, basically within 3 per cent. This result suggests that this ML method provides an alternative and more accessible approach to reconstructing the overall matter distribution in galaxy clusters, which can complement the lensing method.

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arXiv2024

Prospects for studying the mass and gas in protoclusters with future CMB observations

Protoclusters are the progenitors of massive galaxy clusters. Understanding the properties of these structures is important for building a complete picture of cluster formation and for understanding the impact of environment on galaxy evolution. Future cosmic microwave background (CMB) surveys may provide insight into the properties of protoclusters via observations of the thermal Sunyaev Zel'dovich (SZ) effect and gravitational lensing. Using realistic hydrodynamical simulations of protoclusters from the Three Hundred Project, we forecast the ability of CMB Stage 4-like (CMB-S4) experiments to detect and characterize protoclusters with observations of these two signals. For protoclusters that are the progenitors of clusters at $z = 0$ with $M_{200c} \gtrsim 10^{15}\,M_{\odot}$ we find that the S4-Ultra deep survey has a roughly 20\% chance of detecting the main halos in these structures with SNR > 5 at $z \sim 2$ and a 10\% chance of detecting them at $z \sim 2.5$, where these probabilities include the impacts of noise, CMB foregrounds, and the different possible evolutionary histories of the structures. On the other hand, if protoclusters can be identified using alternative means, such as via galaxy surveys like LSST and Euclid, CMB-S4 will be able to obtain high signal-to-noise measurements of their stacked lensing and SZ signals, providing a way to measure their average mass and gas content. With a sample of 2700 protoclusters at $z = 3$, the CMB-S4 wide survey can measure the stacked SZ signal with a signal-to-noise of 7.2, and the stacked lensing signal with a signal-to-noise of 5.7. Future CMB surveys thus offer exciting prospects for understanding the properties of protoclusters.

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arXiv2023

The impact of halo concentration on the Sunyaev Zel'dovich effect signal from massive galaxy clusters

The Sunyaev Zel'dovich (SZ) effect is sensitive to the pressure of ionized gas inside galaxy clusters, which is in turn controlled largely by the gravitational potential of the cluster. Changing the concentration parameter describing the cluster mass distribution impacts the gravitational potential and thus the cluster SZ signal, with implications for cosmological and other analyses of SZ-selected clusters. We investigate the concentration-SZ relation in theory and simulations. We find that the impact of concentration on the inner SZ profile ($R \lesssim 0.75 R_{200c}$) can be captured with standard polytropic gas models. However, we find that such models do a poor job of reproducing the outer SZ profiles ($R \gtrsim 0.75 R_{200c}$) and the relation between the integrated SZ signal, $Y$, and concentration. This disagreement results from a sharp truncation of the gas pressure profile near the splashback radius, likely caused by virial shocks. We develop a simple description of the truncation that leads to a good match with the simulated SZ profiles out to several $R_{200c}$ for clusters of varying mass and concentration, and that also accurately predicts the concentration-$Y$ relationship. Finally, we determine how inference of the linear bias parameter and splashback radius for SZ-selected clusters can be biased by ignoring the concentration dependence of the SZ signal, finding that bias to the former is essentially negligible, while bias to the latter can be as much as 2\%.

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arXiv2023

Outshining by Recent Star Formation Prevents the Accurate Measurement of High-z Galaxy Stellar Masses

In this paper, we demonstrate that the inference of galaxy stellar masses via spectral energy distribution (SED) fitting techniques for galaxies formed in the first billion years after the Big Bang carries fundamental uncertainties owing to the loss of star formation history (SFH) information from the very first episodes of star formation in the integrated spectra of galaxies. While this early star formation can contribute substantially to the total stellar mass of high-redshift systems, ongoing star formation at the time of detection outshines the residual light from earlier bursts, hampering the determination of accurate stellar masses. As a result, order of magnitude uncertainties in stellar masses can be expected. We demonstrate this potential problem via direct numerical simulation of galaxy formation in a cosmological context. In detail, we carry out two cosmological simulations with significantly different stellar feedback models which span a significant range in star formation history burstiness. We compute the mock SEDs for these model galaxies at z=7 via 3D dust radiative transfer calculations, and then backwards fit these SEDs with Prospector SED fitting software. The uncertainties in derived stellar masses that we find for z>7 galaxies motivate the development of new techniques and/or star formation history priors to model early Universe star formation.

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arXiv2023

Feedback-driven anisotropy in the circumgalactic medium for quenching galaxies in the SIMBA simulations

We use the SIMBA galaxy formation simulation suite to explore anisotropies in the properties of circumgalactic gas that result from accretion and feedback processes. We particularly focus on the impact of bipolar active galactic nuclei (AGN) jet feedback as implemented in SIMBA, which quenches galaxies and has a dramatic effect on large-scale gas properties. We show that jet feedback at low redshifts is most common in the stellar mass range $(1-5)\times 10^{10}M_\odot$, so we focus on galaxies with active jets in this mass range. In comparison to runs without jet feedback, jets cause lower densities and higher temperatures along the galaxy minor axis (SIMBA jet direction) at radii >=$0.5r_{200c}-4r_{200c}$ and beyond. This effect is less apparent at higher or lower stellar masses, and is strongest within green valley galaxies. The metallicity also shows strong anisotropy out to large scales, driven by star formation feedback. We find substantially stronger anisotropy at <=$0.5r_{200c}$, but this also exists in runs with no explicit feedback, suggesting that it is due to anisotropic accretion. Finally, we explore anisotropy in the bulk radial motion of the gas, finding that both star formation and AGN wind feedback contribute to pushing the gas outwards along the minor axis at <=1 Mpc, but AGN jet feedback further causes bulk outflow along the minor axis out to several Mpc, which drives quenching via gas starvation. These results provide observational signatures for the operation of AGN feedback in galaxy quenching.

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