arXiv subjects

Weiguang Cui

Publications and source records attributed to Weiguang Cui.

At least 19 recordsLinked to original sources

arXiv2026

Black Hole-Galaxy Correlations in Cluster Zoomed-in Simulations: GIZMO-SIMBA and TNG-Cluster

We investigate the co-evolution of supermassive black holes (SMBHs) and central galaxies in massive clusters using the GIZMO-SIMBA and TNG-Cluster zoom-in simulations at $z=0-5$. We find that the distinct subgrid physics of these two models suggest fundamentally different evolutionary pathways. On the one hand, GIZMO-SIMBA, employs torque-limited accretion and predicts a supply-driven scenario where the SMBHs rapidly assemble synchronized with dark matter halo ($M_{200c}$) growth (i.e. the halo mass-BH mass relation is set by $z=3.0$ and similar to the present-day relationship). On the other hand, TNG-Cluster, exhibits a feedback-regulated growth phase delayed by an early thermal suppression. While both models successfully reproduce some local black hole-galaxy scaling relations, they imply significantly different evolution for these relations. Analysis of the BH mass-gas mass ratio relations suggests that TNG-Cluster's isotropic kinetic winds efficiently deplete cold gas, resulting in a "hard quench" of star formation. In the black hole accretion rate (BHAR)-star formation rate (SFR) relation we find that both simulations successfully reproduce the decoupling of BHAR and star formation observed in recent massive cluster ellipticals. The divergent evolutionary trends emphasize the importance of the multiphase intracluster medium; while these subgrid models do not have the necessary resolution and employ distinct formalisms, the sustained BHAR in quenched systems resemble outcomes broadly consistent with modern multiphase feeding paradigms such as chaotic cold accretion in turbulent cluster cores. Furthermore, we demonstrate that for both models, black hole mass is a primary regulator of atomic and molecular gas depletion in galaxy clusters.

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arXiv2026

ELUCID-DESI II. Revealing dark matter mass, tidal, and velocity (MTV) fields using galaxy group phase information

We introduce a novel method for reconstructing the cosmic mass, tidal, and velocity (MTV) fields over the redshift range $0 < z < 0.6$ using the phase information of galaxy groups. This approach replaces the explicit theoretical bias correction typically needed to relate galaxy groups to the underlying dark matter density field with a simulation-calibrated statistical mapping, reducing a major source of systematic uncertainty and making the method directly applicable to spectroscopic redshift surveys such as the DESI Bright Galaxy Survey (BGS). We evaluate the performance of our MTV reconstruction pipeline with mock redshift surveys that include a comprehensive set of observational selection effects. The galaxy groups used as tracers are identified with an extended halo-based group finder applied to the DESI mock galaxy catalogue with an apparent magnitude limit of $m_z < 19.65$, yielding a galaxy number comparable to that of the DESI BGS faint sample ($m_r < 20.175$). Our tests show that the reconstructed velocities are accurate and unbiased, with a residual dispersion of $\sim 120\ \mathrm{km\,s^{-1}}$ across the redshift bins. The recovered velocity field allows us to shift galaxy groups to their real-space positions, thereby correcting for the Kaiser effect. By iteratively applying this Kaiser correction to the galaxy groups, we further reconstruct the tidal field and the mass-density distribution. The reconstruction is stable with respect to the grid resolution. Overall, our results demonstrate that this group-based phase-space reconstruction provides a robust pathway to recovering the dark matter MTV fields, with strong prospects for application to DESI BGS data.

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arXiv2026

Identifying backsplash galaxies using machine learning

The galaxy population in the outskirts of a cluster contains members that have been pre-processed in groups and filaments, as well as backsplash galaxies -- those that have recently passed through the cluster's center. However, disentangling these two pathways is challenging observationally. In this work, we present a machine-learning-powered model, trained on simulations of galaxy clusters from The Three Hundred suite of simulations, which can identify individual backsplash galaxies in astronomical observations. This model can build samples of backsplash galaxies with a purity and completeness of up to ~70%, and galaxies on their first infall with a purity and completeness of over 80%. It can be tuned to optimise either of these two metrics, and can be used with any combination of a set of observable quantities. We have also applied this model to galaxies with asymmetric HI distributions in the Virgo Cluster, and have demonstrated that these galaxies are all likely approaching the cluster for the first time. This supports the idea that cold gas is removed from these galaxies soon after entering a cluster, and demonstrates how this classifier can provide a better understanding of which properties of galaxies are caused by a previous passage through a cluster. We have made this model publicly available in the form of a web app, with a link in the Conclusions of this paper.

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arXiv2026

The AGORA High-resolution Galaxy Simulations Comparison Project. IX - Part 1: Effects of a Major Galaxy Merger on Star Formation of a Milky Way-mass Galaxy Progenitor

Given their highly nonlinear dynamics and sensitivity to initial conditions, galaxy mergers are a compelling area to conduct a simulation code comparison. We perform a comparative study of a major galaxy merger at $z \approx 4.5$ in cosmological zoom-in hydrodynamic simulations of a Milky Way-mass galaxy progenitor. The comparison employs the AGORA CosmoRun suite of nine well-calibrated, state-of-the-art numerical codes, each adopting a different stellar feedback scheme. We find that the evolution of the star formation rate (SFR) during the interaction is strongly shaped by the stellar feedback type. Using kinetic feedback in the feedback model drives a pronounced merger-induced starburst that starts to subside before coalescence; using thermal feedback without kinetic feedback yields prolonged SFR growth even after coalescence; and using delayed cooling or radiation pressure results in highly fluctuating SFR. Tracking gas particles in particle-based codes reveals that kinetic feedback facilitates gas inflow from the secondary galaxy onto the primary galaxy between the first periapsis and apoapsis, thus producing an earlier and more prominent starburst. In contrast, thermal feedback, augmented by superbubble or delayed-cooling feedback, suppresses gas cooling, creates a more extended gas distribution, and hinders strong starbursts during the merger. We also observe an inverse correlation between burst fraction and pre-merger gas fraction that is independent of feedback models. Overall, these results highlight the sensitivity of simulated galaxy mergers' star formation response to stellar feedback prescriptions. This study indicates that galaxy mergers may serve as a good testbed for stellar feedback processes in cosmological simulations.

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arXiv2026

The AGORA High-resolution Galaxy Simulations Comparison Project. IX - Part 2: Effects of a Major Galaxy Merger on the Stellar Morphology of a Milky Way-mass Galaxy Progenitor

Galaxy mergers, with their high sensitivity to initial conditions, provide a valuable setting for comparative studies of galaxy simulation codes. Following our first paper focusing on merger-driven star formation, we present a code comparison examining the morphological transformation impact of a major galaxy merger at $z \approx 4.5$ on a Milky Way-mass galaxy progenitor. Our analysis employs nine state-of-the-art codes from the AGORA CosmoRun cosmological zoom-in simulation suite. For this merger, we show that the adopted stellar feedback type influences the galaxy's compaction and stellar disc formation. Codes with purely thermal feedback produce a merger remnant that forms a disc and becomes compact primarily during and after coalescence; codes that include kinetic feedback begin disc formation and compaction around the first periapsis; and codes with strong delayed cooling or superbubble feedback suppress disc formation and produce a more extended remnant. In contrast, the orientation of the remnant disc is code-independent. In all codes, the rotational angular momentum of the remnant disc aligns with the interaction's orbital angular momentum rather than the pre-merger rotational axis, implying that the infalling gas preserves its orbital angular momentum to form a new disc. Comparisons with the Santa Cruz semi-analytic model show reasonable agreement in stellar mass and half-mass radius, yet the model underpredicts (overpredicts) the dark matter fraction and velocity dispersion for codes exhibiting strong compaction (expansion). The systematic dependence of our remnants' morphology on feedback schemes demonstrates that merger remnant morphology may serve as a powerful probe of stellar feedback processes.

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arXiv2026

Probing the baryonic--dark matter connection in galaxy clusters using X-rays with gated recurrent unit neural networks

Accurate cluster mass measurements are crucial for cosmology, yet conventional hydrostatic equilibrium (HSE) methods can suffer from systematic biases, particularly in dynamically disturbed systems. We present a gated recurrent unit (GRU) based deep learning framework for predicting three-dimensional mass profiles of galaxy clusters from spherically averaged intra-cluster medium (ICM) radial profiles. By treating ICM profiles as sequential data, the GRU captures radial dependencies and naturally handles profiles with different radial samplings. We train and validate the model using high-resolution hydrodynamical simulations from The Three Hundred Project, achieving unbiased mass predictions with a typical 1$\sigma$ scatter of $\sim$5% over most of the cluster region, significantly improving upon HSE estimates. The model provides radius-dependent uncertainty estimates and remains robust against variations in data quality and cluster morphology. When trained jointly on independent simulation suites (GIZMO-SIMBA and GADGET-X), it successfully generalises across both simulations. Feature importance analysis shows that enclosed gas mass is the dominant predictor, with pressure and temperature providing additional information on the radial mass distribution. We further apply the GRU model to X-ray observations of the REXCESS and X-COP cluster samples from XMM-Newton and compare the inferred mass profiles with HSE estimates. The HSE masses are systematically lower than the GRU predictions for the higher-mass X-COP sample, while the REXCESS sample shows mass differences that are close to zero on average. This work provides a data-driven framework for cluster mass inference that bridges simulations and observations and can be extended to multi-wavelength datasets, including Sunyaev-Zel'dovich and optical observations.

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arXiv2026

The Three Hundred project: Low Gas Fraction Galaxy Clusters properties and their environment

Galaxy cluster samples based on X-ray and Sunyaev-Zel'dovich (SZ) observations are affected by selection biases. These catalogs preferentially include systems with high gas content and surface brightness. Excluding objects with depleted gas content, low-gas-fraction clusters (LGFCs), could lead to an incomplete sampling. We aim to investigate the abundance and the properties of the LGFCs population using The Three Hundred hydrodynamical simulations, focusing on the Gadget-X code. In particular, we study outliers in the $f_{\mathrm{g},500} - M_{500}$ relation, environmental influences, and their behavior in key scaling relations, with a focus on the Compton-Y observable. We analyze a sample of $N_{\mathrm{tot}} = 9858$ simulated objects from The Three Hundred, in the redshift band $z \in [0;0.817]$. LGFCs are selected statistically as outliers of the $f_{\mathrm{g},500}-M_{500}$ relation. To analyze environmental effects, we compare the gas density and temperature radial profiles of LGFCs against the No-LGFCs population. Finally, we study how the temperature, entropy, and spherical Compton parameter scaling relations are affected by the inclusion of LGFCs. We find that LGFCs are preferentially found at the low-mass end and their abundance increases toward low redshift. Radial profiles of LGFCs show lower gas concentrations in the core regions and higher temperatures, suggesting a more diffuse and heated ICM. This behavior is also reflected in the entropy scaling relation, where LGFCs are extreme positive outliers. Contrary to observations, the $Y_{\mathrm{sph},500}$ values of LGFCs show no significant deviation from the general population. Nevertheless, we cannot rule out that these differences are partly driven by the mass incompleteness at the low-mass end and the environmental bias of our simulated sample.

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arXiv2026

Here, There and Everywhere: How AGN jets affect galaxy cluster environments

Active galactic nuclei (AGN) feedback via black hole-driven jets and winds plays a key role in redistributing matter across megaparsec scales. However, the implementation of jet feedback in cosmological simulations remains highly prescriptive, leading to uncertainties in the predicted state of the Warm-Hot Intergalactic Medium and other extragalactic observables. We investigate how variations in AGN jet velocity, orientation, and delayed hydrodynamic coupling impact the thermodynamic state of gas surrounding galaxy clusters. We aim to identify observational signatures in the thermal Sunyaev-Zel'dovich (tSZ) effect and galaxy properties that can constrain these models. We employ zoom-in hydrodynamic simulations centered on three galaxy clusters from The Three Hundred, utilizing the SIMBA-C model and various feedback parameters. We use filament-finding algorithms and oriented stacking to probe the effect on large-scale structure and compare our results to observational data for brightest cluster galaxies from eRASS1, black hole-halo mass relations and baryonic mass fractions. Jet velocity is the dominant tested parameter in heating low-density environments at $z > 1$. At lower-$z$, higher velocity jets quench star formation, expel baryonic matter, and prevent black hole growth. While the tSZ signal within the central cluster and surrounding filaments is only affected by $\sim10\%$, the signal in under-dense regions outside filaments is enhanced by $\sim100\%$. In this case study, high velocity AGN jets provide the best match to galaxy properties from eRASS1 and other X-ray surveys. We find that hot gas in low-density regimes is a sensitive probe of AGN feedback. Future high-resolution tSZ surveys like the Simons Observatory and spectral-distortion experiments like FOSSIL have the potential to probe the thermal state of the gas outside clusters to distinguish between these feedback models.

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arXiv2026

A Consistent Comparison of Intracluster Light Assembly in Simulations I. Redshift Evolution and Progenitor Galaxies

The tidal stripping of satellite galaxies and the stellar detritus ejected during galaxy mergers builds up a diffuse stellar component in galaxy clusters known as the intracluster light (ICL). We investigate ICL assembly in cluster-mass haloes ($M_{178c}\sim10^{14}-10^{15}$ M$_\odot$) using four different hydrodynamical simulations (Horizon-AGN, TNG100, The Three Hundred Gizmo-Simba 7K, and Hydrangea) under a homogenized ICL identification framework. For our fiducial ICL definition we obtain broadly consistent $z\approx0$ ICL stellar mass fractions ($\sim0.1-0.2$) and, by tracking the progenitors of $z\approx0$ clusters back to $z\gtrsim2$, find no significant evolution in average ICL mass fractions. Alternative approaches for distinguishing the ICL from the central galaxy show the absolute ICL fraction to be highly sensitive to adopted definition, but we never find any significant inter-simulation discrepancies when implementing a consistent methodology to identify the ICL. Whether the average ICL mass fraction falls with increasing redshift or does not evolve is determined by the ICL definition adopted. By tracing $z\approx0$ ICL stars back to their progenitor galaxies, we find that lower-mass satellites typically make slightly larger ICL contributions relative to their mass in every considered simulation, but which galaxies make the dominant contribution to the ICL is primarily controlled by the infalling satellite mass function. Most ICL stars sourced from satellite galaxies are therefore expected to originate from galaxies with infall stellar masses above $\sim10^{10}$ M$_\odot$ and largely within $10^{10.5}-10^{11.5}$ M$_\odot$.

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arXiv2026

Anisotropy of Satellite Galaxies-I: Contrasting Correlations with Central Galaxy, Host Halo, and Large-Scale Filament Structures

Using the SIMBA, EAGLE, and IllustrisTNG-100 galaxy formation simulations, we examine the anisotropy of the satellite distribution and its dependencies on central galaxies, host halos, and cosmic filaments. We find that in all simulations the satellite anisotropy is robustly aligned with the halo/central galaxy major axis. This correlation is both redshift- and halo-mass-dependent and also extends to filamentary structures outside the halo to several virial radii. The alignment persists up to $z=1.5$ at high redshifts, and the mass dependence remains down to $M_\mathrm{200c} \approx 10^{11}M_{\odot}$. We identify a clear $3\sigma$ scale-dependent transition in the structural tracers of satellite anisotropy: satellite distributions correlate with central galaxy morphology at small scales ($<0.3R_{\rm 200c}$), are governed by host halo triaxiality at halo scales ($0.3$-$2R_{\rm 200c}$), and align with cosmic filaments beyond $2R_{\rm 200c}$. By tracing satellite trajectories in SIMBA, we uncover the kinematic origin of this transition, demonstrating that satellites prefer halo major-axis aligned regions because their trajectories intersect this axis far more frequently and stay in it for a longer time under the host's gravitational potential. This dynamical processing effectively erases primordial filament-related signals upon accretion ($<2R_{\rm 200c}$), explaining the shift in dominant structural tracers across scales.

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arXiv2026

The Three Hundred project: cosmic web identification from 2D gas and Compton-$y$ maps of galaxy clusters outskirts

Galaxy clusters are located at the nodes of the filamentary network known as the cosmic web. A more comprehensive understanding of galaxy clusters can be achieved by considering their environment, in particular, the filamentary structures to which they are connected. In this work, we aim to assess the reliability of the cosmic web reconstruction from mock observational data. In particular, we aim to quantify the effects of the 2D projection relative to the underlying 3D network and the impact of using the Sunyaev-Zel'dovich (SZ) effect as a tracer of the cosmic web. We reconstruct the filamentary networks in the outskirts of The Three Hundred simulated clusters with the filament finder DisPerSE. First, we extract the networks from the 2D gas distribution and evaluate their purity and completeness with respect to the 3D networks projected along the line of sight. We also compute the distances between the corresponding skeletons. Moreover, we identify filaments from simulated Compton-$y$ maps of the clusters at redshift $z=0$, and we compare them with the 2D gas network. The skeletons extracted from 2D maps provide good representations of the underlying 3D ones, both in terms of critical points and filaments. We find a median distance between the spines of the 2D and projected 3D networks of approximately $0.22 \, h^{-1}$ Mpc, although the connectivity derived from the 2D networks is slightly underestimated. We observe a good spatial agreement between the gas and SZ networks, with a median distance of $\approx 0.24 \, h^{-1}$ Mpc. Finally, we show that gas outside galaxy clusters is preferentially located in filamentary structures, which contribute $\sim 80\%$ of the integrated Compton-$Y$ parameter of clusters' outskirts.

astro-ph.CO↗

arXiv2026

A measurement of gas rotation in galaxy groups via the kinetic Sunyaev-Zeldovich effect

We utilise the kinetic Sunyaev-Zeldovich effect (kSZ) to measure the rotation of ionised gas within galaxy groups defined in the SDSS-DR7 galaxy sample, via their dipolar imprint on the cosmic microwave background (CMB). We estimate the direction of the projected angular momentum for each group by measuring the redshift dipole of satellite galaxies around their group centre. We find a clear redshift dipole in the stacked data for the SDSS groups. We then perform oriented stacking of the Planck CMB temperature map using the group centres and directions of angular momenta. We report a $2.3\sigma$ measurement of the coherent rotational kSZ effect (rkSZ) within the virial radii of SDSS groups with an average mass of $10^{14}h^{-1} \rm M_{\odot}$. We estimate the averaged rotational velocity of the sample to be $\sim 100-200 ~\rm km ~s^{-1}$, peaking at approximately half the virial radius. Our results are consistent within the errors with predictions based on the ELUCID constrained realisation simulation, with the predicted amplitude of the rkSZ signal being slightly lower near the centre. We also identify a systematic bias when estimating rotational velocities using the observed redshifts of galaxies, but find it to be subdominant for our analysis.

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arXiv2025

The Advanced X-ray Imaging Satellite (AXIS) Community Science Book

The AXIS Community Science Book represents the collective effort of 592 scientists worldwide to define the transformative science enabled by the Advanced X-ray Imaging Satellite (AXIS), a next-generation X-ray mission selected by NASA's Astrophysics Probe Program for Phase A study. AXIS will advance the legacy of high-angular-resolution X-ray astronomy with ~1.5'' imaging over a wide 24' field of view and an order of magnitude greater collecting area than Chandra in the 0.3-12 keV band. Combining sharp imaging, high throughput, and rapid response capabilities, AXIS will open new windows on virtually every aspect of modern astrophysics, exploring the birth and growth of supermassive black holes, the feedback processes that shape galaxies, the life cycles of stars and exoplanet environments, and the nature of compact stellar remnants, supernova remnants, and explosive transients. This book compiles 138 community-contributed science cases developed by five Science Working Groups focused on AGN and supermassive black holes, galaxy evolution and feedback, compact objects and supernova remnants, stellar physics and exoplanets, and time-domain and multi-messenger astrophysics. Together, these studies establish the scientific foundation for next-generation X-ray exploration in the 2030s and highlight strong synergies with facilities of the 2030s, such as JWST, Roman, Rubin/LSST, SKA, ALMA, ngVLA, and next-generation gravitational-wave and neutrino networks.

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arXiv2025

Deriving accurate galaxy cluster masses using X-ray thermodynamic profiles and graph neural networks

Precise determination of galaxy cluster masses is crucial for establishing reliable mass-observable scaling relations in cluster cosmology. We employ graph neural networks (GNNs) to estimate galaxy cluster masses from radially sampled profiles of the intra-cluster medium (ICM) inferred from X-ray observations. GNNs naturally handle inputs of variable length and resolution by representing each ICM profile as a graph, enabling accurate and flexible modeling across diverse observational conditions. We trained and tested GNN model using state-of-the-art hydrodynamical simulations of galaxy clusters from The Three Hundred Project. The mass estimates using our method exhibit no systematic bias compared to the true cluster masses in the simulations. Additionally, we achieve a scatter in recovered mass versus true mass of about 6%, which is a factor of six smaller than obtained from a standard hydrostatic equilibrium approach. Our algorithm is robust to both data quality and cluster morphology and it is capable of incorporating model uncertainties alongside observational uncertainties. Finally, we apply our technique to XMM-Newton observed galaxy cluster samples and compare the GNN derived mass estimates with those obtained with $Y_{\rm SZ}$-M$_{500}$ scaling relations. Our results provide strong evidence, at 5$\sigma$ level, for a mass-dependent bias in SZ derived masses, with higher mass clusters exhibiting a greater degree of deviation. Furthermore, we find the median bias to be $(1-b)=0.85_{-0.14}^{+0.34}$, albeit with significant dispersion due to its mass dependence. This work takes a significant step towards establishing unbiased observable mass scaling relations by integrating X-ray, SZ and optical datasets using deep learning techniques, thereby enhancing the role of galaxy clusters in precision cosmology.

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arXiv2025

The life and times of dark matter haloes: what will I be when I grow up?

Are the most massive objects in the Universe today the direct descendants of the most massive objects at higher redshift? We address this question by tracing the evolutionary histories of haloes in the MultiDark Planck2 simulation. By following the 100 most massive halos at $z = 0$ across cosmic time, we find that only 40\% of them were among the largest 100 halos at $z = 1$. This suggests that many of today's most massive clusters were not the most dominant structures at earlier times, while some of the most massive objects at high redshift do not remain in the top mass ranks at later epochs. The hierarchical nature of structure formation predicts that, on average, massive haloes grow over time, with their abundance in comoving space decreasing rapidly at higher redshifts. However, individual clusters exhibit diverse evolutionary paths: some undergo early rapid growth, while others experience steady accretion or significant merger-driven mass changes. A key assumption in self-similar models of cluster evolution is that the most massive objects maintain their rank in the mass hierarchy across cosmic time. In this work, we test this assumption by constructing a mass-complete sample of haloes within the $(1 h^{-1}{\rm Gpc})^3$ volume of MultiDark and analysing when clusters enter and exit a high-mass-selected sample. Our results demonstrate that cluster selections must be carefully constructed, as significant numbers of objects can enter and leave the sample over time. These findings have important implications for observational cluster selection and comparisons between simulations and surveys, especially at high redshift.

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arXiv2025

The Three Hundred Project: deducing the stellar splashback structure of galaxy clusters from their orbiting profiles

We examine the splashback structure of galaxy clusters using hydrodynamical simulations from the GIZMO run of The Three Hundred Project, focusing on the relationship between the stellar and dark matter components. We dynamically decompose clusters into orbiting and infalling material and fit their density profiles. We find that the truncation radius $r_{\mathrm{t}}$, associated with the splashback feature, coincides for stars and dark matter, but the stellar profile exhibits a systematically steeper decline. Both components follow a consistent $r_{\mathrm{t}}{-}\Gamma$ relation, where $\Gamma$ is the mass accretion rate, which suggests that stellar profiles can be used to infer recent cluster mass growth. We also find that the normalisation of the density profile of infalling material correlates with $\Gamma$, and that stellar and dark matter scale radii coincide when measured non-parametrically. By fitting stellar profiles in projection, we show that $r_{\mathrm{t}}$ can, in principle, be recovered observationally, with a typical scatter of $\sim 0.3\,R_{200\mathrm{m}}$. Our results demonstrate that the splashback feature in the stellar component provides a viable proxy for the cluster's physical boundary and recent growth by mass accretion, offering a complementary observable tracer to satellite galaxies and weak lensing.

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arXiv2025

Investigating the residuals in the $M_\bullet-M_*$ relation using the SIMBA cosmological simulation

We study the scaling relation between the black hole and stellar mass ($M_\bullet-M_*$), diagnosing the residual $\Delta \log(M_\bullet/M_\odot)$ ($\Delta$) in this relation to understand the coevolution of the galaxy and black hole (BH) in the cosmological hydrodynamic simulation SIMBA. We showed that SIMBA can reproduce the observed $M_\bullet-M_*$ relation well with little difference between central and satellite galaxies. By using the median value to determine the residuals, we found that the residual is correlated with galaxy cold gas content, star formation rate, colour and black hole accretion properties. Both torque and Bondi models implemented in SIMBA, contribute to this residual, with torque accretion playing a major role at high redshift and low-mass galaxies, while Bondi (also BH merge) takes over at low redshift and massive galaxies. By dividing the sample into two populations: $\Delta>0$ and $\Delta <0$, we compared their evolution paths following the main progenitors. With evolution tracking, we proposed a simple picture for the BH-galaxy coevolution: Early-formed galaxies seeded black holes earlier, with stellar mass increasing rapidly to quickly reach the point of triggering `jet mode' feedback. This process reduced the cold gas content and stopped the growth of $M_*$, effectively quenching galaxies. Meanwhile, during the initial phase of torque accretion growth, the BH mass is comparable between galaxies formed early and those formed later. However, those galaxies that formed earlier appear to attain a marginally greater BH mass when shifting to Bondi accretion, aligning with the galaxy transition time. As the early-formed galaxies reach this point earlier -- leaving a longer time for them to have Bondi accretion as well as merging, their residuals become positive, i.e., having more massive BHs at $z=0$ compared to these late-formed galaxies at the same $M_*$. This picture is further supported by the strong positive correlation between the residuals and the galaxy age, which we are proposing as a verification with observation data on this story suggested by SIMBA.

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arXiv2025

PyMGal: A Python Package for Generating Optical Mock Observations from Hydrodynamical Simulations

We introduce PyMGal, a Python package for generating optical mock observations of galaxies from hydrodynamical simulations. PyMGal reads the properties of stellar particles from these simulations and generates spectral energy distributions (SEDs) based on a variety of stellar population models that can be customised to fit the user's choice of applications. Given these SEDs, the program can calculate the brightness of particles in different output units for hundreds of unique filters. These quantities can then be projected to a 2D plane mimicking a telescope observation. The software is compatible with different snapshot formats and allows a flexible selection of models, filters, output units, axes of projection, angular resolutions, fields of view, and more. It also supports additional features including dust attenuation, particle smoothing, and the option to output spectral data cubes and maps of mass, age, and metallicity. These synthetic observations can be used to directly compare the simulated objects to reality in order to model galaxy evolution, study different theoretical models, and investigate different observational effects. This package allows the user to perform fast and consistent comparisons between simulation and observation, leading to a better and more precise understanding of what we see in our Universe.

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