Searcharxiv⌕ Search

arXiv subjects

Daisuke Nagai

Publications and source records attributed to Daisuke Nagai.

At least 55 records · Page 3Linked to original sources
arXiv2024

Zooming by in the CARPoolGP lane: new CAMELS-TNG simulations of zoomed-in massive halos

Galaxy formation models within cosmological hydrodynamical simulations contain numerous parameters with non-trivial influences over the resulting properties of simulated cosmic structures and galaxy populations. It is computationally challenging to sample these high dimensional parameter spaces with simulations, particularly for halos in the high-mass end of the mass function. In this work, we develop a novel sampling and reduced variance regression method, CARPoolGP, which leverages built-in correlations between samples in different locations of high dimensional parameter spaces to provide an efficient way to explore parameter space and generate low variance emulations of summary statistics. We use this method to extend the Cosmology and Astrophysics with MachinE Learning Simulations (CAMELS) to include a set of 768 zoom-in simulations of halos in the mass range of $10^{13} - 10^{14.5} M_\odot\,h^{-1}$ that span a 28-dimensional parameter space in the IllustrisTNG model. With these simulations and the CARPoolGP emulation method, we explore parameter trends in the Compton $Y-M$, black hole mass-halo mass, and metallicity-mass relations, as well as thermodynamic profiles and quenched fractions of satellite galaxies. We use these emulations to provide a physical picture of the complex interplay between supernova and active galactic nuclei feedback. We then use emulations of the $Y-M$ relation of massive halos to perform Fisher forecasts on astrophysical parameters for future Sunyaev-Zeldovich observations and find a significant improvement in forecasted constraints. We publicly release both the simulation suite and CARPoolGP software package.

astro-ph.GA↗
arXiv2024

Morphological Parameters and Associated Uncertainties for 8 Million Galaxies in the Hyper Suprime-Cam Wide Survey

We use the Galaxy Morphology Posterior Estimation Network (GaMPEN) to estimate morphological parameters and associated uncertainties for $\sim 8$ million galaxies in the Hyper Suprime-Cam (HSC) Wide survey with $z \leq 0.75$ and $m \leq 23$. GaMPEN is a machine learning framework that estimates Bayesian posteriors for a galaxy's bulge-to-total light ratio ($L_B/L_T$), effective radius ($R_e$), and flux ($F$). By first training on simulations of galaxies and then applying transfer learning using real data, we trained GaMPEN with $<1\%$ of our dataset. This two-step process will be critical for applying machine learning algorithms to future large imaging surveys, such as the Rubin-Legacy Survey of Space and Time (LSST), the Nancy Grace Roman Space Telescope (NGRST), and Euclid. By comparing our results to those obtained using light-profile fitting, we demonstrate that GaMPEN's predicted posterior distributions are well-calibrated ($\lesssim 5\%$ deviation) and accurate. This represents a significant improvement over light profile fitting algorithms which underestimate uncertainties by as much as $\sim60\%$. For an overlapping sub-sample, we also compare the derived morphological parameters with values in two external catalogs and find that the results agree within the limits of uncertainties predicted by GaMPEN. This step also permits us to define an empirical relationship between the Sérsic index and $L_B/L_T$ that can be used to convert between these two parameters. The catalog presented here represents a significant improvement in size ($\sim10 \times $), depth ($\sim4$ magnitudes), and uncertainty quantification over previous state-of-the-art bulge+disk decomposition catalogs. With this work, we also release GaMPEN's source code and trained models, which can be adapted to other datasets.

astro-ph.GA↗
arXiv2024

An Observationally Driven Multifield Approach for Probing the Circum-Galactic Medium with Convolutional Neural Networks

The circum-galactic medium (CGM) can feasibly be mapped by multiwavelength surveys covering broad swaths of the sky. With multiple large datasets becoming available in the near future, we develop a likelihood-free Deep Learning technique using convolutional neural networks (CNNs) to infer broad-scale physical properties of a galaxy's CGM and its halo mass for the first time. Using CAMELS (Cosmology and Astrophysics with MachinE Learning Simulations) data, including IllustrisTNG, SIMBA, and Astrid models, we train CNNs on Soft X-ray and 21-cm (HI) radio 2D maps to trace hot and cool gas, respectively, around galaxies, groups, and clusters. Our CNNs offer the unique ability to train and test on ''multifield'' datasets comprised of both HI and X-ray maps, providing complementary information about physical CGM properties and improved inferences. Applying eRASS:4 survey limits shows that X-ray is not powerful enough to infer individual halos with masses $\log(M_{\rm{halo}}/M_{\odot}) < 12.5$. The multifield improves the inference for all halo masses. Generally, the CNN trained and tested on Astrid (SIMBA) can most (least) accurately infer CGM properties. Cross-simulation analysis -- training on one galaxy formation model and testing on another -- highlights the challenges of developing CNNs trained on a single model to marginalize over astrophysical uncertainties and perform robust inferences on real data. The next crucial step in improving the resulting inferences on physical CGM properties hinges on our ability to interpret these deep-learning models.

astro-ph.GA↗
arXiv2023

The Structure and Dynamics of Massive High-$z$ Cosmic-Web Filaments: Three Radial Zones in Filament Cross-Sections

We analyse the internal structure and dynamics of cosmic-web filaments that connect massive high-$z$ haloes. Our analysis is based on a high-resolution AREPO cosmological simulation zooming-in on a volume encompassing three ${\rm Mpc}$-scale filaments feeding three massive haloes of $\sim 10^{12}\,\text{M}_\odot$ at $z \sim 4$, embedded in a large-scale sheet. Each filament is surrounded by a cylindrical accretion shock of radius $r_{\rm shock} \sim 50 \,{\rm kpc}$. The post-shock gas is in virial equilibrium with the potential well set by an isothermal dark-matter filament. The filament line-mass is $\sim 9\times 10^8\,\text{M}_\odot\,{\rm kpc}^{-1}$, the gas fraction within $r_{\rm shock}$ is the universal baryon fraction, and the virial temperature is $\sim 7\times 10^5 {\rm K}$. In the outer ''thermal'' (T) zone, $r \geq 0.65 \, r_{\rm shock}$, inward gravity and ram-pressure forces are over-balanced by outwards thermal pressure forces, decelerating the inflowing gas expanding the shock outward. In the intermediate ''vortex'' (V) zone, $0.25 \leq r/ r_{\rm shock} \leq 0.65$, the velocity field is dominated by a quadrupolar vortex structure due to offset inflow along the sheet through the post-shock gas. The outwards force is dominated by centrifugal forces associated with these vortices, with additional contributions from global rotation and thermal pressure. The shear and turbulent forces associated with the vortices act inward. The inner ''stream'' (S) zone, $r < 0.25 \, r_{\rm shock}$, is a dense isothermal core, $T\sim 3 \times 10^4 \, {\rm K}$ and $n_{\rm H}\sim 0.01 \,{\rm cm^{-3}}$, defining the cold streams that feed galaxies. The core is formed by an isobaric cooling flow and is associated with a decrease in outwards forces, though it exhibits both inflows and outflows. [abridged]

astro-ph.CO↗
arXiv2023

Formation of dense filaments induced by runaway supermassive black holes

A narrow linear object extending $\sim 60 \,{\rm kpc}$ from the centre of a galaxy at redshift $z \sim 1$ has recently been discovered and interpreted as shocked gas filament forming stars. The host galaxy presents an irregular morphology, implying recent merger events. Supposing that each of the progenitor galaxies has a central supermassive black hole (SMBH) and the SMBHs are accumulated at the centre of the merger remnant, a fraction of them can be ejected from the galaxy with a high velocity due to interactions between SMBHs. When such a runaway SMBH (RSMBH) passes through the circumgalactic medium (CGM), converging flows are induced along the RSMBH path, and star formation could eventually be ignited. We show that the CGM temperature prior to the RSMBH perturbation should be below the peak temperature in the cooling function to trigger filament formation. While the gas is temporarily heated due to compression, the cooling efficiency increases, and gas accumulation becomes allowed along the path. When the CGM density is sufficiently high, the gas can cool down and develop a dense filament by $z = 1$. The mass and velocity of the RSMBH determine the scale of filament formation. Hydrodynamical simulations validate the analytical expectations. Therefore, we conclude that the perturbation by RSMBHs is a viable channel to form the observed linear object. Using the analytic model validated by simulations, we show that the CGM around the linear object to be warm ($T < 2 \times 10^5 \, K$) and dense ($n > 2 \times 10^{-5} (T/2 \times 10^5 \, K)^{-1} \, {\rm cm^{-3}}$).

astro-ph.GA↗
arXiv2023

Mapping the Intracluster Medium in the Era of High-resolution X-ray Spectroscopy

High-resolution spectroscopy in soft X-rays will open a new window to map multiphase gas in galaxy clusters and probe physics of the intracluster medium (ICM), including chemical enrichment histories, circulation of matter and energy during large-scale structure evolution, stellar and black hole feedback, halo virialization, and gas mixing processes. An eV-level spectral resolution, large field-of-view, and effective area are essential to separate cluster emissions from the Galactic foreground and efficiently map the cluster outskirts. Several mission concepts that meet these criteria have been proposed recently, e.g., LEM, HUBS, and SuperDIOS. This theoretical study explores what information on ICM physics could be recovered with such missions and the associated challenges. We emphasize the need for a comprehensive comparison between simulations and observations to interpret the high-resolution spectroscopic observations correctly. Using Line Emission Mapper (LEM) characteristics as an example, we demonstrate that it enables the use of soft X-ray emission lines (e.g., O VII/VIII and Fe-L complex) from the cluster outskirts to measure the thermodynamic, chemical, and kinematic properties of the gas up to $r_{200}$ and beyond. By generating mock observations with full backgrounds, analysing their images/spectra with observational approaches, and comparing the recovered characteristics with true ones from simulations, we develop six key science drivers for future missions, including the exploration of multiphase gas in galaxy clusters (e.g., temperature fluctuations, phase-space distributions), metallicity, ICM gas bulk motions and turbulence power spectra, ICM-cosmic filament interactions, and advances for cluster cosmology.

astro-ph.HE↗
arXiv2023

A Differentiable Model of the Evolution of Dark Matter Halo Concentration

We introduce a new model of the evolution of the concentration of dark matter halos, c(t). For individual halos, our model approximates c(t) as a power law with a time-dependent index, such that at early times, concentration has a nearly constant value of c=3-4, and as cosmic time progresses, c(t) smoothly increases. Using large samples of halo merger trees taken from the Bolshoi-P and MDPL2 cosmological simulations, we demonstrate that our 3-parameter model can approximate the evolution of the concentration of individual halos with a typical accuracy of 0.1 dex for t>2 Gyr for all Bolshoi-P and MDPL2 halos of present-day mass greater than 10^11.5 Msun. We additionally present a new model of the evolution of the concentration of halo populations, which we show faithfully reproduces both average concentration growth, as well as the diversity of smooth trajectories of c(t), including capturing correlations with halo mass and halo assembly history. Our publicly available source code, Diffprof, can be used to generate Monte Carlo realizations of the concentration histories of cosmologically representative halo populations; Diffprof is differentiable due to its implementation in the JAX autodiff library, which facilitates the incorporation of our model into existing analytical halo model frameworks.

astro-ph.CO↗
arXiv2023

C2-GaMe: Classification of Cluster Galaxy Membership with Machine Learning

We present Classification of Cluster GAlaxy MEmbers (C$^2$-GaMe), a classification algorithm based on a suite of machine learning models that differentiates galaxies into orbiting, infalling, and background (interloper) populations, using phase space information as input. We train and test C$^2$-GaMe with the galaxies from UniverseMachine mock catalog based on Multi-Dark Planck 2 N-body simulations. We show that probabilistic classification is superior to deterministic classification in estimating the physical properties of clusters, including density profiles and velocity dispersion. We propose a set of estimators to get an unbiased estimation of cluster properties. We demonstrate that C$^2$-GaMe can recover the distribution of orbiting and infalling galaxies' position and velocity distribution with $<1\%$ statistical error when using probabilistic predictions in the presence of interlopers in the projected phase space. Additionally, we demonstrate the robustness of trained models by applying them to a different simulation. Finally, adding a specific star formation rate and the ratio of the galaxy's halo mass to the cluster's halo mass as additional features improves the classification performance. We discuss potential applications of this technique to enhance cluster cosmology and galaxy quenching.

astro-ph.CO↗
arXiv2023

Benchmarks and Explanations for Deep Learning Estimates of X-ray Galaxy Cluster Masses

We evaluate the effectiveness of deep learning (DL) models for reconstructing the masses of galaxy clusters using X-ray photometry data from next-generation surveys. We establish these constraints using a catalogue of realistic mock eROSITA X-ray observations which use hydrodynamical simulations to model realistic cluster morphology, background emission, telescope response, and AGN sources. Using bolometric X-ray photon maps as input, DL models achieve a predictive mass scatter of $σ_{\ln M_\mathrm{500c}} = 17.8\%$, a factor of two improvements on scalar observables such as richness $N_\mathrm{gal}$, 1D velocity dispersion $σ_\mathrm{v,1D}$, and photon count $N_\mathrm{phot}$ as well as a $32\%$ improvement upon idealised, volume-integrated measurements of the bolometric X-ray luminosity $L_X$. We then show that extending this model to handle multichannel X-ray photon maps, separated in low, medium, and high energy bands, further reduces the mass scatter to $16.2\%$. We also tested a multimodal DL model incorporating both dynamical and X-ray cluster probes and achieved marginal gains at a mass scatter of $15.9\%$. Finally, we conduct a quantitative interpretability study of our DL models and find that they greatly down-weight the importance of pixels in the centres of clusters and at the location of AGN sources, validating previous claims of DL modelling improvements and suggesting practical and theoretical benefits for using DL in X-ray mass inference.

astro-ph.CO↗
arXiv2023

Cosmological baryon spread and impact on matter clustering in CAMELS

We quantify the cosmological spread of baryons relative to their initial neighboring dark matter distribution using thousands of state-of-the-art simulations from the Cosmology and Astrophysics with MachinE Learning Simulations (CAMELS) project. We show that dark matter particles spread relative to their initial neighboring distribution owing to chaotic gravitational dynamics on spatial scales comparable to their host dark matter halo. In contrast, gas in hydrodynamic simulations spreads much further from the initial neighboring dark matter owing to feedback from supernovae (SNe) and Active Galactic Nuclei (AGN). We show that large-scale baryon spread is very sensitive to model implementation details, with the fiducial \textsc{SIMBA} model spreading $\sim$40\% of baryons $>$1\,Mpc away compared to $\sim$10\% for the IllustrisTNG and \textsc{ASTRID} models. Increasing the efficiency of AGN-driven outflows greatly increases baryon spread while increasing the strength of SNe-driven winds can decrease spreading due to non-linear coupling of stellar and AGN feedback. We compare total matter power spectra between hydrodynamic and paired $N$-body simulations and demonstrate that the baryonic spread metric broadly captures the global impact of feedback on matter clustering over variations of cosmological and astrophysical parameters, initial conditions, and galaxy formation models. Using symbolic regression, we find a function that reproduces the suppression of power by feedback as a function of wave number ($k$) and baryonic spread up to $k \sim 10\,h$\,Mpc$^{-1}$ while highlighting the challenge of developing models robust to variations in galaxy formation physics implementation.

astro-ph.GA↗
arXiv2023

Circumgalactic Medium on the Largest Scales: Detecting X-ray Absorption Lines with Large-Area Microcalorimeters

The circumgalactic medium (CGM) plays a crucial role in galaxy evolution as it fuels star formation, retains metals ejected from the galaxies, and hosts gas flows in and out of galaxies. For Milky Way-type and more massive galaxies, the bulk of the CGM is in hot phases best accessible at X-ray wavelengths. However, our understanding of the CGM remains largely unconstrained due to its tenuous nature. A promising way to probe the CGM is via X-ray absorption studies. Traditional absorption studies utilize bright background quasars, but this method probes the CGM in a pencil beam, and, due to the rarity of bright quasars, the galaxy population available for study is limited. Large-area, high spectral resolution X-ray microcalorimeters offer a new approach to exploring the CGM in emission and absorption. Here, we demonstrate that the cumulative X-ray emission from cosmic X-ray background sources can probe the CGM in absorption. We construct column density maps of major X-ray ions from the Magneticum simulation and build realistic mock images of nine galaxies to explore the detectability of X-ray absorption lines arising from the large-scale CGM. We conclude that the OVII absorption line is detectable around individual massive galaxies at the $3σ-6σ$ confidence level. For Milky Way-type galaxies, the OVII and OVIII absorption lines are detectable at the $\sim\,6σ$ and $\sim\,3σ$ levels even beyond the virial radius when co-adding data from multiple galaxies. This approach complements emission studies, does not require additional exposures, and will allow probing of the baryon budget and the CGM at the largest scales.

astro-ph.GA↗
arXiv2023

The SZ flux-mass ($Y$-$M$) relation at low halo masses: improvements with symbolic regression and strong constraints on baryonic feedback

Feedback from active galactic nuclei (AGN) and supernovae can affect measurements of integrated SZ flux of halos ($Y_\mathrm{SZ}$) from CMB surveys, and cause its relation with the halo mass ($Y_\mathrm{SZ}-M$) to deviate from the self-similar power-law prediction of the virial theorem. We perform a comprehensive study of such deviations using CAMELS, a suite of hydrodynamic simulations with extensive variations in feedback prescriptions. We use a combination of two machine learning tools (random forest and symbolic regression) to search for analogues of the $Y-M$ relation which are more robust to feedback processes for low masses ($M\lesssim 10^{14}\, h^{-1} \, M_\odot$); we find that simply replacing $Y\rightarrow Y(1+M_*/M_\mathrm{gas})$ in the relation makes it remarkably self-similar. This could serve as a robust multiwavelength mass proxy for low-mass clusters and galaxy groups. Our methodology can also be generally useful to improve the domain of validity of other astrophysical scaling relations. We also forecast that measurements of the $Y-M$ relation could provide percent-level constraints on certain combinations of feedback parameters and/or rule out a major part of the parameter space of supernova and AGN feedback models used in current state-of-the-art hydrodynamic simulations. Our results can be useful for using upcoming SZ surveys (e.g., SO, CMB-S4) and galaxy surveys (e.g., DESI and Rubin) to constrain the nature of baryonic feedback. Finally, we find that the an alternative relation, $Y-M_*$, provides complementary information on feedback than $Y-M$

astro-ph.CO↗
arXiv2023

The Evolving Effect Of Cosmic Web Environment On Galaxy Quenching

We investigate how cosmic web structures affect galaxy quenching in the IllustrisTNG (TNG100) cosmological simulations by reconstructing the cosmic web within each snapshot using the DisPerSE framework. We measure the comoving distance from each galaxy with stellar mass $\log(M_{\ast}/\mathrm{M}_{\odot}) \geq 8$ to the nearest node ($d_{\mathrm{node}}$) and the nearest filament spine ($d_{\mathrm{fil}}$) to study the dependence of both median specific star formation rate ( ) and median gas fraction (<$f_{\mathrm{gas}}$>) on these distances. We find that the of galaxies is only dependent on cosmic web environment at $z<2$, with the dependence increasing with time. At $z\leq0.5$, $8 \leq \log(M_{\ast}/\mathrm{M}_{\odot}) < 9$ galaxies are quenched at $d_{\mathrm{node}}\lesssim1$~Mpc, and have significantly-suppressed star formation at $d_{\mathrm{fil}}\lesssim1$~Mpc, trends driven mostly by satellite galaxies. At $z\leq1$, in contrast to the monotonic drop in of $\log(M_{\ast}/\mathrm{M}_{\odot}) <10$ galaxies with decreasing $d_{\mathrm{node}}$ and $d_{\mathrm{fil}}$, $\log(M_{\ast}/\mathrm{M}_{\odot}) \geq 10$ galaxies - both centrals and satellites - experience an upturn in at $d_{\mathrm{node}}\lesssim0.2$~Mpc. Much of this cosmic web dependence of star formation activity can be explained by an evolution in $ $. Our results suggest that in the past $\sim$10 Gyr, low-mass satellites are quenched by rapid gas stripping in dense environments near nodes and gradual gas starvation in intermediate-density environments near filaments, while at earlier times cosmic web structures efficiently channeled cold gas into most galaxies. State-of-the-art ongoing spectroscopic surveys such as SDSS and DESI, as well as those planned with the Subaru Prime Focus Spectrograph, JWST and Roman, are required to test our predictions against observations.

astro-ph.GA↗
arXiv2023

Line Emission Mapper (LEM): Probing the physics of cosmic ecosystems

The Line Emission Mapper (LEM) is an X-ray Probe for the 2030s that will answer the outstanding questions of the Universe's structure formation. It will also provide transformative new observing capabilities for every area of astrophysics, and to heliophysics and planetary physics as well. LEM's main goal is a comprehensive look at the physics of galaxy formation, including stellar and black-hole feedback and flows of baryonic matter into and out of galaxies. These processes are best studied in X-rays, and emission-line mapping is the pressing need in this area. LEM will use a large microcalorimeter array/IFU, covering a 30x30' field with 10" angular resolution, to map the soft X-ray line emission from objects that constitute galactic ecosystems. These include supernova remnants, star-forming regions, superbubbles, galactic outflows (such as the Fermi/eROSITA bubbles in the Milky Way and their analogs in other galaxies), the Circumgalactic Medium in the Milky Way and other galaxies, and the Intergalactic Medium at the outskirts and beyond the confines of galaxies and clusters. LEM's 1-2 eV spectral resolution in the 0.2-2 keV band will make it possible to disentangle the faintest emission lines in those objects from the bright Milky Way foreground, providing groundbreaking measurements of the physics of these plasmas, from temperatures, densities, chemical composition to gas dynamics. While LEM's main focus is on galaxy formation, it will provide transformative capability for all classes of astrophysical objects, from the Earth's magnetosphere, planets and comets to the interstellar medium and X-ray binaries in nearby galaxies, AGN, and cooling gas in galaxy clusters. In addition to pointed observations, LEM will perform a shallow all-sky survey that will dramatically expand the discovery space.

astro-ph.IM↗
arXiv2023

A candidate runaway supermassive black hole identified by shocks and star formation in its wake

The interaction of a runaway supermassive black hole (SMBH) with the circumgalactic medium (CGM) can lead to the formation of a wake of shocked gas and young stars behind it. Here we report the serendipitous discovery of an extremely narrow linear feature in HST/ACS images that may be an example of such a wake. The feature extends 62 kpc from the nucleus of a compact star-forming galaxy at z=0.964. Keck LRIS spectra show that the [OIII]/H$β$ ratio varies from ~1 to ~10 along the feature, indicating a mixture of star formation and fast shocks. The feature terminates in a bright [OIII] knot with a luminosity of 1.9x10$^{41}$ ergs/s. The stellar continuum colors vary along the feature, and are well-fit by a simple model that has a monotonically increasing age with distance from the tip. The line ratios, colors, and the overall morphology are consistent with an ejected SMBH moving through the CGM at high speed while triggering star formation. The best-fit time since ejection is ~39 Myr and the implied velocity is v~1600 km/s. The feature is not perfectly straight in the HST images, and we show that the amplitude of the observed spatial variations is consistent with the runaway SMBH interpretation. Opposite the primary wake is a fainter and shorter feature, marginally detected in [OIII] and the rest-frame far-ultraviolet. This feature may be shocked gas behind a binary SMBH that was ejected at the same time as the SMBH that produced the primary wake.

astro-ph.GA↗
arXiv2023

Accurate Model of the Projected Velocity Distribution of Galaxies in Dark Matter Halos

We present a percent-level accurate model of the line-of-sight velocity distribution of galaxies around dark matter halos as a function of projected radius and halo mass. The model is developed and tested using synthetic galaxy catalogs generated with the UniverseMachine run on the Multi-Dark Planck 2 N-body simulations. The model decomposes the galaxies around a cluster into three kinematically distinct classes: orbiting, infalling, and interloping galaxies. We demonstrate that: 1) we can statistically distinguish between these three types of galaxies using only projected line-of-sight velocity information; 2) the halo edge radius inferred from the line-of-sight velocity dispersion is an excellent proxy for the three-dimensional halo edge radius; 3) we can accurately recover the full velocity dispersion profile for each of the three populations of galaxies. Importantly, the velocity dispersion profiles of the orbiting and infalling galaxies contain five independent parameters -- three distinct radial scales and two velocity dispersion amplitudes -- each of which is correlated with mass. Thus, the velocity dispersion profile of galaxy clusters has inherent redundancies that allow us to perform nontrivial systematics check from a single data set. We discuss several potential applications of our new model for detecting the edge radius and constraining cosmology and astrophysics using upcoming spectroscopic surveys.

astro-ph.CO↗
arXiv2023

Weak-lensing mass bias in merging galaxy clusters

Although weak lensing (WL) is a powerful method to estimate a galaxy cluster mass without any dynamical assumptions, a model bias can arise when the cluster density profile departs from the assumed model profile. In a merging system, the bias is expected to become most severe because the constituent halos undergo significant structural changes. In this study, we investigate WL mass bias in binary cluster mergers using a suite of idealized hydrodynamical simulations. Realistic WL shear catalogs are generated by matching the source galaxy properties, such as intrinsic shape dispersion, measurement noise, source densities, etc., to those from Subaru and {\it Hubble Space Telescope} observations. We find that, with the typical mass-concentration ($M$-$c$) relation and the Navarro-Frenk-White (NFW) profile, the halo mass bias depends on the time since the first pericenter passage and increases with the mass of the companion cluster. The time evolution of the mass bias is similar to that of the concentration, indicating that, to first order, the mass bias is modulated by the concentration change. For a collision between two $\sim10^{15}~M_{\odot}$ clusters, the maximum bias amounts to $\sim60\%$. This suggests that previous WL studies may have significantly overestimated the mass of the clusters in some of the most massive mergers. Finally, we apply our results to three merger cases: Abell 2034, MACS J1752.0+4440, and ZwCl 1856.8+6616, and report their mass biases at the observed epoch, as well as their pre-merger masses, utilizing their merger shock locations as tracers of the merger phases.

astro-ph.CO↗
arXiv2023

X-ray Absorption Lines in the Warm-Hot Intergalactic Medium: Probing Chandra observations with the CAMEL simulations

Known as the "Missing Baryon Problem", about one-third of baryons in the local universe remain unaccounted for. The missing baryons are thought to reside in the warm-hot intergalactic medium (WHIM) of the cosmic web filaments, which are challenging to detect. Recent Chandra X-ray observations used a novel stacking analysis and detected an OVII absorption line toward the sightline of a luminous quasar, hinting that the missing baryons may reside in the WHIM. To explore how the properties of the OVII absorption line depend on feedback physics, we compare the observational results with predictions obtained from the Cosmology and Astrophysics with MachinE Learning (CAMEL) Simulation suite. CAMELS consists of cosmological simulations with state-of-the-art supernova (SN) and active galactic nuclei (AGN) feedback models from the IllustrisTNG and SIMBA simulations, with varying strengths. We find that the simulated OVII column densities are higher in the outskirts of galaxies than in the large-scale WHIM, but they are consistently lower than those obtained in the Chandra observations, for all feedback runs. We establish that the OVII distribution is primarily sensitive to changes in the SN feedback prescription, whereas changes in the AGN feedback prescription have minimal impact. We also find significant differences in the OVII column densities between the IllustrisTNG and SIMBA runs. We conclude that the tension between the observed and simulated OVII column densities cannot be explained by the wide range of feedback models implemented in CAMELS.

astro-ph.CO↗