Mock Images Research Articles

Signatures of Massive Black Hole Merger Host Galaxies from Cosmological Simulations. I. Unique Galaxy Morphologies in Imaging

Low-frequency gravitational-wave experiments such as the Laser Interferometer Space Antenna and pulsar timing arrays are expected to detect individual massive black hole (MBH) binaries and mergers. However, secure methods of identifying the exact host galaxy of each MBH merger among the large number of galaxies in the gravitational-wave localization region are currently lacking. We investigate the distinct morphological signatures of MBH merger host galaxies, using the Romulus25 cosmological simulation. We produce mock telescope images of 201 simulated galaxies in Romulus25 hosting recent MBH mergers through stellar population synthesis and dust radiative transfer. Based on comparisons to mass- and redshift-matched control samples, we show that combining multiple morphological statistics via a linear discriminant analysis enables identification of the host galaxies of MBH mergers, with accuracies that increase with chirp mass and mass ratio. For mergers with high chirp masses (≳108.2 M ⊙) and high mass ratios (≳0.5), the accuracy of this approach reaches ≳80%, and does not decline for at least ∼1 Gyr after numerical merger. We argue that these trends arise because the most distinctive morphological characteristics of MBH merger and binary host galaxies are prominent classical bulges, rather than relatively short-lived morphological disturbances from their preceding galaxy mergers. Since these bulges are formed though major mergers of massive galaxies, they lead to (and become permanent signposts for) MBH binaries and mergers that have high chirp masses and mass ratios. Our results suggest that galaxy morphology can aid in identifying the host galaxies of future MBH binaries and mergers.

A machine learning method to infer clusters of galaxies mass radial profiles from mock Sunyaev-Zel’dovich maps with The Three Hundred clusters

Our study introduces a new machine learning algorithm for estimating 3D cumulative radial profiles of total and gas mass in galaxy clusters from thermal Sunyaev-Zel’dovich (SZ) effect maps. We generate mock images from 2522 simulated clusters, employing an autoencoder and random forest in our approach. Notably, our model makes no prior assumptions about hydrostatic equilibrium. Our results indicate that the model successfully reconstructs unbiased total and gas mass profiles, with a scatter of approximately 10%. We analyse clusters in various dynamical states and mass ranges, finding that our method’s accuracy and precision are consistent. We verify the capabilities of our model by comparing it with the hydrostatic equilibrium technique, showing that it accurately recovers total mass profiles without any bias.

Euclidpreparation

Forthcoming imaging surveys will increase the number of known galaxy-scale strong lenses by several orders of magnitude. For this to happen, images of billions of galaxies will have to be inspected to identify potential candidates. In this context, deep-learning techniques are particularly suitable for finding patterns in large data sets, and convolutional neural networks (CNNs) in particular can efficiently process large volumes of images. We assess and compare the performance of three network architectures in the classification of strong-lensing systems on the basis of their morphological characteristics. In particular, we implemented a classical CNN architecture, an inception network, and a residual network. We trained and tested our networks on different subsamples of a data set of 40 000 mock images whose characteristics were similar to those expected in the wide survey planned with the ESA missionEuclid, gradually including larger fractions of faint lenses. We also evaluated the importance of adding information about the color difference between the lens and source galaxies by repeating the same training on single- and multiband images. Our models find samples of clear lenses with ≳90% precision and completeness. Nevertheless, when lenses with fainter arcs are included in the training set, the performance of the three models deteriorates with accuracy values of ~0.87 to ~0.75, depending on the model. Specifically, the classical CNN and the inception network perform similarly in most of our tests, while the residual network generally produces worse results. Our analysis focuses on the application of CNNs to high-resolution space-like images, such as those that theEuclidtelescope will deliver. Moreover, we investigated the optimal training strategy for this specific survey to fully exploit the scientific potential of the upcoming observations. We suggest that training the networks separately on lenses with different morphology might be needed to identify the faint arcs. We also tested the relevance of the color information for the detection of these systems, and we find that it does not yield a significant improvement. The accuracy ranges from ~0.89 to ~0.78 for the different models. The reason might be that the resolution of theEuclidtelescope in the infrared bands is lower than that of the images in the visual band.

Preparing for low surface brightness science with the Vera C. Rubin Observatory: a comparison of observable and simulated intracluster light fractions

ABSTRACT Intracluster light (ICL) provides an important record of the interactions galaxy clusters have undergone. However, we are limited in our understanding by our measurement methods. To address this, we measure the fraction of cluster light that is held in the Brightest Cluster Galaxy and ICL (BCG+ICL fraction) and the ICL alone (ICL fraction) using observational methods (surface brightness threshold-SB, non-parametric measure-NP, composite models-CM, and multi-galaxy fitting-MGF) and new approaches under development (wavelet decomposition-WD) applied to mock images of 61 galaxy clusters (14 <log10M200c/M⊙ < 14.5) from four cosmological hydrodynamical simulations. We compare the BCG+ICL and ICL fractions from observational measures with those using simulated measures (aperture and kinematic separations). The ICL fractions measured by kinematic separation are significantly larger than observed fractions. We find the measurements are related and provide equations to estimate kinematic ICL fractions from observed fractions. The different observational techniques give consistent BCG+ICL and ICL fractions but are biased to underestimating the BCG+ICL and ICL fractions when compared with aperture simulation measures. Comparing the different methods and algorithms, we find that the MGF algorithm is most consistent with the simulations, and CM and SB methods show the smallest projection effects for the BCG+ICL and ICL fractions, respectively. The Ahad (CM), MGF, and WD algorithms are best set up to process larger samples; however, the WD algorithm in its current form is susceptible to projection effects. We recommend that new algorithms using these methods are explored to analyse the massive samples that Rubin Observatory’s Legacy Survey of Space and Time will provide.

Mock Observations: Formation and Evolution of Diffuse Light in Galaxy Groups and Clusters in the IllustrisTNG Simulations

In this paper, by analyzing mock images from the IllustrisTNG100-1 simulation, we examine the properties of diffuse light and compare them to those of central and satellite galaxies. Our findings suggest that the majority of the diffuse light originates from satellites. This claim is supported by the similarity between the age and metallicity distributions of the diffuse light and those of the satellites. Notably, the color distribution of the diffuse light gradually evolves to resemble that of the centrals at lower redshifts, suggesting a coevolution or passive process. The radial profiles of the diffuse light reveal distinct trends, with the inner regions displaying a relatively flat distribution and the outer regions showing a descending pattern. This finding suggests that the formation of the diffuse light is influenced by both major mergers and stellar tidal stripping. Moreover, strong correlations are found between the stellar mass of the diffuse light and the overall stellar mass of the satellites, as well as between the stellar mass of the diffuse light and the number of satellites within groups or clusters. These relationships can be described by power-law and logarithmic functions. Overall, the diffuse light components predominantly originate from satellites with intermediate ages and metallicities. These satellites typically fall within the stellar mass range and the color range −1 < [g − r]0.1 < 0. As the redshift decreases, the growth of the diffuse light is primarily influenced by the redder satellites, while the most massive and reddest satellites have minimal roles in its growth.

A Feminist Approach to the Reconstruction of Fidelity Paradigm - A Case Study of Jane Eyre

From a feminist perspective and using feminist translation theory as its theoretical framework, this article, subverts the traditional notion of fidelity in translation through Sherry Simons feminist translation theory. It employs strategies of supplementation and hijacking to conduct a comparative study of male and female translations of Charlotte Brontes Jane Eyre. This research demonstrates differences in translation strategies and ideological perspectives between male and female translators, indicating that female translators, when using the supplementation strategy, pay more attention to shaping female characters and qualities. They also incorporate their own understanding and sympathy for female characters into the translation process to highlight the translators subjective position. However, male translators may deliberately or inadvertently stigmatize, belittle, or mock female images in their translations. Therefore, female translators employ the hijacking strategy to intervene in the text with feminism and embed female thinking. The goal is to eliminate discrimination against women and strive for gender equality. And it highlights the identity and subjectivity of female translators and advocating for gender equality. At the same time, the strategies and significance of feminist translation theory provide rich intellectual resources for the criticism and development of translation theory.

Study on knowledge of front-of-pack labeling and food group-based dietary intake among chronic gastritis patients.

Chronic gastritis is one of the most prevalent disorders affecting individuals, which affects hundreds of millions of people in different ways around the world. The significant incidence of poor dietary quality and diet-related illnesses may be addressed by orienting customers toward healthier food options. The objective of the study was to estimate the knowledge of front-of-package labels (FoPLs) and food group-based dietary intake of nutrients among patients with chronic gastritis. The study design was a hospital-based cross-sectional study that was done in Guntur district of Andhra Pradesh. The study population included 208 chronic gastritis patients between 20 to 60 years of age selected by systematic sampling. Detailed information on sociodemographic and lifestyle factors was collected using a questionnaire and 24-h dietary recall was done. The objective assessment of Knowledge of FoPLs was assessed mock package images representing a fictional brand to prevent other factors from interfering with product evaluation. A total of 208 patients were studied with a near-equal proportion of males and females. Among participants, more than half (57.2%) can interpret FoPL, more than three-fourths (77.4%) have a belief that they eat a healthy diet mostly and only half (52.4%) of participants are somewhat knowledgeable about nutrition, and finally almost half (46.6%) of participants are not seeing the FoP label during food purchase. The mean score of knowledge of FoP labeling was 0.92 ± 1.135. Knowledge of FOPL was positively associated with the age of study participants OR 0.178 (95% CI: 0.178 to 0.856) with P value = 0.02. Grains have the maximum intake among all the food groups with a mean intake of 123.21 g/day. The majority of participants do not know the food labeling, thus methods of education that focus on dietary interventions are urgently needed to raise awareness among the people.

Mass Reconstruction of Galaxy-scale Strong Gravitational Lenses Using a Broken Power-law Model

With mock strong gravitational lensing images, we investigate the performance of the broken power-law (BPL) model proposed by Du et al. () on the mass reconstruction of galaxy-scale lenses. An end-to-end test is carried out, including the creation of mock strong lensing images, the subtraction of lens light, and the reconstruction of lensed images, where the lenses are selected from the galaxies in the Illustris-1 simulation. We notice that, regardless of the adopted mass models (the BPL model or its special cases), the Einstein radius can be robustly determined from imaging data alone, and the median bias is typically less than 1%. Away from the Einstein radius, the lens mass distribution tends to be harder to measure, especially at radii where there are no lensed images detected. We find that, with rigid priors, the BPL model can clearly outperform the single power-law models by achieving <5% median bias on the radial convergence profile within the Einstein radius. As for the source light reconstructions, they are found to be sensitive to both lens light contamination and lens mass models, where the BPL model with rigid priors still performs best when there is no lens light contamination. We show that, by correcting for the projection effect, the BPL model can estimate the aperture and luminosity weighted line-of-sight velocity dispersions to an accuracy of ∼6% scatter. These results highlight the great potential of the BPL model in strong lensing related studies.

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 O VII absorption line is detectable around individual massive galaxies at the 3σ–6σ confidence level. For Milky Way–type galaxies, the O VII and O VIII absorption lines are detectable at the ∼ 6σ and ∼ 3σ levels even beyond the virial radius when coadding data from multiple galaxies. This approach complements emission studies, does not require additional exposures, and will allow for probing the baryon budget and the CGM at the largest scales.

TDCOSMO

Time-delay distance measurements of strongly lensed quasars have provided a powerful and independent probe of the current expansion rate of the Universe (H0). However, in light of the discrepancies between early- and late-time cosmological studies, current efforts revolve around the characterisation of systematic uncertainties in the methods. In this work we focus on the mass-sheet degeneracy (MSD), which is commonly considered a significant source of systematics in time-delay strong lensing studies, and aim to assess the constraining power provided by integral field unit (IFU) stellar kinematics. To this end, we approximated the MSD with a cored, two-parameter extension to the adopted lensing mass profiles (with core radius rc and mass-sheet parameter λint), which introduces a full degeneracy between λint and H0 from lensing data alone. In addition, we utilised spatially resolved mock IFU stellar kinematics of time-delay strong lenses, given the prospects of obtaining such high-quality data with the James Webb Space Telescope (JWST) in the near future. We constructed joint strong lensing and generalised two-integral axisymmetric Jeans models, where the time delays, mock imaging, and IFU observations are used as input to constrain the mass profile of lens galaxies at the individual galaxy level and consequently yield joint constraints on the time-delay distance (DΔt) and the angular diameter distance (Dd) to the lens. We find that mock JWST-like stellar kinematics constrain the amount of internal mass sheet that is physically associated with the lens galaxy and limit its contribution to the uncertainties of DΔt and Dd, each at the ≤4% level, without assumptions on the background cosmological model. Incorporating additional uncertainties due to external mass sheets associated with mass structures along the lens line of sight, these distance constraints would translate to a ≲4% precision measurement on H0 in flat Λ cold dark matter cosmology for a single lens. Our study shows that future IFU stellar kinematics of time-delay lenses will be key in lifting the MSD on a per lens basis, assuming reasonable and physically motivated core sizes. However, even in the limit of infinite rc, where DΔt is fully degenerate with λint and is thus not constrained, stellar kinematics of the deflector, time delays, and imaging data will provide powerful constraints on Dd, which becomes the dominant source of information in the cosmological inference.

Mock X-Ray Observations of Hot Gas with L-Galaxies Semi-analytic Models of Galaxy Formation

We create mock X-ray observations of hot gas in galaxy clusters with a new extension of the L-Galaxies semi-analytic model of galaxy formation, which includes the radial distribution of hot gas in each halo. Based on the model outputs, we first build some mock light cones, then generate mock spectra with the SOXS package and derive the mock images in the light cones. Using the mock data, we simulate mock X-ray spectra for the ROSAT all-sky survey, and compare the mock spectra with the observational results. Then, we consider the design parameters of the HUBS mission and simulate the observation of the halo hot gas for HUBS as an important application of our mock work. We find: (1) our mock data match the observations by current X-ray telescopes. (2) The survey of hot baryons in resolved clusters by HUBS is effective below redshift 0.5, and the observations of the emission lines in point-like sources at z > 0.5 by HUBS help us understand the hot baryons in the early universe. (3) By taking advantage of the large simulation box and flexibility in semi-analytic models, our mock X-ray observations provide the opportunity to select targets and observation strategies for forthcoming X-ray facilities.

Translators of Galaxy Morphology Indicators between Observation and Simulation

Based on the recent advancements in numerical simulations of galaxy formation, we anticipate the achievement of realistic models of galaxies in the near future. Morphology is the most basic and fundamental property of galaxies, yet observations and simulations still use different methods to determine galaxy morphology, making it difficult to compare them. We hereby perform a test on the recent NewHorizon simulation, which has spatial and mass resolutions that are remarkably high for a large-volume simulation, to resolve the situation. We generate mock images for the simulated galaxies using SKIRT, which calculates complex radiative transfer processes in each galaxy. We measure morphological and kinematic indicators using photometric and spectroscopic methods following observers’ techniques. We also measure the kinematic disk-to-total ratios using the Gaussian mixture model and assume that they represent the true structural composition of galaxies. We found that spectroscopic indicators such as V/σ and λ R closely trace the kinematic disk-to-total ratios. In contrast, photometric disk-to-total ratios based on the radial profile fitting method often fail to recover the true kinematic structure of galaxies, especially small ones. We provide translating equations between various morphological indicators.

Distinguishing magnetized disc winds from turbulent viscosity through substructure morphology in planet-forming discs

ABSTRACT The traditional paradigm of viscosity-dominated evolution of protoplanetary discs has been recently challenged by existence of magnetized disc winds. However, distinguishing wind-driven and turbulence-driven accretion through observations has been difficult. In this study, we present a novel approach to identifying their separate contribution to angular momentum transport by studying the gap and ring morphology of planet-forming discs in the ALMA continuum. We model the gap-opening process of planets in discs with both viscous evolution and wind-driven accretion by 2D multifluid hydrodynamical simulations. Our results show that gap-opening planets in wind-driven accreting discs generate characteristic dust substructures that differ from those in purely viscous discs. Specifically, we demonstrate that discs where wind-driven accretion dominates the production of substructures exhibit significant asymmetries. Based on the diverse outputs of mock images in the ALMA continuum, we roughly divide the planet-induced features into four regimes (moderate-viscosity dominated, moderate-wind dominated, strong-wind dominated, and inviscid). The classification of these regimes sets up a potential method to constrain the strength of magnetized disc wind and viscosity based on the observed gap and ring morphology. We discuss the asymmetry feature in our mock images and its potential manifestation in ALMA observations.

Prospects for Ray-tracing Light Intensity and Polarization in Models of Accreting Compact Objects Using a GPU

The Event Horizon Telescope (EHT) has recently released high-resolution images of accretion flows onto two supermassive black holes. Our physical understanding of these images depends on the accuracy and precision of numerical models of plasma and radiation around compact objects. The goal of this work is to speed up radiative-transfer simulations used to create mock images of black holes for comparison with the EHT observations. A ray-tracing code for general relativistic and fully polarized radiative transfer through plasma in strong gravity is ported onto a graphics processing unit (GPU). We describe our GPU implementation and carry out speedup tests using models of optically thin advection-dominated accretion flow onto a black hole realized semianalytically and in 3D general relativistic magnetohydrodynamic simulations, low and very high image pixel resolutions, and two different sets of CPU+GPUs. We show that a GPU with high double precision computing capability can significantly reduce the image production computational time, with a speedup factor of up to approximately 1200. The significant speedup facilitates, e.g., dynamic model fitting to the EHT data, including polarimetric data. The method extension may enable studies of emission from plasma with nonthermal particle distribution functions for which accurate approximate synchrotron emissivities are not available. The significant speedup reduces the carbon footprint of the generation of the EHT image libraries by at least an order of magnitude.

The three hundredproject: a machine learning method to infer clusters of galaxy mass radial profiles from mock Sunyaev–Zel’dovich maps

ABSTRACTWe develop a machine learning algorithm to infer the three-dimensional cumulative radial profiles of total and gas masses in galaxy clusters from thermal Sunyaev–Zel’dovich effect maps. We generate around 73 000 mock images along various lines of sight using 2522 simulated clusters from the three hundred project at redshift z &amp;lt; 0.12 and train a model that combines an auto-encoder and a random forest. Without making any prior assumptions about the hydrostatic equilibrium of the clusters, the model is capable of reconstructing the total mass profile as well as the gas mass profile, which is responsible for the Sunyaev–Zel’dovich effect. We show that the recovered profiles are unbiased with a scatter of about 10 per cent, slightly increasing towards the core and the outskirts of the cluster. We selected clusters in the mass range of $10^{13.5} \le M_{200} /({{\, h^{-1}\,{\rm {{\rm M}_{\odot }}}}}) \le 10^{15.5}$, spanning different dynamical states, from relaxed to disturbed haloes. We verify that both the accuracy and precision of this method show a slight dependence on the dynamical state, but not on the cluster mass. To further verify the consistency of our model, we fit the inferred total mass profiles with a Navarro–Frenk–White model and contrast the concentration values with those of the true profiles. We note that the inferred profiles are unbiased for higher concentration values, reproducing a trustworthy mass–concentration relation. The comparison with a widely used mass estimation technique, such as hydrostatic equilibrium, demonstrates that our method recovers the total mass that is not biased by non-thermal motions of the gas.

Mock galaxy surveys for HST and JWST from the IllustrisTNG simulations

ABSTRACT We present and analyse a series of synthetic galaxy survey fields based on the IllustrisTNG simulation suite. With the IllustrisTNG public data release and JupyterLab service, we generated a set of 12 light-cone catalogues covering areas from 5 to 365 square arcmin, similar to several JWST Cycle 1 programs, including JADES, CEERS, PRIMER, and NGDEEP. From these catalogues, we queried the public application programming interface to generate simple mock images in a series of broad-band filters used by JWST-NIRCam and the Hubble Space Telescope cameras. This procedure generates wide-area simulated mosaic images that can support investigating the predicted evolution of galaxies alongside real data. Using these mocks, we demonstrate a few simple science cases, including morphological evolution and close pair selection. We publicly release the catalogues and mock images through MAST, along with the code used to generate these projects, so that the astrophysics community can use these products in their scientific analyses of JWST deep field observations.

Photometric Redshift Estimates using Bayesian Neural Networks in the CSST Survey

Galaxy photometric redshift (photoz) is crucial in cosmological studies, such as weak gravitational lensing and galaxy angular clustering measurements. In this work, we try to extract photoz information and construct its probability distribution function (PDF) using the Bayesian neural networks from both galaxy flux and image data expected to be obtained by the China Space Station Telescope (CSST). The mock galaxy images are generated from the Hubble Space Telescope - Advanced Camera for Surveys (HST-ACS) and COSMOS catalogs, in which the CSST instrumental effects are carefully considered. In addition, the galaxy flux data are measured from galaxy images using aperture photometry. We construct a Bayesian multilayer perceptron (B-MLP) and Bayesian convolutional neural network (B-CNN) to predict photoz along with the PDFs from fluxes and images, respectively. We combine the B-MLP and B-CNN together, and construct a hybrid network and employ the transfer learning techniques to investigate the improvement of including both flux and image data. For galaxy samples with signal-to-noise ratio (SNR) > 10 in g or i band, we find the accuracy and outlier fraction of photoz can achieve σ NMAD = 0.022 and η = 2.35% for the B-MLP using flux data only, and σ NMAD = 0.022 and η = 1.32% for the B-CNN using image data only. The Bayesian hybrid network can achieve σ NMAD = 0.021 and η = 1.23%, and utilizing transfer learning technique can improve results to σ NMAD = 0.019 and η = 1.17%, which can provide the most confident predictions with the lowest average uncertainty.

TDCOSMO

The largest source of systematic errors in the time-delay cosmography method likely arises from the lens model mass distribution, where an inaccurate choice of model could in principle bias the value of H0. A Bayesian hierarchical framework has been proposed which combines lens systems with kinematic data, constraining the mass profile shape at a population level. The framework has been previously validated using a small sample of lensing galaxies drawn from hydro-simulations. The goal of this work is to expand the validation to a more general set of lenses consistent with observed systems, as well as confirm the capacity of the method to combine two lens populations: one which has time delay information and one which lacks time delays and has systematically different image radii. For this purpose, we generated samples of analytic lens mass distributions made of baryons+dark matter and fit the subsequent mock images with standard power-law models. Corresponding kinematics data were also emulated. The hierarchical framework applied to an ensemble of time-delay lenses allowed us to correct the H0 bias associated with model choice to find H0 within 1.5σ of the fiducial value. We then combined this set with a sample of corresponding lens systems which have no time delays and have a source at lower z, resulting in a systematically smaller image radius relative to their effective radius. The hierarchical framework has successfully accounted for this effect, recovering a value of H0 which is both more precise (σ ∼ 2%) and more accurate (0.7% median offset) than the time-delay set alone. This result confirms that non-time-delay lenses can nonetheless contribute valuable constraining power to the determination of H0 via their kinematic constraints, assuming they come from the same global population as the time-delay set.

A deep learning approach to infer galaxy cluster masses from Planck Compton-y parameter maps

Galaxy clusters are useful laboratories to investigate the evolution of the Universe, and accurately measuring their total masses allows us to constrain important cosmological parameters. However, estimating mass from observations that use different methods and spectral bands introduces various systematic errors. This paper evaluates the use of a Convolutional Neural Network (CNN) to reliably and accurately infer the masses of galaxy clusters from the Compton-y parameter maps provided by the Planck satellite. The CNN is trained with mock images generated from hydrodynamic simulations of galaxy clusters, with Planck's observational limitations taken into account. We observe that the CNN approach is not subject to the usual observational assumptions, and so is not affected by the same biases. By applying the trained CNNs to the real Planck maps, we find cluster masses compatible with Planck measurements within a 15% bias. Finally, we show that this mass bias can be explained by the well known hydrostatic equilibrium assumption in Planck masses, and the different parameters in the Y500-M500 scaling laws. This work highlights that CNNs, supported by hydrodynamic simulations, are a promising and independent tool for estimating cluster masses with high accuracy, which can be extended to other surveys as well as to observations in other bands.

X-ray morphology of cluster-mass haloes in self-interacting dark matter

ABSTRACT We perform cosmological zoom-in simulations of 19 relaxed cluster-mass haloes with the inclusion of adiabatic gas in the cold dark matter (CDM) and self-interacting dark matter (SIDM) models. These clusters are selected as dynamically relaxed clusters from a parent simulation with $M_{\rm 200} \simeq (1\!-\!3)\times 10^{15}{\, \rm M_\odot }$. Both the dark matter and the intracluster gas distributions in SIDM appear more spherical than their CDM counterparts. Mock X-ray images are generated based on the simulations and are compared to the real X-ray images of 84 relaxed clusters selected from the Chandra and ROSAT archives. We perform ellipse fitting for the isophotes of mock and real X-ray images and obtain the ellipticities at cluster-centric radii of $r\simeq 0.1\!-\!0.2R_{\rm 200}$. The X-ray isophotes in SIDM models with increasing cross-sections are rounder than their CDM counterparts, which manifests as a systematic shift in the distribution function of ellipticities. Unexpectedly, the X-ray morphology of the observed non-cool-core clusters agrees better with SIDM models with cross-section $(\sigma /m)= 0.5\!-\!1\, {\rm cm}^2\, {\rm g}^{-1}$ than CDM and SIDM with $(\sigma /m)=0.1\, {\rm cm}^2\, {\rm g}^{-1}$. Our statistical analysis indicates that the latter two models are disfavoured at the $68{{\ \rm per\ cent}}$ confidence level (as conservative estimates). This conclusion is not altered by shifting the radial range of measurements or applying a temperature selection criterion. However, the primary uncertainty originates from the lack of baryonic physics in the adiabatic model, such as cooling, star formation and feedback effects, which still have the potential to reconcile CDM simulations with observations.