arXiv subjects

John ZuHone

Publications and source records attributed to John ZuHone.

At least 19 recordsLinked to original sources

arXiv2026

XRISM observations of the Perseus cluster along two arms: Chaotic ICM motions probed by resonant scattering

XRISM has mapped gas velocities across the core of the Perseus cluster, separating the kinematic effects of mergers and AGN feedback. The physical properties of these motions remain unclear: are they a superposition of bulk flows, predominantly random/turbulent motions, or a mixture of both? Without resolving this question, constraints on the nonthermal pressure fraction and heating rate remain uncertain, as both assume predominantly random motions. Unlike emission line broadening, resonant scattering is most sensitive to small-scale, random motions rather than coherent bulk flows. Taking advantage of the extensive XRISM coverage of the Perseus cluster, we detect the full effects of resonant scattering on the He{\alpha} w line for the first time. This includes flux suppression in the cluster center, enhancement in the outer regions, and non-Gaussianity in the emission line. We employ radiative transfer simulations to constrain the amplitude of small-scale ICM velocities in the inner 60 kpc of Perseus, finding them to be consistent with the line broadening measurements within the uncertainties. This indicates the observed velocity dispersion is primarily due to small-scale random motions in the central Perseus regions rather than coherent bulk flows. We further explore potential anisotropy of these motions, showing that they are consistent with isotropic or radial motions rather than tangential ones. Longer XRISM observations are required to improve these anisotropy constraints. Finally, we explore azimuthal variations between the two complete radial arms observed by XRISM.

astro-ph.HE↗

arXiv2026

Lynx2030 Science Analysis Group: Final Report

The Lynx2030 Science Analysis Group (SAG) was convened to reassess the scientific goals and technical drivers of the Lynx mission concept amid a rapidly evolving astrophysics landscape. Building on the original Lynx Concept Study, the SAG examined how recent discoveries, emerging facilities, and advances in instrumentation influence the scientific opportunities for a next-generation flagship X-ray observatory. Through focused working groups, the SAG investigated the scientific impact of enhanced capabilities: (i) improved angular resolution, (ii) broader bandpass coverage, (iii) an enhanced microcalorimeter, (iv) new capabilities and observing modes, and (v) larger fields of view. Across a broad range of topics, from the formation of the first black holes and the evolution of galaxies to the baryon cycle, compact objects, stellar explosions, multi-messenger astrophysics, and the dynamic high-energy Universe, the SAG finds that the scientific motivation for a Lynx-class observatory remains compelling and, in many areas, has significantly strengthened over the past decade, prominently through JWST's discovery of the "Little Red Dots", likely massive accreting black holes in infant galaxies whose nature is fundamentally an X-ray question. This report shows that modest extensions beyond the original Lynx design reference mission can unlock transformative science while preserving the observatory's core architecture. Powerful current and future facilities such as Roman, Rubin, JWST, SKA, ngVLA, LISA, and NewAthena highlight the unique role a high-angular-resolution, high-throughput X-ray observatory would play in the multi-wavelength and multi-messenger ecosystem of the 2030s and beyond. The findings of the Lynx2030 SAG confirm Lynx's central vision: an unprecedented view of the hot and energetic Universe, enabling discoveries that will define high-energy astrophysics in the coming decades.

astro-ph.IM↗

arXiv2026

Ardua: Unveiling the Baryon Cycle from Stars to the Cosmic Web

The circumgalactic medium (CGM) -- the multiphase gas reservoirs surrounding galaxies -- remains the least understood component of the baryon cycle governing galaxy growth, despite its central role in the Astro2020 Decadal Survey's priorities. Existing constraints come almost exclusively from pencil-beam absorption spectroscopy, leaving the spatial structure, kinematics, and phase interactions of CGM gas fundamentally unmapped. We present Ardua, a mission concept for NASA's ASTRA Initiative that combines wide-field far-ultraviolet spectroscopy with a Line Emission Mapper (LEM)-derived X-ray microcalorimeter instrument to obtain the first comprehensive emission maps spanning the full CGM temperature range, including cool neutral gas, ionized warm-hot phase gas, and the volume-filling hot corona. By observing more than 50 nearby galaxies comprehensively in the UV and X-ray, Ardua will test competing galaxy formation models, resolve multiphase gas flows and feedback-driven outflows, and extend baryon-cycle science to the intergalactic medium and the environments of exoplanet-hosting stars. Beyond its core CGM/IGM program, Ardua's wide-field, high-sensitivity instruments are designed to serve as a flexible community resource, supporting guest-investigator science across astrophysics. No planned or approved mission is designed to deliver this combined UV/X-ray survey capability.

astro-ph.IM↗

arXiv2026

Supersonic Motion in the Driving Region of M82

The prototypical starburst galaxy M82 is host to an expansive, multiphase outflow whose driving mechanism is not fully understood. Longstanding models suggest that energy and mass injection from supernova into the hottest phase of the galactic wind could drive the cooler phases, but validating these models has been difficult due to the lack of constraints on the hot wind energetics. The high-resolution spectral capabilities of XRISM have generated the tightest constraints to date on the temperatures of the hot wind, as well as the first direct measurement of its velocity dispersion. In this work, we use these new observational constraints to test a model of a supernova-driven free wind. We generate a suite of highly idealized hydrodynamic simulations varying the energy and mass loading of the starburst and construct mock spectra to compare against the XRISM results. We find that the observed velocity dispersion is impossible to replicate using our free-wind model alone, and extra broadening is required to fit the spectrum. We interpret this broadening to be due not to bulk outflow, but rather to smaller scale non-thermal motions in the driving region of the starburst. This implies supersonic motion (Mach 1.71-3.14) of the hot gas in the central region of the galaxy. As supersonic motions are unexpected, it is possible that a significant amount of the energy that should go into heating the gas is instead going towards other sources such as amplifying magnetic fields and driving cosmic rays.

astro-ph.GA↗

arXiv2026

Lensing-Reconstructed Dark Matter-Intracluster Medium Coherence as a Probe of Cluster Dynamical State: Application to HSTFF, RELICS, and CLASH Clusters

We present the first application of Fourier-space coherence analysis between the lensing-reconstructed projected mass distribution and the X-ray-emitting intracluster medium to a sample of 49 observed galaxy clusters. Using publicly available HST convergence maps from the Hubble Frontier Fields, CLASH, and RELICS programs, together with Chandra X-ray imaging, we measure the scale-dependent coherence between the dark-matter-dominated surface mass density and the hot baryonic gas. We use the coherence length, l_CR, defined as the scale above which the two maps remain at least 90% coherent, as a diagnostic of cluster dynamical state. Across the sample, dynamically relaxed systems exhibit high coherence over a broad range of scales and small l_CR/r500, while disturbed and merging systems show a loss of coherence on intermediate and small scales, yielding larger l_CR/r500. The inferred coherence lengths show sensitivity to lens-model assumptions and to the heterogeneous extent of the available convergence maps. Nevertheless, the coherence signal remains physically interpretable and provides a stringent measure of dark-matter-gas alignment. Applying a conservative threshold, l_CR/r500 < 0.2, we find that only 16% of the sample is relaxed; this fraction rises to 41% for a more permissive threshold of l_CR/r500 < 0.4. Relative to previous X-ray and morphological classifications, we find a 24% disagreement, with the coherence method identifying more systems as dynamically disturbed. These results demonstrate that lensing-X-ray coherence provides a complementary, scale-resolved probe of cluster dynamical state, while highlighting the need for homogeneous, wide-field weak-lensing maps to control reconstruction and field-of-view systematics.

astro-ph.CO↗

arXiv2026

Estimating the triaxiality of massive clusters from 2D observables in MillenniumTNG with machine learning

Properties of massive galaxy clusters, such as mass abundance and concentration, are sensitive to cosmology, making cluster statistics a powerful tool for cosmological studies. However, favoring a more simplified, spherically symmetric model for galaxy clusters can lead to biases in the estimates of cluster properties. In this work, we present a deep-learning approach for estimating the triaxiality and orientations of massive galaxy clusters (those with masses $\gtrsim 10^{14}\,M_\odot h^{-1}$) from 2D observables. We utilize the flagship hydrodynamical volume of the suite of cosmological-hydrodynamical MillenniumTNG (MTNG) simulations as our ground truth. Our model combines the feature extracting power of a convolutional neural network (CNN) and the message passing power of a graph neural network (GNN) in a multi-modal, fusion network. Our model is able to extract 3D geometry information from 2D idealized cluster multi-wavelength images (soft X-ray, medium X-ray, hard X-ray and tSZ effect) and mathematical graph representations of 2D cluster member observables (line-of-sight radial velocities, 2D projected positions and V-band luminosities). Our network improves cluster geometry estimation in MTNG by $30\%$ compared to assuming spherical symmetry. We report an $R^2 = 0.85$ regression score for estimating the major axis length of triaxial clusters and correctly classifying $71\%$ of prolate clusters with elongated orientations along our line-of-sight.

astro-ph.CO↗

arXiv2026

Probable Detection of a Cooler Gas Component in the Perseus Cluster with XRISM

We present an analysis of the temperature structure of the Perseus cluster atmosphere using XRISM Resolve observations. The average temperature rises from 3.3 keV near the nucleus of NGC 1275 to 8 keV at 10 arcmin (210 kpc), which is consistent with Chandra and XMM measurements. The velocity and velocity dispersion profiles are broadly consistent with those in arXiv:2509.04421. While the gas at altitudes beyond $\sim60$ kpc can be modeled as a single temperature plasma, we find evidence for more than one gas phase in the inner $\sim60$ kpc. The hotter gas component, traced primarily by the Fe He$α$ line, has a velocity dispersion of $\lesssim140$ km s$^{-1}$. We detect a cooler, $\sim1.87-2.43$ keV, gas component with a velocity dispersion of $\sim300-400$ km s$^{-1}$ and a bulk velocity of $\sim 21-213$ km s$^{-1}$ with respect to the central galaxy. These ranges reflect large systematic uncertainties associated with modeling spatial-spectral mixing and the bright central point source. Potential low energy gain variations may add additional uncertainties. The cooler component is identified by broad wings in prominent emission lines, most notably S Ly$α$ and Fe He$α$. This cooler component's Mach number $\sim0.73-0.96$ and non-thermal pressure fraction of $\sim22.9-33.7\%$ are much higher than found for the hotter gas. The cooler gas may be associated with merging halos along the line of sight which formed the cool, sloshing spiral and/or cooling gas being disturbed by the radio jets and lobes.

astro-ph.HE↗

arXiv2026

Cool-Core Destruction in Merging Clusters with AGN Feedback and Radiative Cooling

The origin of cool-core (CC) and non-cool-core (NCC) dichotomy of galaxy clusters remains uncertain. Previous simulations have found that cluster mergers are effective in destroying CCs but fail to prevent overcooling in cluster cores when radiative cooling is included. Feedback from active galactic nuclei (AGN) is a promising mechanism for balancing cooling in CCs; however, the role of AGN feedback in CC/NCC transitions remains elusive. In this work, we perform three-dimensional binary cluster merger simulations incorporating AGN feedback and radiative cooling, aiming to investigate the heating effects from mergers and AGN feedback on CC destruction. We vary the mass ratio and impact parameter to examine the entropy evolution of different merger scenarios. We find that AGN feedback is essential in regulating the merging clusters, and that CC destruction depends on the merger parameters. Our results suggest three scenarios regarding CC/NCC transitions: (1) CCs are preserved in minor mergers or mergers that do not trigger sufficient heating, in which cases AGN feedback is crucial for preventing the cooling catastrophe; (2) CCs are transformed into NCCs by major mergers during the first core passage, and AGN feedback is subdominant; (3) in major mergers with a large impact parameter, mergers and AGN feedback operate in concert to destroy the CCs.

astro-ph.CO↗

arXiv2026

Effects of Viscosity on Sloshing Cold Fronts in Galaxy Clusters

The viscous properties of the intracluster medium (ICM) remain poorly constrained. Cold fronts-sharp discontinuities formed during cluster mergers-offer a potential avenue to probe the effective viscosity of the ICM. Velocity shear across these fronts should generate Kelvin-Helmholtz instabilities (KHI), unless viscosity or magnetic tension suppresses them. We perform cluster merger simulations incorporating four ICM viscosity models: (A) inviscid, (B) isotropic Spitzer viscosity, (C) anisotropic Braginskii viscosity, and (D) Braginskii viscosity limited by microinstabilities. The isotropic Spitzer viscosity (case B) strongly suppresses KHI, producing smooth cold front surfaces, while the inviscid (A) and microinstability-limited (D) cases show prominent ripples. The Braginskii case (C) yields intermediate suppression. We also vary the plasma $β$ parameter ($β\approx$ 100 and 1600) to examine how a changing magnetic field strength affects the results. Stronger magnetic fields further suppress KHI, leading to smoother fronts and reduced differences between different viscosity models, while also widening the range of permitted pressure anisotropies when microinstability-based limiters are present. These results indicate that both viscosity and magnetic fields play crucial roles in stabilising sloshing cold fronts in galaxy clusters.

astro-ph.HE↗

arXiv2025

Exploring the statistical properties of double radio relics in the TNG-Cluster and TNG300 simulations

Double radio relics, pairs of diffuse radio features located on opposite sides of merging galaxy clusters, are a rare subclass of radio relics that are believed to trace merger shocks and provide valuable constraints on plasma acceleration models and merger history. With the number of known double relics growing in recent and upcoming radio surveys, statistical analyses of their properties are becoming feasible. In this study, we utilize the cosmological magnetohydrodynamics zoom-in simulations TNG-Cluster, in combination with TNG300-1, to examine the statistical properties of double radio relics. The simulated double relic pairs exhibit a wide range of luminosity ratios, broadly consistent with the observations. We find that the two relics in a given double system often differ significantly in their shock properties and magnetic field strengths. This diversity implies that the observed brightness asymmetry in the pair cannot be explained by a single factor alone, but instead reflects an interplay of multiple physical parameters. Nevertheless, double radio relics tend to align with the collision axis within $\sim30^{\circ}$ and their separation ($d_{\rm drr}$) correlates tightly with the time since collision (TSC) as ${\rm TSC~[Gyr]} = 0.52 d_{\rm drr}/R_{500\rm c} - 0.24$, allowing it to be inferred with an accuracy of $\sim0.2~\rm Gyr$. With the statistical samples of simulated radio relics, we predict that low-mass clusters will constitute the dominant population of double radio relic systems detected with upcoming surveys such as SKA. These results demonstrate that double radio relics can serve as robust probes of merger dynamics and plasma acceleration, and that simulations provide critical guidance for interpreting the large samples expected from next-generation radio surveys.

astro-ph.GA↗

arXiv2025

Mapping the Perseus Galaxy Cluster with XRISM: Gas Kinematic Features and their Implications for Turbulence

In this paper, we present extended gas kinematic maps of the Perseus cluster by combining five new XRISM/Resolve pointings observed in 2025 with four Performance Verification datasets from 2024, totaling 745 ks net exposure. To date, Perseus remains the only cluster that has been extensively mapped out to ~0.7$r_{2500}$ by XRISM/Resolve, while simultaneously offering sufficient spatial resolution to resolve gaseous substructures driven by mergers and AGN feedback. Our observations cover multiple radial directions and a broad dynamical range, enabling us to characterize the intracluster medium kinematics up to the scale of ~500 kpc. In the measurements, we detect high velocity dispersions ($\simeq$300 km/s) in the eastern region of the cluster, corresponding to a nonthermal pressure fraction of $\simeq$7-13%. The velocity field outside the AGN-dominant region can be effectively described by a single, large-scale kinematic driver based on the velocity structure function, which statistically favors an energy injection scale of at least a few hundred kpc. The estimated turbulent dissipation energy is comparable to the gravitational potential energy released by a recent merger, implying a significant role of turbulent cascade in the merger energy conversion. In the bulk velocity field, we observe a dipole-like pattern along the east-west direction with an amplitude of $\simeq\pm$200-300 km/s, indicating rotational motions induced by the recent merger event. This feature constrains the viewing direction to ~30$^\circ$-50$^\circ$ relative to the normal of the merger plane. Our hydrodynamic simulations suggest that Perseus has experienced at least two energetic mergers since redshift z~1, the latest associated with the radio galaxy IC310. This study showcases exciting scientific opportunities for future missions with high-resolution spectroscopic capabilities (e.g., HUBS, LEM, and NewAthena).

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arXiv2025

The Importance of Being Adaptable: An Exploration of the Power and Limitations of Domain Adaptation for Simulation-Based Inference with Galaxy Clusters

The application of deep machine learning methods in astronomy has exploded in the last decade, with new models showing remarkably improved performance on benchmark tasks. Not nearly enough attention is given to understanding the models' robustness, especially when the test data are systematically different from the training data, or "out of domain." Domain shift poses a significant challenge for simulation-based inference, where models are trained on simulated data but applied to real observational data. In this paper, we explore domain shift and test domain adaptation methods for a specific scientific case: simulation-based inference for estimating galaxy cluster masses from X-ray profiles. We build datasets to mimic simulation-based inference: a training set from the Magneticum simulation, a scatter-augmented training set to capture uncertainties in scaling relations, and a test set derived from the IllustrisTNG simulation. We demonstrate that the Test Set is out of domain in subtle ways that would be difficult to detect without careful analysis. We apply three deep learning methods: a standard neural network (NN), a neural network trained on the scatter-augmented input catalogs, and a Deep Reconstruction-Regression Network (DRRN), a semi-supervised deep model engineered to address domain shift. Although the NN improves results by 17% in the Training Data, it performs 40% worse on the out-of-domain Test Set. Surprisingly, the Scatter-Augmented Neural Network (SANN) performs similarly. While the DRRN is successful in mapping the training and Test Data onto the same latent space, it consistently underperforms compared to a straightforward Yx scaling relation. These results serve as a warning that simulation-based inference must be handled with extreme care, as subtle differences between training simulations and observational data can lead to unforeseen biases creeping into the results.

astro-ph.IM↗

arXiv2025

Mapping the Nearest Ancient Sloshing Cold Front in the Sky with XMM-Newton

The Virgo Cluster is the nearest cool core cluster that features two well-studied sloshing cold fronts at radii of $r \approx 30$ kpc and $r \approx 90$ kpc, respectively. In this work, we present results of XMM-Newton mosaic observations of a third, southwestern, cold front at a radius of $r \approx 250$ kpc, originally discovered with Suzaku. All three cold fronts are likely to be parts of an enormous swirling pattern, rooted in the core. The comparison with a numerical simulation of a binary cluster merger indicates that these cold fronts were produced in the same single event $-$ likely the infall of M49 from the northwest of Virgo and it is now re-entering the cluster from the south. This outermost cold front has probably survived for $2-3$ Gyr since the disturbance. We identified single sharp edges in the surface brightness profiles of the southern and southwestern sections of the cold front, whereas the western section is better characterized with double edges. This implies that magnetic fields have preserved the leading edge of the cold front, while its western side is beginning to split into two cold fronts likely due to Kelvin-Helmholtz instabilities. The slopes of the 2D power spectrum of the X-ray surface brightness fluctuations, derived for the brighter side of the cold front, are consistent with the expectation from Kolmogorov turbulence. Our findings highlight the role of cold fronts in shaping the thermal dynamics of the intracluster medium beyond the cluster core, which has important implications for cluster cosmology. Next-generation X-ray observatories, such as the proposed AXIS mission, will be ideal for identifying and characterizing ancient cold fronts.

astro-ph.HE↗

arXiv2025

Revisiting Galaxy Cluster Scaling Relations through Dark Matter-Gas Coherence: Scatter Dependence on Dynamical State

Galaxy clusters, the most massive, dark-matter-dominated, and most recently assembled structures in the Universe, are key tools for probing cosmology. However, uncertainties in scaling relations that connect cluster mass to observables like X-ray luminosity and temperature remain a significant challenge. In this paper, we present the results of an extensive investigation of 329 simulated clusters from Illustris TNG300 cosmological simulations. Our analysis involves cross-correlating dark matter and the hot X-ray-emitting gas, considering both the 3D and 2D projected distributions to account for projection effects. We demonstrate that this approach is highly effective in evaluating the dynamical state of these systems and validating the often-utilized assumption of hydrostatic equilibrium, which is key for inferring cluster masses and constructing scaling relations. Our study revisits both the X-ray luminosity-mass and X-ray temperature-mass scaling relations, and demonstrates how the scatter in these relations correlates with the clusters' dynamical state. We demonstrate that matter-gas coherence enables the identification of an optimal set of relaxed clusters, reducing scatter in scaling relations by up to 40%. This innovative approach, which integrates higher-dimensional insights into scaling relations, might offer a new path to further reduce uncertainties in determining cosmological parameters from galaxy clusters.

astro-ph.CO↗

arXiv2025

X-ray emission signatures of galactic feedback in the hot circumgalactic medium: predictions from cosmological hydrodynamical simulations

Little is currently known about the physical properties of the hot circumgalactic medium (CGM) surrounding massive galaxies. Next-generation X-ray observatories will enable detailed studies of the hot CGM in emission. To support these future efforts, we make predictions of the X-ray emission from the hot CGM using a sample of 28 $\sim$Milky Way-mass disk galaxies at $z=0$ from seven cosmological hydrodynamical simulation suites incorporating a wide range of galactic feedback prescriptions. The X-ray surface brightness (XSB) morphology of the hot CGM varies significantly across simulations. XSB-enhanced outflows and bubble-like structures are predicted in many galaxies simulated with AGN feedback and in some stellar-feedback-only galaxies, while other galaxies exhibit more isotropic XSB distributions at varying brightnesses. Galaxies simulated without cosmic ray physics exhibit radial XSB profiles with similar shapes ($\propto r^{-3}$ within $20-200$ kpc), with scatter about this slope likely due to underlying feedback physics. The hot CGM kinematics also differ substantially: velocity maps reveal signatures of bulk CGM rotation and high-velocity biconical outflows, particularly in simulations incorporating AGN feedback. Some stellar-feedback-only models also generate similar AGN-like outflows, which we postulate is due to centrally-concentrated star formation. Simulations featuring AGN feedback frequently produce extended temperature enhancements in large-scale galactic outflows, while simulations incorporating cosmic ray physics predict the coolest CGM due to pressure support being provided by cosmic rays rather than hot CGM. Individually-resolved X-ray emission lines further distinguish hot CGM phases, with lower-energy lines (e.g., O VII) largely tracing volume-filling gas, and higher-energy lines (e.g., Fe XVII) highlighting high-velocity feedback-driven outflows.

astro-ph.GA↗

arXiv2025

Quantifying Observational Projection Effects with a Simulation-based hot CGM model

The hot phase of the circumgalactic medium (CGM) allows us to probe the inflow and outflow of gas within a galaxy, which is responsible for dictating the evolution of the galaxy. Studying the hot CGM sheds light on a better understanding of gas physics, which is crucial to inform and constrain simulation models. With the recent advances in observational measurements probing the hot CGM in X-rays and tSZ, we have a new avenue for widening our knowledge of gas physics and feedback by exploiting the information from current/future observations. In this paper, we use the TNG300 hydrodynamical simulations to build a fully self-consistent forward model for the hot CGM. We construct a lightcone and generate mock X-ray observations. We quantify the projection effects, namely the locally correlated large-scale structure in X-rays and the effect due to satellite galaxies misclassified as centrals which affects the measured hot CGM galactocentric profiles in stacking experiments. We present an analytical model that describes the intrinsic X-ray surface brightness profile across the stellar and halo mass bins. The increasing stellar mass bins result in decreasing values of $β$, the exponent quantifying the slope of the intrinsic galactocentric profiles. We carry forward the current state-of-the-art by also showing the impact of the locally correlated environment on the measured X-ray surface brightness profiles. We also present, for the first time, the effect of misclassified centrals in stacking experiments for three stellar mass bins: $10^{10.5-11}\ M_\odot$, $10^{11-11.2}\ M_\odot$, and $10^{11.2-11.5}\ M_\odot$. We find that the contaminating effect of the misclassified centrals on the stacked profiles increases when the stellar mass decreases.

astro-ph.GA↗

arXiv2025

Direct Evidence of a Major Merger in the Perseus Cluster

Although the Perseus cluster has often been regarded as an archetypical relaxed galaxy cluster, several lines of evidence including ancient, large-scale cold fronts, asymmetric plasma morphology, filamentary galaxy distribution, etc., provide a conflicting view of its dynamical state, suggesting that the cluster might have experienced a major merger. However, the absence of a clear merging companion identified to date hampers our understanding of the evolutionary track of the Perseus cluster consistent with these observational features. In this paper, through careful weak lensing analysis, we successfully identified the missing subcluster halo ($M_{200}=1.70^{+0.73}_{-0.59}\times10^{14}~M_{\odot}$) at the >5$σ$ level centered on NGC1264, which is located ~430 kpc west of the Perseus main cluster core. Moreover, a significant ($>3σ$) mass bridge, which is also traced by the cluster member galaxies, is detected between the Perseus main and sub clusters, which serves as direct evidence of gravitational interaction. With idealized numerical simulations, we demonstrate that a ~3:1 off-axis major merger can create the cold front observed ~700 kpc east of the main cluster core and also generate the observed mass bridge through multiple core crossings. This discovery resolves the long-standing puzzle of Perseus' dynamical state.

astro-ph.GA↗

arXiv2025

Galaxy cluster characterization with machine learning techniques

We present an analysis of the X-ray properties of the galaxy cluster population in the z=0 snapshot of the IllustrisTNG simulations, utilizing machine learning techniques to perform clustering and regression tasks. We examine five properties of the hot gas (the central cooling time, the central electron density, the central entropy excess, the concentration parameter, and the cuspiness) which are commonly used as classification metrics to identify cool core (CC), weak cool core (WCC) and non cool core (NCC) clusters of galaxies. Using mock Chandra X-ray images as inputs, we first explore an unsupervised clustering scheme to see how the resulting groups correlate with the CC/WCC/NCC classification based on the different criteria. We observe that the groups replicate almost exactly the separation of the galaxy cluster images when classifying them based on the concentration parameter. We then move on to a regression task, utilizing a ResNet model to predict the value of all five properties. The network is able to achieve a mean percentage error of 1.8% for the central cooling time, and a balanced accuracy of 0.83 on the concentration parameter, making them the best-performing metrics. Finally, we use simulation-based inference (SBI) to extract posterior distributions for the network predictions. Our neural network simultaneously predicts all five classification metrics using only mock Chandra X-ray images. This study demonstrates that machine learning is a viable approach for analyzing and classifying the large galaxy cluster datasets that will soon become available through current and upcoming X-ray surveys, such as eROSITA.

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