Retrieving the hot CGM physics from the X-ray radial profile from eROSITA with an IlustrisTNG-based forward model

TL;DR

The paper develops an IllustrisTNG (TNG300)-based forward model to interpret eROSITA stacked X-ray radial profiles around Milky Way–mass galaxies. By decomposing the emission into hot CGM around centrals and satellites and unresolved point sources (AGN/XRB), and by varying the underlying halo-mass distribution in mock catalogues, the authors show that halo mass strongly modulates the stacked X-ray luminosity. Fitting to the Full$_{\rm phot}$ data from zhang2024hot, Model 3 (mean $M_{200m} \approx 3.5\times10^{12}\rm M_\odot$) provides the best match, yielding ${L}_{X,\rm CGM} \approx 1.7\times10^{40}$ erg s$^{-1}$ within $R_{500c}$ and a satellite contribution ${L}_{X,\rm SAT} \approx 3\times10^{41}$ erg s$^{-1}$, with central CGM and point-source components each contributing ~40–50% at $\lesssim40$ kpc. The results constrain the allowable AGN/XRB luminosities and demonstrate a method to jointly infer hot CGM physics and AGN activity, offering a new avenue to test galaxy-formation models with current and upcoming X-ray surveys.

Abstract

Recent eROSITA measurements of the radial profiles of the hot CGM in the Milky-Way stellar mass (MW-mass) regime provide us with a new benchmark to constrain the hot gas around MW-mass central and satellite galaxies and their halo mass distributions. Modelling this rich data set with state-of-the-art hydrodynamical simulations is required to further our understanding of the shortcomings in the current paradigm of galaxy formation and evolution models. We develop forward models for the stacked X-ray radial surface brightness profile measured by eROSITA around MW-mass galaxies. Our model contains two emitting components: hot gas (around central galaxies and satellite galaxies hosted by more massive halos) and X-ray point sources (X-ray binaries and Active Galactic Nuclei). We model the hot gas profile using the TNG300-based products. We generate mock observations with our TNG300-based model (matching stellar mass and redshift with observations) with different underlying halo mass distributions. We show that for the same mean stellar mass, a factor 2x increase in the mean value of the underlying halo mass distribution results in a ~4x increase in the stacked X-ray luminosity from the hot CGM. The point sources are described by a simple point-spread-function (PSF) of eROSITA, and we fit their normalization in this work. Using empirical models to derive a permissible range of AGN and XRB luminosities in the MW-mass X-ray galaxy stack, we choose our forward model best describing the hot CGM for the eROSITA observations. We find that at < 40 kpc from the galaxy centre, the hot CGM from central galaxies and the X-ray point sources emission each account for 40-50% of the total X-ray emission budget. In summary, we show that the gas physics driving the shape of the observed hot CGM (in stellar-mass-selected samples) is tightly correlated by the underlying halo-mass distribution (abridged).

Figures (6)

• Figure 1: Forward models constructed in this work for the hot CGM from central galaxies by varying the underlying halo mass distribution. Left panel: The purple halo mass distribution (Model 1) is obtained from the mock central galaxy catalogue - constructed with the TNG300 lightcone (LC-TNG300) from Shreeram2024quantifying - for the X-ray stack from zhang2024hot that uses optically detected galaxies with photometric redshifts (Full$_{\rm phot}$) from LS DR9 dey2019overview. Note that the mock galaxy catalogue is generated by matching LC-TNG300 to Full$_{\rm phot}$ in stellar mass and redshift (see details in Sec. \ref{['subsec:mock']}); the median stellar mass and redshift of the Full$_{\rm phot}$ (and our mock catalogues) are $5.5\times 10^{10} \ {\rm M}_\odot$ and $0.14$, respectively. The underlying halo mass distribution of the Full$_{\rm phot}$ optical dataset is unknown. The pink distribution (Model 2; with mean $M_{\rm 200m} = 5.4\times 10^{12}\ {\rm M}_\odot$) discards the top $10\%$ most massive halos before the generation of the mock galaxy catalogue. The yellow distribution (Model 3; with mean $M_{\rm 200m} = 3.5\times 10^{12}\ {\rm M}_\odot$) discards the top $30\%$ most massive halos before the generation of the mock galaxy catalogue. Right panel: The corresponding X-ray surface brightness profiles in the $0.5-2$ kev energy band (for details on their generation see Sec. \ref{['subsec:fmodel_hot']}) for the three mock galaxy catalogues with different halo mass distributions, which are shown in the left panel. The profiles are convolved with the eROSITA PSF and they represents the Full$_{\rm phot}$ dataset in the stellar mass and redshift plane. Nevertheless, due to the impact of the underlying halo mass distribution, the shape and normalization of the hot CGM profiles are impacted, where discarding the most massive halos from the underlying halo distribution results in steeper profiles with lower normalizations.
• Figure 2: Comparison of the mean point source (AGN and XRB) luminosities from our three forward models (crosses, based on the different halo distributions shown in Fig. \ref{['fig:halo-models']}) with the empirically allowed range of XRB and total point source luminosities, as shown by the grey hatched region and the green shaded region, respectively. We estimate the contribution due to XRB emission using the aird2017x model. For estimating the AGN luminosity budget, ${L}_{X,\ \rm AGN}$, we use the aird2013primus model for the incidence rate distribution as a function of the $L_{X, \rm \ AGN}^{2-10\ \rm keV}$ keV. To covert the $2-10$ keV luminosity distribution in the $0.5-2$ keV band, we use an empirical obscuration model from Comparat2019agnmodel. For more details, see the text of Sec. \ref{['subsec:XRB']} and \ref{['subsec:AGN']}. This comparison favours model $3$, shown by the yellow cross, where the hot CGM component allows for a point source component with luminosity that agrees with empirical estimates from the low redshift universe.
• Figure 3: Decomposition of the X-ray stack of the galaxies in the photometric sample, Full$_{\rm phot}$, into contributions from hot gas events (centrals and satellites hosted by more massive host halos) and point sources (AGN and XRB). The orange data points from zhang2024hot are described with the model from this work (shown by the black solid line). The orange dashed-dotted line at $292$ kpc corresponds to the virial radius of the observational sample. The model is composed of the following: the hot CGM from central galaxies (yellow), the events around satellites probing the hot gas of their more massive host halos (green), and X-ray events from unresolved and resolved point-like sources comprising AGN and XRB (grey). The bottom panel shows the percentage deviation of the best-fit forward model from the data. The dashed-dotted lines show the $15\%$ level.
• Figure 4: Posterior probability distributions of the renormalization factor of the ${S}_{\rm X,\ sat}$ profile: $\mathcal{N}_{\rm sat}$, and the normalization of the point source component: $\mathcal{N}_{\rm ps}$, which are obtained by fitting the forward-model $3$ from this work to the Full$_{\rm phot}$ data points from zhang2024hot shown in Fig. \ref{['fig:best-fit']}. The vertical red lines in the diagonal plots correspond to the most likely value; the respective values are mentioned in the titles (refer to Tab. \ref{['tab:best-fit-params0']}). The black dashed lines are the $68\%$ confidence interval of the marginalized distribution of the free parameters. The contour plot marks the most likely values with the red cross, and the contours correspond to the $68\%, 95\%$ and $99.7\%$ confidence intervals.
• Figure 5: The fractional contribution to the total X-ray surface brightness profile of the hot CGM from central galaxies (yellow), the events around satellites probing the hot gas of their more massive host halos (green), and X-ray events from unresolved and resolved point-like sources comprising AGN and XRB (dashed grey line). The errors on the profiles are obtained from the posterior distributions of the MCMC fitting analysis