Search arXiv⌕ Search
Home/Archive/arXiv

arXiv · 1608.03653

The morphology and kinematics of neutral hydrogen in the vicinity of z=0 galaxies with Milky Way masses -- a study with the Illustris simulation

Guinevere Kauffmann·Sanchayeeta Borthakur·Dylan Nelson
View original source ↗Read source document ↗Export metadata ↓

Abstract

We analyze the properties of the circumgalactic gas (CGM) around 120 galaxies with stellar and dark matter halo masses similar to that of the Milky Way. We focus on the morphology and kinematics of the neutral hydrogen and how this depends on f_g, the ratio of gas-to-stellar mass within the optical radius. In gas-rich galaxies with f_g > 0.1, gas temperatures rise slowly from center of the halo out to the virial radius and average neutral gas column densities remain above 10^19 atoms cm^-2 out to radii of 50-70 kpc. In gas-poor galaxies with f_g < 0.1, gas temperatures rise quickly outside the edge of the disk to 10^6 K, and then remain fixed out to radii of 100 kpc. The column density of neutral gas quickly drops below 10^19 atoms cm^-2 at radii of 10 kpc. Neutral gas distributions are also more asymmetric in gas-poor galaxies. Most of the differences between gas-poor and gas-rich galaxies in the Illustris simulation can be attributed to the effects of "radio-mode" AGN feedback. In the Illustris simulation, the circumgalactic gas is found to rotate coherently about the center of the galaxy with a maximum rotational velocity of around 200 km/s. In gas-rich galaxies, the average coherence length of the rotating gas is 40 kpc, compared to 10 kpc in gas-poor galaxies. In the very most gas-rich systems, the CGM can rotate coherently over scales of 70-100 kpc. We discuss our results in the context of recent observations of the CGM in low mass galaxies via UV absorption-line spectroscopy and deep 21cm observations of edge-on spiral galaxies.

Explore related subjects

astro-ph.GA

Keep this discovery

Explore connections, maps & timelines

BibTeXRIS

Guinevere Kauffmann, Sanchayeeta Borthakur, Dylan Nelson. 2016-08-15. The morphology and kinematics of neutral hydrogen in the vicinity of z=0 galaxies with Milky Way masses -- a study with the Illustris simulation. https://doi.org/10.1093/mnras%2Fstw1950

Cite the original work for its findings. Save a collection to share your selection of sources.

KEEP EXPLORING

Related papers

arXiv2026

Spatially Resolved Physical Properties of Young Star Clusters and Star-forming Clumps in the Brightest z>6 Galaxy, the Strongly Lensed Cosmic Spear at z=6.2

We present spatially resolved analysis of stellar populations in the brightest $z>6$ galaxy known to date (AB mag 23), the strongly lensed MACS0308$-$zD1 (dubbed the ``Cosmic Spear'') at $z_{\rm spec}=6.2$. New JWST NIRCam imaging and high-resolution NIRSpec IFU spectroscopy span the rest-frame ultraviolet to optical. The NIRCam imaging reveals bright star-forming clumps and a tail consisting of three distinct, extremely compact star clusters that are multiply-imaged by gravitational lensing. The star clusters have delensed effective radii of $R_{\rm{eff}} \lesssim 8$ pc, stellar masses of $M_{*} \sim 10^{6}-10^{7}\,M_{\odot}$, and high stellar mass surface densities of $Σ_{*} \gtrsim 2\times 10^{4}\,M_{\odot}~\rm{pc}^{-2}$. While their stellar populations are very young ($\sim 6-11$ Myr), their dynamical ages exceed unity, consistent with the clusters being gravitationally bound systems. Placing the star clusters in the size vs.~stellar mass density plane, we find they occupy a region similar to other high-redshift star clusters within galaxies observed recently with JWST, being significantly more massive and denser than local star clusters. Spatially resolved analysis of the brightest clump reveals a compact, intensely star-forming core. The ionizing photon production efficiency ($ξ_{\rm{ion}}$) is slightly suppressed in this central region, potentially indicating a locally elevated Lyman continuum escape fraction facilitated by feedback-driven channels.

astro-ph.GA↗
arXiv2026

Predicting Supermassive Black Hole-Host Mass Offsets from Broadband Photometry Across Cosmological Simulations with Forecasts for LSST

The possibility of over-massive black holes suggested by James Webb Space Telescope photometric discoveries of 'little red dots', may disfavor light supermassive black hole (SMBH) seeds. However, what should constitute the mass (range) of 'heavy' seeds remains relatively unconstrained. Moreover, Vera C Rubin Observatory's Legacy Survey of Space and Time will photometrically characterize galaxies without direct black hole mass measurements. We forward-model the SIMBA, IllustrisTNG, and EAGLE cosmological simulations into the photometric bands of LSST to train an ensemble machine learning classifier. Our framework achieves $91\%$--$94\%$ accuracy across SIMBA and IllustrisTNG in distinguishing between over-massive and under-massive SMBH growth regimes under LSST magnitude limits, using only broadband photometry. Furthermore, cross-simulation transfer experiments (training on one cosmological simulation and evaluating on another using rank-normalized features) achieve $83\%$--$89\%$ accuracy. This suggests the relative photometric ordering of growth regimes is largely preserved even across fundamentally different sub-grid SMBH feedback prescriptions. Signal decomposition shows our classification is driven by host galaxy colors ($82\%$--$87\%$ accuracy) and, relatedly, the accretion-state's spectral energy distribution shape as opposed to an inversion of our forward model's analytical luminosity prescription. Given that the evaluated simulations employ heavy seed prescriptions ($\geq 10^{4}~M_\odot$), our methodology establishes a validated baseline for classifying post-seeding growth regimes.

astro-ph.GA↗
arXiv2026

Cross Subtype Transferability of Machine Learning Photometric Redshift Relations in Low Redshift Seyfert AGN

Photometric redshift estimation for active galactic nuclei (AGN) is complicated by the combined effects of host-galaxy light, nuclear emission, dust attenuation, and broadband spectral diversity. We investigate whether machine learning photo-z relations trained on one low-redshift Seyfert subtype remain valid when transferred to another, and whether probabilistic subtype classification can be used to identify sources for which a specialised regressor is reliable. Using spectroscopically selected Seyfert I and Seyfert II samples from SDSS, matched to AllWISE photometry over 0 < z_spec <= 0.6, we constructed a common 45-feature representation from SDSS ugriz and WISE W1-W4 data. Random Forest and XGBoost regressors were evaluated within each subtype, followed by controlled cross-subtype transfer tests, redshift and sample size-matched experiments, feature ablations, and an independent classifier-gated regression test. The subtype specific models achieved strong within-sample performance, with the Seyfert II model reaching R2 = 0.965 and sigma_NMAD = 0.0169. However, transfer between Seyfert I and Seyfert II produced a clear and asymmetric degradation in accuracy that persisted after matching the samples and restricting the photometric inputs. A probabilistic Seyfert classifier further identified subsets for which the Seyfert II regressor was more reliable, while extrapolation beyond the redshift range represented in training produced systematic underestimation. These results demonstrate that AGN photo-z performance depends strongly on the population and redshift domain represented in the training data, supporting subtype-aware calibration and applicability-based source selection.

astro-ph.GA↗