More Like this

1. IllustrisTNG Snapshots for 10 Gyr of Dynamical Evolution of Brightest Cluster Galaxies and Their Host Clusters

   https://doi.org/10.3847/1538-4357/ac8f23  

   Sohn, Jubee; Geller, Margaret J.; Vogelsberger, Mark; Borrow, Josh (October 2022, The Astrophysical Journal)

   Abstract We explore the redshift evolution of the dynamical properties of massive clusters and their brightest cluster galaxies (BCGs) at z < 2 based on the IllustrisTNG-300 simulation. We select 270 massive clusters with M 200 < 10 14 M ⊙ at z = 0 and trace their progenitors based on merger trees. From 67 redshift snapshots covering z < 2, we compute the 3D subhalo velocity dispersion as a cluster velocity dispersion ( σ cl ). We also calculate the 3D stellar velocity dispersion of the BCGs ( σ *,BCG ). Both σ cl and σ *,BCG increase as the universe ages. The BCG velocity dispersion grows more slowly than the cluster velocity dispersion. Furthermore, the redshift evolution of the BCG velocity dispersion shows dramatic changes at some redshifts resulting from dynamical interaction with neighboring galaxies (major mergers). We show that σ *,BCG is comparable with σ cl at z > 1, offering an interesting observational test. The simulated redshift evolution of σ cl and σ *,BCG generally agrees with an observed cluster sample for z < 0.3, but with large scatter. Future large spectroscopic surveys reaching to high redshift will test the implications of the simulations for the mass evolution of both clusters and their BCGs. 

   more » « less
2. The Evolution of AGN Activity in Brightest Cluster Galaxies

   https://doi.org/10.3847/1538-3881/ac5030  

   Somboonpanyakul, T.; McDonald, M.; Noble, A.; Aguena, M.; Allam, S.; Amon, A.; Andrade-Oliveira, F.; Bacon, D.; Bayliss, M. B.; Bertin, E.; et al (March 2022, The Astronomical Journal)

   Abstract We present the results of an analysis of Wide-field Infrared Survey Explorer (WISE) observations of the full 2500 deg 2 South Pole Telescope (SPT)-Sunyaev–Zel’dovich cluster sample. We describe a process for identifying active galactic nuclei (AGN) in brightest cluster galaxies (BCGs) based on WISE mid-IR color and redshift. Applying this technique to the BCGs of the SPT-SZ sample, we calculate the AGN-hosting BCG fraction, which is defined as the fraction of BCGs hosting bright central AGNs over all possible BCGs. Assuming an evolving single-burst stellar population model, we find statistically significant evidence (>99.9%) for a mid-IR excess at high redshift compared to low redshift, suggesting that the fraction of AGN-hosting BCGs increases with redshift over the range of 0 < z < 1.3. The best-fit redshift trend of the AGN-hosting BCG fraction has the form (1 + z ) 4.1±1.0 . These results are consistent with previous studies in galaxy clusters as well as as in field galaxies. One way to explain this result is that member galaxies at high redshift tend to have more cold gas. While BCGs in nearby galaxy clusters grow mostly by dry mergers with cluster members, leading to no increase in AGN activity, BCGs at high redshift could primarily merge with gas-rich satellites, providing fuel for feeding AGNs. If this observed increase in AGN activity is linked to gas-rich mergers rather than ICM cooling, we would expect to see an increase in scatter in the P cav versus L cool relation at z > 1. Last, this work confirms that the runaway cooling phase, as predicted by the classical cooling-flow model, in the Phoenix cluster is extremely rare and most BCGs have low (relative to Eddington) black hole accretion rates. 

   more » « less
3. The growth of brightest cluster galaxies and intracluster light over the past 10 billion years

   https://doi.org/10.1093/mnras/stz3236  

   DeMaio, Tahlia; Gonzalez, Anthony H; Zabludoff, Ann; Zaritsky, Dennis; Aldering, Greg; Brodwin, Mark; Connor, Thomas; Donahue, Megan; Hayden, Brian; Mulchaey, John S; et al (January 2020, Monthly Notices of the Royal Astronomical Society)

   null (Ed.)

   ABSTRACT We constrain the evolution of the brightest cluster galaxy plus intracluster light (BCG + ICL) using an ensemble of 42 galaxy groups and clusters that span redshifts of z = 0.05−1.75 and masses of M500,c= 2 × 1013−1015 M⊙. Specifically, we measure the relationship between the BCG + ICL stellar mass M⋆ and M500,c at projected radii 10 < r < 100 kpc for three different epochs. At intermediate redshift ($$\bar{z}=0.40$$), where we have the best data, we find M⋆ ∝ M500,c0.48 ± 0.06. Fixing the exponent of this power law for all redshifts, we constrain the normalization of this relation to be 2.08 ± 0.21 times higher at $$\bar{z}=0.40$$ than at high redshift ($$\bar{z}=1.55$$). We find no change in the relation from intermediate to low redshift ($$\bar{z}=0.10$$). In other words, for fixed M500,c, M⋆ at 10 < r < 100 kpc increases from $$\bar{z}=1.55$$ to $$\bar{z}=0.40$$ and not significantly thereafter. Theoretical models predict that the physical mass growth of the cluster from z = 1.5 to z = 0 within r500,c is 1.4×, excluding evolution due to definition of r500,c. We find that M⋆ within the central 100 kpc increases by ∼3.8× over the same period. Thus, the growth of M⋆ in this central region is more than a factor of 2 greater than the physical mass growth of the cluster as a whole. Furthermore, the concentration of the BCG + ICL stellar mass, defined by the ratio of stellar mass within 10 kpc to the total stellar mass within 100 kpc, decreases with increasing M500,c at all z. We interpret this result as evidence for inside–out growth of the BCG + ICL over the past 10 Gyr, with stellar mass assembly occurring at larger radii at later times. 

   more » « less
4. Redshift Evolution of the Feedback–Cooling Equilibrium in the Core of 48 SPT Galaxy Clusters: A Joint Chandra–SPT–ATCA Analysis

   https://doi.org/10.3847/1538-4357/acc38d  

   Ruppin, F.; McDonald, M.; Hlavacek-Larrondo, J.; Bayliss, M.; Bleem, L. E.; Calzadilla, M.; Edge, A. C.; Filipović, M. D.; Floyd, B.; Garmire, G.; et al (May 2023, The Astrophysical Journal)

   Abstract We analyze the cooling and feedback properties of 48 galaxy clusters at redshifts 0.4 < z < 1.3 selected from the South Pole Telescope (SPT) catalogs to evolve like the progenitors of massive and well-studied systems at z ∼ 0. We estimate the radio power at the brightest cluster galaxy (BCG) location of each cluster from an analysis of Australia Telescope Compact Array data. Assuming that the scaling relation between the radio power and active galactic nucleus (AGN) cavity power P cav observed at low redshift does not evolve with redshift, we use these measurements in order to estimate the expected AGN cavity power in the core of each system. We estimate the X-ray luminosity within the cooling radius L cool of each cluster from a joint analysis of the available Chandra X-ray and SPT Sunyaev–Zel’dovich (SZ) data. This allows us to characterize the redshift evolution of the P cav / L cool ratio. When combined with low-redshift results, these constraints enable investigations of the properties of the feedback–cooling cycle across 9 Gyr of cluster growth. We model the redshift evolution of this ratio measured for cool-core clusters by a log-normal distribution Log -  ( α + β z , σ 2 ) and constrain the slope of the mean evolution to β = −0.05 ± 0.47. This analysis improves the constraints on the slope of this relation by a factor of two. We find no evidence of redshift evolution of the feedback–cooling equilibrium in these clusters, which suggests that the onset of radio-mode feedback took place at an early stage of cluster formation. High values of P cav / L cool are found at the BCG location of noncool-core clusters, which might suggest that the timescales of the AGN feedback cycle and the cool core–noncool core transition are different. This work demonstrates that the joint analysis of radio, SZ, and X-ray data solidifies the investigation of AGN feedback at high redshifts. 

   more » « less
5. Augmenting astrophysical scaling relations with machine learning: Application to reducing the Sunyaev–Zeldovich flux–mass scatter

   https://doi.org/10.1073/pnas.2202074120  

   Wadekar, Digvijay; Thiele, Leander; Villaescusa-Navarro, Francisco; Hill, J. Colin; Cranmer, Miles; Spergel, David N.; Battaglia, Nicholas; Anglés-Alcázar, Daniel; Hernquist, Lars; Ho, Shirley (March 2023, Proceedings of the National Academy of Sciences)

   Complex astrophysical systems often exhibit low-scatter relations between observable properties (e.g., luminosity, velocity dispersion, oscillation period). These scaling relations illuminate the underlying physics, and can provide observational tools for estimating masses and distances. Machine learning can provide a fast and systematic way to search for new scaling relations (or for simple extensions to existing relations) in abstract high-dimensional parameter spaces. We use a machine learning tool called symbolic regression (SR), which models patterns in a dataset in the form of analytic equations. We focus on the Sunyaev-Zeldovich flux−cluster mass relation ( Y SZ − M ), the scatter in which affects inference of cosmological parameters from cluster abundance data. Using SR on the data from the IllustrisTNG hydrodynamical simulation, we find a new proxy for cluster mass which combines Y SZ and concentration of ionized gas ( c gas ): M ∝ Y conc 3/5 ≡ Y SZ 3/5 (1 − A c gas ). Y conc reduces the scatter in the predicted M by ∼20 − 30% for large clusters ( M ≳ 10 14 h −1 M ⊙ ), as compared to using just Y SZ . We show that the dependence on c gas is linked to cores of clusters exhibiting larger scatter than their outskirts. Finally, we test Y conc on clusters from CAMELS simulations and show that Y conc is robust against variations in cosmology, subgrid physics, and cosmic variance. Our results and methodology can be useful for accurate multiwavelength cluster mass estimation from upcoming CMB and X-ray surveys like ACT, SO, eROSITA and CMB-S4. 

   more » « less