We present a combined radio/X-ray study of six massive galaxy clusters, aimed at determining the potential for heating of the intra-cluster medium (ICM) by non-central radio galaxies. Since X-ray cavities associated with the radio lobes of non-central galaxies are generally not detectable, we use Giant Metrewave Radio Telescope 610 MHz observations to identify jet sources and estimate their size, and Chandra data to estimate the pressure of the surrounding ICM. In the radio, we detect 4.5 per cent of galaxies above the spectroscopic survey limit (M$^{*}_{K}$ + 2.0) of the Arizona cluster redshift survey (ACReS) that covers five of our six clusters. Approximately one-tenth of these are extended radio sources. Using star formation (SF) rates determined from mid-infrared data, we estimate the expected contribution to radio luminosity from the stellar population of each galaxy, and find that most of the unresolved or poorly resolved radio sources are likely SF dominated. The relatively low frequency and good spatial resolution of our radio data allows us to trace SF emission down to galaxies of stellar mass ∼10 9.5 M⊙. We estimate the enthalpy of the (AGN-dominated) jet/lobe and tailed sources, and place limits on the energy available from unresolved radio jets. We find jet powers in the range ∼1043 to 1046 erg s−1, comparable to those of brightest cluster galaxies. Our results suggest that while cluster-central sources are the dominant factor balancing ICM cooling over the long-term, non-central sources may have a significant impact, and that further investigation is possible and warranted.
We evaluate the effectiveness of deep learning (DL) models for reconstructing the masses of galaxy clusters using X-ray photometry data from next-generation surveys. We establish these constraints using a catalogue of realistic mock eROSITA X-ray observations which use hydrodynamical simulations to model realistic cluster morphology, background emission, telescope response, and active galactic nucleus (AGN) sources. Using bolometric X-ray photon maps as input, DL models achieve a predictive mass scatter of $\sigma _{\ln M_\mathrm{500c}} = 17.8~{{\ \rm per\ cent}}$, a factor of two improvements on scalar observables such as richness Ngal, 1D velocity dispersion σv,1D, and photon count Nphot as well as a 32 per cent improvement upon idealized, volume-integrated measurements of the bolometric X-ray luminosity LX. We then show that extending this model to handle multichannel X-ray photon maps, separated in low, medium, and high energy bands, further reduces the mass scatter to 16.2 per cent. We also tested a multimodal DL model incorporating both dynamical and X-ray cluster probes and achieved marginal gains at a mass scatter of 15.9 per cent. Finally, we conduct a quantitative interpretability study of our DL models and find that they greatly down-weight the importance of pixels in the centres of clusters and at the location of AGN sources, validating previous claims of DL modelling improvements and suggesting practical and theoretical benefits for using DL in X-ray mass inference.
more » « less- NSF-PAR ID:
- 10434301
- Publisher / Repository:
- Oxford University Press
- Date Published:
- Journal Name:
- Monthly Notices of the Royal Astronomical Society
- Volume:
- 524
- Issue:
- 3
- ISSN:
- 0035-8711
- Format(s):
- Medium: X Size: p. 3289-3302
- Size(s):
- ["p. 3289-3302"]
- Sponsoring Org:
- National Science Foundation
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