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Abstract:

Many scientific investigations of photometric galaxy surveys require redshift estimates, whose uncertainty properties are best encapsulated by photometric redshift (photo-z) posterior probability density functions (PDFs). A plethora of photo-z PDF estimation methodologies abound, producing discrepant results with no consensus on a preferred approach. We present the results of a comprehensive experiment comparing 12 photo-z algorithms applied to mock data produced for The Rubin Observatory Legacy Survey of Space and Time Dark Energy Science Collaboration. By supplying perfect prior information, in the form of the complete template library and a representative training set as inputs to each code, we demonstrate the impact of the assumptions underlying each technique on the output photo-z PDFs. In the absence of a notion of true, unbiased photo-z PDFs, we evaluate and interpret multiple metrics of the ensemble properties of the derived photo-z PDFs as well as traditional reductions to photo-z point estimates. We report systematic biases and overall over/underbreadth of the photo-z PDFs of many popular codes, which may indicate avenues for improvement in the algorithms or implementations. Furthermore, we raise attention to the limitations of established metrics for assessing photo-z PDF accuracy; though we identify the conditional density estimate loss as a promising metric of photo-z PDF performance in the case where true redshifts are available but true photo-z PDFs are not, we emphasize the need for science-specific performance metrics.

Abstract:

Wide-area imaging surveys are one of the key ways of advancing our understanding of cosmology, galaxy formation physics, and the large-scale structure of the Universe in the coming years. These surveys typically require calculating redshifts for huge numbers (hundreds of millions to billions) of galaxies – almost all of which must be derived from photometry rather than spectroscopy. In this paper, we investigate how using statistical models to understand the populations that make up the colour–magnitude distribution of galaxies can be combined with machine learning photometric redshift codes to improve redshift estimates. In particular, we combine the use of Gaussian mixture models with the high-performing machine-learning photo-z algorithm GPz and show that modelling and accounting for the different colour–magnitude distributions of training and test data separately can give improved redshift estimates, reduce the bias on estimates by up to a half, and speed up the run-time of the algorithm. These methods are illustrated using data from deep optical and near-infrared data in two separate deep fields, where training and test data of different colour–magnitude distributions are constructed from the galaxies with known spectroscopic redshifts, derived from several heterogeneous surveys.

Abstract:

Our understanding of how active galactic nucleus feedback operates in galaxy clusters has improved in recent years owing to large efforts in multiwavelength observations and hydrodynamical simulations. However, it is much less clear how feedback operates in galaxy groups, which have shallower gravitational potentials. In this work, using very deep Very Large Array and new MeerKAT observations from the MIGHTEE survey, we compiled a sample of 247 X-ray selected galaxy groups detected in the COSMOS field. We have studied the relation between the X-ray emission of the intra-group medium and the 1.4 GHz radio emission of the central radio galaxy. For comparison, we have also built a control sample of 142 galaxy clusters using ROSAT and NVSS data. We find that clusters and groups follow the same correlation between X-ray and radio emission. Large radio galaxies hosted in the centres of groups and merging clusters increase the scatter of the distribution. Using statistical tests and Monte Carlo simulations, we show that the correlation is not dominated by biases or selection effects. We also find that galaxy groups are more likely than clusters to host large radio galaxies, perhaps owing to the lower ambient gas density or a more efficient accretion mode. In these groups, radiative cooling of the intra-cluster medium could be less suppressed by active galactic nucleus heating. We conclude that the feedback processes that operate in galaxy clusters are also effective in groups.

Abstract:

Galaxy clusters have long been theorized to quench the star formation of their members. This study uses integral-field unit observations from the K-band MultiObject Spectrograph (KMOS) – Cluster Lensing And Supernova survey with Hubble (CLASH) survey (K-CLASH) to search for evidence of quenching in massive galaxy clusters at redshifts 0.3 < z < 0.6. We first construct mass-matched samples of exclusively star-forming cluster and field galaxies, then investigate the spatial extent of their H α emission and study their interstellar medium conditions using emission line ratios. The average ratio of H α half-light radius to optical half-light radius ($r_{\mathrm{e}, {\rm {H}\,\alpha }}/r_{\mathrm{e}, R_{\mathrm{c} } }$) for all galaxies is 1.14 ± 0.06, showing that star formation is taking place throughout stellar discs at these redshifts. However, on average, cluster galaxies have a smaller $r_{\mathrm{e}, {\rm {H}\alpha }}/r_{\mathrm{e}, R_{\mathrm{c} } }$ ratio than field galaxies: 〈$r_{\mathrm{e}, {\rm {H}\alpha }}/r_{\mathrm{e}, R_{\mathrm{c} } }$〉 = 0.96 ± 0.09 compared to 1.22 ± 0.08 (smaller at a 98 per cent credibility level). These values are uncorrected for the wavelength difference between H α emission and Rc-band stellar light but implementing such a correction only reinforces our results. We also show that whilst the cluster and field samples follow indistinguishable mass–metallicity (MZ) relations, the residuals around the MZ relation of cluster members correlate with cluster-centric distance; galaxies residing closer to the cluster centre tend to have enhanced metallicities (significant at the 2.6σ level). Finally, in contrast to previous studies, we find no significant differences in electron number density between the cluster and field galaxies. We use simple chemical evolution models to conclude that the effects of disc strangulation and ram-pressure stripping can quantitatively explain our observations.