The PAU Survey (PAUS) is an innovative photometric survey with 40 narrow bands at the William Herschel Telescope (WHT). The narrow bands are spaced at 100Å intervals covering the range 4500Å to 8500Å and, in combination with standard broad bands, enable excellent redshift precision. This paper describes the technique, galaxy templates and additional photometric calibration used to determine early photometric redshifts from PAUS. Using bcnz2, a new photometric redshift code developed for this purpose, we characterise the photometric redshift performance using PAUS data on the COSMOS field. Comparison to secure spectra from zCOSMOS DR3 shows that PAUS achieves σ 68 /(1+z) = 0.0037 to i AB < 22.5 when selecting the best 50% of the sources based on a photometric redshift quality cut. Furthermore, a higher photo-z precision (σ 68 /(1 + z) ∼ 0.001) is obtained for a bright and high quality selection, which is driven by the identification of emission lines. We conclude that PAUS meets its design goals, opening up a hitherto uncharted regime of deep, wide, and dense galaxy survey with precise redshifts that will provide unique insights into the formation, evolution and clustering of galaxies, as well as their intrinsic alignments.

Narrow-band imaging surveys allow the study of the spectral characteristics of galaxies without the need of performing their spectroscopic follow-up. In this work, we forward-model the Physics of the Accelerating Universe Survey (PAUS) narrow-band data. The aim is to improve the constraints on the spectral coefficients used to create the galaxy spectral energy distributions (SED) of the galaxy population model in In that work, the model parameters were inferred from the Canada-France-Hawaii Telescope Legacy Survey (CFHTLS) data using Approximate Bayesian Computation (ABC). This led to stringent constraints on the B-band galaxy luminosity function parameters, but left the spectral coefficients only broadly constrained. To address that, we perform an ABC inference using CFHTLS and PAUS data. This is the first time our approach combining forwardmodelling and ABC is applied simultaneously to multiple datasets. We test the results of the ABC inference by comparing the narrow-band magnitudes of the observed and simulated galaxies using Principal Component Analysis, finding a very good agreement. Furthermore, we prove the scientific potential of the constrained galaxy population model to provide realistic stellar population properties by measuring them with the CIGALE SED fitting code. We use CFHTLS broad-band and PAUS narrow-band photometry for a flux-limited (i < 22.5) sample of galaxies spanning the redshift range 0 < z < 1.0. We find that properties like stellar masses, star-formation rates, mass-weighted stellar ages and metallicities are in agreement within errors between observations and simulations. Overall, this work shows the ability of our galaxy population model to correctly forward-model a complex dataset such as PAUS and the ability to reproduce the diversity of galaxy properties at the redshift range spanned by CFHTLS and PAUS.

Context. The processes responsible for galaxy evolution in different environments as a function of galaxy mass remain heavily debated. Rich galaxy clusters are ideal laboratories in which to distinguish the role of environmental versus mass quenching because they consist of a full range of galaxies and environments. Aims. Using the CLASH-VLT survey, we assembled an unprecedentedly large sample of 1234 spectroscopically confirmed members in Abell S1063. We found a dynamically complex structure at ⟨zcl⟩ = 0.3457 with a velocity dispersion σv = 1380−32+26 km s−1. We investigated cluster environmental and dynamical effects by analysing the projected phase-space diagram and the orbits as a function of galaxy spectral properties. Methods. We classified cluster galaxies according to the presence and strength of the [OII] emission line, the strength of the Hδ absorption line, and colours. We investigated the relation between the spectral classes of galaxies and their position in the projected phase-space diagram. We separately analysed red and blue galaxy orbits. By correlating the observed positions and velocities with the projected phase-space constructed from simulations, we constrained the accretion redshift of galaxies with different spectral types. Results. Passive galaxies are mainly located in the virialised region, while emission-line galaxies lie beyond r200 and are accreted into the cluster at a later time. Emission-line and post-starburst galaxies show an asymmetric distribution in projected phase-space within r200; emission-line galaxies are prominent at Δv/σ ≲ −1.5 and post-starburst galaxies at Δv/σ ≳ 1.5, suggesting that backsplash galaxies lie at high positive velocities. We find that low-mass passive galaxies are accreted into the cluster before high-mass galaxies. This suggests that we observe as passives only the low-mass galaxies that are accreted early into the cluster as blue galaxies. They had the time to quench their star formation. We also find that red galaxies move on more radial orbits than blue galaxies. This can be explained if infalling galaxies can remain blue by moving on tangential orbits.

We analyse the Kormendy relations (KRs) of the two Frontier Fields clusters, Abell S1063, at z = 0.348, and MACS J1149.5+2223, at z = 0.542, exploiting very deep Hubble Space Telescope photometry and VLT/MUSE integral field spectroscopy. With this novel dataset, we are able to investigate how the KR parameters depend on the cluster galaxy sample selection and how this affects studies of galaxy evolution based on the KR. We define and compare four different galaxy samples according to: (a) Sérsic indices: early-type ('ETG'), (b) visual inspection: 'ellipticals', (c) colours: 'red', (d) spectral properties: 'passive'. The classification is performed for a complete sample of galaxies with m F814W ≤ 22.5 ABmag (M * 10 10.0 M ). To derive robust galaxy structural parameters, we use two methods: (1) an iterative estimate of structural parameters using images of increasing size, in order to deal with closely separated galaxies and (2) different background estimations, to deal with the Intracluster light contamination. The comparison between the KRs obtained from the different samples suggests that the sample selection could affect the estimate of the best-fitting KR parameters. The KR built with ETGs is fully consistent with the one obtained for ellipticals and passive. On the other hand, the KR slope built on the red sample is only marginally consistent with those obtained with the other samples. We also release the photometric catalogue with structural parameters for the galaxies included in the present analysis.