We present a new, updated version of the EuclidEmulator (called EuclidEmulator2), a fast and accurate predictor for the nonlinear correction of the matter power spectrum. 2 per cent-level accurate emulation is now supported in the eight-dimensional parameter space of w0waCDM+∑mν models between redshift z = 0 and z = 3 for spatial scales within the range 0.01 h Mpc−1 ≤ k ≤ 10 h Mpc−1. In order to achieve this level of accuracy, we have had to improve the quality of the underlying N-body simulations used as training data: (i) we use self-consistent linear evolution of non-dark matter species such as massive neutrinos, photons, dark energy and the metric field, (ii) we perform the simulations in the so-called N-body gauge, which allows one to interpret the results in the framework of general relativity, (iii) we run over 250 high-resolution simulations with 30003 particles in boxes of 1(h−1 Gpc)3 volumes based on paired-and-fixed initial conditions and (iv) we provide a resolution correction that can be applied to emulated results as a post-processing step in order to drastically reduce systematic biases on small scales due to residual resolution effects in the simulations. We find that the inclusion of the dynamical dark energy parameter wa significantly increases the complexity and expense of creating the emulator. The high fidelity of EuclidEmulator2 is tested in various comparisons against N-body simulations as well as alternative fast predictors like HALOFIT, HMCode and CosmicEmu. A blind test is successfully performed against the Euclid Flagship v2.0 simulation. Nonlinear correction factors emulated with EuclidEmulator2 are accurate at the level of $1{{\ \rm per\ cent}}$ or better for 0.01 h Mpc−1 ≤ k ≤ 10 h Mpc−1 and z ≤ 3 compared to high-resolution dark matter only simulations. EuclidEmulator2 is publicly available at https://github.com/miknab/EuclidEmulator2.

We present – and make publicly available – accurate and precise photometric redshifts in the ACS footprint from the COSMOS field for objects with iAB ≤ 23. The redshifts are computed using a combination of narrow-band photometry from PAUS, a survey with 40 narrow bands spaced at $100\,\mathring{\rm A}$ intervals covering the range from 4500 to $8500\,\mathring{\rm A}$, and 26 broad, intermediate, and narrow bands covering the UV, visible and near-infrared spectrum from the COSMOS2015 catalogue. We introduce a new method that models the spectral energy distributions as a linear combination of continuum and emission-line templates and computes its Bayes evidence, integrating over the linear combinations. The correlation between the UV luminosity and the O ii line is measured using the 66 available bands with the zCOSMOS spectroscopic sample, and used as a prior which constrains the relative flux between continuum and emission-line templates. The flux ratios between the O ii line and Hα, Hβ and $\mathrm{O\,{\small III}}$ are similarly measured and used to generate the emission-line templates. Comparing to public spectroscopic surveys via the quantity Δz ≡ (zphoto − zspec)/(1 + zspec), we find the photometric redshifts to be more precise than previous estimates, with σ68(Δz) ≈ (0.003, 0.009) for galaxies at magnitude iAB ∼ 18 and iAB ∼ 23, respectively, which is three times and 1.66 times tighter than COSMOS2015. Additionally, we find the redshifts to be very accurate on average, yielding a median of the Δz distribution compatible with |median(Δz)| ≤ 0.001 at all redshifts and magnitudes considered. Both the added PAUS data and new methodology contribute significantly to the improved results. The catalogue produced with the technique presented here is expected to provide a robust redshift calibration for current and future lensing surveys, and allows one to probe galaxy formation physics in an unexplored luminosity-redshift regime, thanks to its combination of depth, completeness, and excellent redshift precision and accuracy.

Upcoming surveys will map the growth of large-scale structure with unprecented precision, improving our understanding of the dark sector of the Universe. Unfortunately, much of the cosmological information is encoded on small scales, where the clustering of dark matter and the effects of astrophysical feedback processes are not fully understood. This can bias the estimates of cosmological parameters, which we study here for a joint analysis of mock Euclid cosmic shear and Planck cosmic microwave background data. We use different implementations for the modelling of the signal on small scales and find that they result in significantly different predictions. Moreover, the different non-linear corrections lead to biased parameter estimates, especially when the analysis is extended into the highly non-linear regime, with the Hubble constant, H0, and the clustering amplitude, σ8, affected the most. Improvements in the modelling of non-linear scales will therefore be needed if we are to resolve the current tension with more and better data. For a given prescription for the non-linear power spectrum, using different corrections for baryon physics does not significantly impact the precision of Euclid, but neglecting these correction does lead to large biases in the cosmological parameters. In order to extract precise and unbiased constraints on cosmological parameters from Euclid cosmic shear data, it is therefore essential to improve the accuracy of the recipes that account for non-linear structure formation, as well as the modelling of the impact of astrophysical processes that redistribute the baryons.

The Euclid mission -with its spectroscopic galaxy survey covering a sky area over 15 000 deg 2 in the redshift range 0.9 < z < 1.8 -will provide a sample of tens of thousands of cosmic voids. This paper thoroughly explores for the first time the constraining power of the void size function on the properties of dark energy (DE) from a survey mock catalogue, the official Euclid Flagship simulation. We identified voids in the Flagship light-cone, which closely matches the features of the upcoming Euclid spectroscopic data set. We modelled the void size function considering a state-of-the art methodology: we relied on the volume-conserving (Vdn) model, a modification of the popular Sheth & van de Weygaert model for void number counts, extended by means of a linear function of the large-scale galaxy bias. We found an excellent agreement between model predictions and measured mock void number counts. We computed updated forecasts for the Euclid mission on DE from the void size function and provided reliable void number estimates to serve as a basis for further forecasts of cosmological applications using voids. We analysed two different cosmological models for DE: the first described by a constant DE equation of state parameter, w, and the second by a dynamic equation of state with coefficients w 0 and w a . We forecast 1σ errors on w lower than 10% and we estimated an expected figure of merit (FoM) for the dynamical DE scenario FoM w 0 ,wa = 17 when considering only the neutrino mass as additional free parameter of the model. The analysis is based on conservative assumptions to ensure full robustness, and is a pathfinder for future enhancements of the technique. Our results showcase the impressive constraining power of the void size function from the Euclid spectroscopic sample, both as a stand-alone probe, and to be combined with other Euclid cosmological probes.

We present the first measurements of the projected clustering and intrinsic alignments (IA) of galaxies observed by the Physics of the Accelerating Universe Survey (PAUS). With photometry in 40 narrow optical passbands (4500 Å–8500 Å), the quality of photometric redshift estimation is σz ∼ 0.01(1 + z) for galaxies in the 19 deg2 Canada-France-Hawaii Telescope Legacy Survey W3 field, allowing us to measure the projected 3D clustering and IA for flux-limited, faint galaxies (i < 22.5) out to z ∼ 0.8. To measure two-point statistics, we developed, and tested with mock photometric redshift samples, ‘cloned’ random galaxy catalogues which can reproduce data selection functions in 3D and account for photometric redshift errors. In our fiducial colour-split analysis, we made robust null detections of IA for blue galaxies and tentative detections of radial alignments for red galaxies (∼1 − 3σ), over scales of 0.1 − 18 h−1 Mpc. The galaxy clustering correlation functions in the PAUS samples are comparable to their counterparts in a spectroscopic population from the Galaxy and Mass Assembly survey, modulo the impact of photometric redshift uncertainty which tends to flatten the blue galaxy correlation function, whilst steepening that of red galaxies. We investigate the sensitivity of our correlation function measurements to choices in the random catalogue creation and the galaxy pair-binning along the line of sight, in preparation for an optimised analysis over the full PAUS area.