Redshift and stellar mass dependence of intrinsic shapes of disc-dominated galaxies from COSMOS observations below z = 1.0

The high abundance of disc galaxies without a large central bulge challenges predictions of current hydrodynamic simulations of galaxy formation. We aim to shed light on the formation of these objects by studying the redshift and mass dependence of their intrinsic 3D shape distributions in the COSMOS galaxy survey below redshift z = 1.0. This distribution is inferred from the observed distribution of 2D shapes, using a reconstruction method which we test using hydrodynamic simulations. Our tests reveal a moderate bias for the inferred average disc circularity and relative thickness, but a large bias on the dispersion of these quantities. Applying the reconstruction method on COSMOS data, we find variations of the average disc circularity and relative thickness with redshift of around ~1 per cent and ~10 per cent, respectively, which is comparable to the error estimates on these quantities. The average relative disc thickness shows a significant mass dependence which can be accounted for by the scaling of disc radius with galaxy mass. We conclude that our data provides no evidence for a strong dependence of the average circularity and absolute thickness of disc-dominated galaxies on redshift and mass that is significant with respect to the statistical uncertainties in our analysis. These findings are expected in the absence of disruptive merging or feedback events that would affect galaxy shapes. They hence support a scenario where present-day discs form early ( z > 1.0) and subsequently undergo a tranquil evolution in isolation. However, more data and a better understanding of systematics are needed to reaffirm our results

The Physics of the Accelerating Universe Survey: narrow-band image photometry

PAUCam is an innovative optical narrow-band imager mounted at the William Herschel Telescope built for the Physics of the Accelerating Universe Survey (PAUS). Its set of 40 filters results in images that are complex to calibrate, with specific instrumental signatures that cannot be processed with traditional data reduction techniques. In this paper, we present two pipelines developed by the PAUS data management team with the objective of producing science-ready catalogues from the uncalibrated raw images. The NIGHTLY pipeline takes care of entire image processing, with bespoke algorithms for photometric calibration and scatter-light correction. The Multi-Epoch and Multi-Band Analysis pipeline performs forced photometry over a reference catalogue to optimize the photometric redshift (photo-z) performance. We verify against spectroscopic observations that the current approach delivers an inter-band photometric calibration of 0.8 per cent across the 40 narrow-band set. The large volume of data produced every night and the rapid survey strategy feedback constraints require operating both pipelines in the Port d’Informació Cientifica data centre with intense parallelization. While alternative algorithms for further improvements in photo-z performance are under investigation, the image calibration and photometry presented in this work already enable state-of-the-art photo-z down to iAB = 23.0

The PAU Survey: Narrow-band image photometry

PAUCam is an innovative optical narrow-band imager mounted at the William Herschel Telescope built for the Physics of the Accelerating Universe Survey (PAUS). Its set of 40 filters results in images that are complex to calibrate, with specific instrumental signatures that cannot be processed with traditional data reduction techniques. In this paper we present two pipelines developed by the PAUS data management team with the objective of producing science-ready catalogues from the uncalibrated raw images. The Nightly pipeline takes care of all image processing, with bespoke algorithms for photometric calibration and scatter-light correction. The Multi-Epoch and Multi-Band Analysis (MEMBA) pipeline performs forced photometry over a reference catalogue to optimize the photometric redshift performance. We verify against spectroscopic observations that the current approach delivers an inter-band photometric calibration of 0.8% across the 40 narrow-band set. The large volume of data produced every night and the rapid survey strategy feedback constraints require operating both pipelines in the Port d'Informaci\'o Cientifica data centre with intense parallelization. While alternative algorithms for further improvements in photo-z performance are under investigation, the image calibration and photometry presented in this work already enable state-of-the-art photometric redshifts down to iAB=23.0.Comment: 32 pages, 26 figures, MNRAS in pres

The PAU survey: measurements of the 4000 rA spectral break with narrow-band photometry

Galaxie

Euclid preparation: XXIV. Calibration of the halo mass function in (?)CDM cosmologies

Euclid s photometric galaxy cluster survey has the potential to be a very competitive cosmological probe. The main cosmological probe with observations of clusters is their number count, within which the halo mass function (HMF) is a key theoretical quantity. We present a new calibration of the analytic HMF, at the level of accuracy and precision required for the uncertainty in this quantity to be subdominant with respect to other sources of uncertainty in recovering cosmological parameters from Euclid cluster counts. Our model is calibrated against a suite of N-body simulations using a Bayesian approach taking into account systematic errors arising from numerical effects in the simulation. First, we test the convergence of HMF predictions from different N-body codes, by using initial conditions generated with different orders of Lagrangian Perturbation theory, and adopting different simulation box sizes and mass resolution. Then, we quantify the effect of using different halo finder algorithms, and how the resulting differences propagate to the cosmological constraints. In order to trace the violation of universality in the HMF, we also analyse simulations based on initial conditions characterised by scale-free power spectra with different spectral indexes, assuming both Einsteinde Sitter and standard CDM expansion histories. Based on these results, we construct a fitting function for the HMF that we demonstrate to be sub-percent accurate in reproducing results from 9 different variants of the CDM model including massive neutrinos cosmologies. The calibration systematic uncertainty is largely sub-dominant with respect to the expected precision of future massobservation relations; with the only notable exception of the effect due to the halo finder, that could lead to biased cosmological inference

Euclid: Forecasts for k-cut 3×2 Point Statistics

Modelling uncertainties at small scales, i.e. high k in the power spectrum P(k), due to baryonic feedback, nonlinear structure growth and the fact that galaxies are biased tracers poses a significant obstacle to fully leverage the constraining power of the Euclid wide-field survey. k-cut cosmic shear has recently been proposed as a method to optimally remove sensitivity to these scales while preserving usable information. In this paper we generalise the k-cut cosmic shear formalism to 3×2 point statistics and estimate the loss of information for different k-cuts in a 3×2 point analysis of the Euclid data. Extending the Fisher matrix analysis of Euclid Collaboration: Blanchard et al. (2019), we assess the degradation in constraining power for different k-cuts. We find that taking a k-cut at 2.6 h Mpc⁻¹ yields a dark energy Figure of Merit (FOM) of 1018. This is comparable to taking a weak lensing cut at ℓ=5000 and a galaxy clustering and galaxy-galaxy lensing cut at ℓ=3000 in a traditional 3×2 point analysis. We also find that the fraction of the observed galaxies used in the photometric clustering part of the analysis is one of the main drivers of the FOM. Removing 50% (90%) of the clustering galaxies decreases the FOM by 19% (62%). Given that the FOM depends so heavily on the fraction of galaxies used in the clustering analysis, extensive efforts should be made to handle the real-world systematics present when extending the analysis beyond the luminous red galaxy (LRG) sample

Euclid: Covariance of weak lensing pseudo-C_ell estimates. Calculation, comparison to simulations, and dependence on survey geometry

An accurate covariance matrix is essential for obtaining reliable cosmological results when using a Gaussian likelihood. In this paper we study the covariance of pseudo-C_ estimates of tomographic cosmic shear power spectra. Using two existing publicly available codes in combination, we calculate the full covariance matrix, including mode-coupling contributions arising from both partial sky coverage and non-linear structure growth. For three different sky masks, we compare the theoretical covariance matrix to that estimated from publicly available N-body weak lensing simulations, finding good agreement. We find that as a more extreme sky cut is applied, a corresponding increase in both Gaussian off-diagonal covariance and non-Gaussian super-sample covariance is observed in both theory and simulations, in accordance with expectations. Studying the different contributions to the covariance in detail, we find that the Gaussian covariance dominates along the main diagonal and the closest off-diagonals, but further away from the main diagonal the super-sample covariance is dominant. Forming mock constraints in parameters describing matter clustering and dark energy, we find that neglecting non-Gaussian contributions to the covariance can lead to underestimating the true size of confidence regions by up to 70 per cent. The dominant non-Gaussian covariance component is the super-sample covariance, but neglecting the smaller connected non-Gaussian covariance can still lead to the underestimation of uncertainties by 10--20 per cent. A real cosmological analysis will require marginalisation over many nuisance parameters, which will decrease the relative importance of all cosmological contributions to the covariance, so these values should be taken as upper limits on the importance of each component

Euclid: Discovering pair-instability supernovae with the Deep Survey

Pair-instability supernovae are theorized supernovae that have not yet been observationally confirmed. They are predicted to exist in low-metallicity environments. Because overall metallicity becomes lower at higher redshifts, deep near-infrared transient surveys probing high-redshift supernovae are suitable to discover pair-instability supernovae. The Euclid satellite, which is planned to be launched in 2023, has a near-infrared wide-field instrument that is suitable for a high-redshift supernova survey. Although no dedicated supernova survey is currently planned during the Euclid's 6 year primary mission, the Euclid Deep Survey is planned to make regular observations of three Euclid Deep Fields (40 deg2 in total) spanning six years. While the observations of the Euclid Deep Fields are not frequent, we show that the predicted long duration of pair-instability supernovae would allow us to search for high-redshift pair-instability supernovae with the Euclid Deep Survey. Based on the current observational plan of the Euclid mission, we conduct survey simulations in order to estimate the expected numbers of pair-instability supernova discoveries. We find that up to several hundred pair-instability supernovae at z < ~ 3.5 can be discovered by the Euclid Deep Survey. We also show that pair-instability supernova candidates can be efficiently identified by their duration and color that can be determined with the current Euclid Deep Survey plan. We conclude that the Euclid mission can lead to the first confident discovery of pair-instability supernovae if their event rates are as high as those predicted by recent theoretical studies. We also update the expected numbers of superluminous supernova discoveries in the Euclid Deep Survey based on the latest observational plan.Comment: 12 pages, 13 figures, 2 tables, submitted to Astronomy & Astrophysic

The PAU Survey & Euclid: Improving broad-band photometric redshifts with multi-task learning

Current and future imaging surveys require photometric redshifts (photo-z) to be estimated for millions of galaxies. Improving the photo-z quality is a major challenge to advance our understanding of cosmology. In this paper, we explore how the synergies between narrow-band photometric data and large imaging surveys can be exploited to improve broad-band photometric redshifts. We use a multi-task learning (MTL) network to improve broad-band photo-z estimates by simultaneously predicting the broad-band photo-z and the narrow-band photometry from the broad-band photometry. The narrow-band photometry is only required in the training field, which enables better photo-z predictions also for the galaxies without narrow-band photometry in the wide field. This technique is tested with data from the Physics of the Accelerating Universe Survey (PAUS) in the COSMOS field. We find that the method predicts photo-z that are 14% more precise down to magnitude i_AB<23, while reducing the outlier rate by 40% with respect to the baseline network mapping broad-band colours to only photo-zs. Furthermore, MTL significantly reduces the photo-z bias for high-redshift galaxies, improving the redshift distributions for tomographic bins with z>1. Applying this technique to deeper samples is crucial for future surveys like \Euclid or LSST. For simulated data, training on a sample with i_AB <23, the method reduces the photo-z scatter by 15% for all galaxies with 24<i_AB<25. We also study the effects of extending the training sample with photometric galaxies using PAUS high-precision photo-zs, which further reduces the photo-z scatter.Comment: 20 pages, 16 figure