Showing papers by "Edwin A. Valentijn published in 2022"

Euclid preparation. XVIII. The NISP photometric system

Abstract: Euclid Collaboration: M. Schirmer1?, K. Jahnke1, G. Seidel1, H. Aussel2, C. Bodendorf3, F. Grupp3,4, F. Hormuth1, S. Wachter5, P.N. Appleton6, R. Barbier7, J. Brinchmann8,9, J.M. Carrasco10, F.J. Castander11,12, J. Coupon13, F. De Paolis14,15, A. Franco14,15, K. Ganga16, P. Hudelot17, E. Jullo18, A. Lançon19, A.A. Nucita14,15, S. Paltani13, G. Smadja7, F. Strafella14,15,20, L.M.G. Venancio21, M. Weiler11,10, A. Amara22, T. Auphan23, N. Auricchio24, A. Balestra25, R. Bender3,4, D. Bonino26, E. Branchini27,28, M. Brescia29, V. Capobianco26, C. Carbone30, J. Carretero31,32, R. Casas11,12, M. Castellano33, S. Cavuoti34,29,35, A. Cimatti36,37, R. Cledassou38,39, G. Congedo40, C.J. Conselice41, L. Conversi42,43, Y. Copin7, L. Corcione26, A. Costille18, F. Courbin44, A. Da Silva45,46, H. Degaudenzi13, M. Douspis47, F. Dubath13, X. Dupac43, S. Dusini48, A. Ealet7, S. Farrens2, S. Ferriol7, P. Fosalba11,12, M. Frailis49, E. Franceschi24, P. Franzetti30, M. Fumana30, B. Garilli30, W. Gillard23, B. Gillis40, C. Giocoli50,51, A. Grazian25, L. Guzzo52,53,54, S.V.H. Haugan55, H. Hoekstra56, W. Holmes57, A. Hornstrup58, M. Kümmel4, S. Kermiche23, A. Kiessling57, M. Kilbinger2, T. Kitching59, R. Kohley43, M. Kunz60, H. Kurki-Suonio61, R. Laureijs21, S. Ligori26, P.B. Lilje55, I. Lloro62, T. Maciaszek38, E. Maiorano24, O. Mansutti49, O. Marggraf63, K. Markovic57, F. Marulli64,24,65, R. Massey66, S. Maurogordato67, Y. Mellier68,17,69, M. Meneghetti24,65, E. Merlin33, G. Meylan44, M. Moresco64,24, L. Moscardini64,24,65, E. Munari49, R. Nakajima63, R.C. Nichol22, S.M. Niemi21, C. Padilla31, F. Pasian49, K. Pedersen70, W.J. Percival71,72,73, V. Pettorino2, S. Pires2, M. Poncet38, L. Popa74, L. Pozzetti24, E. Prieto18, F. Raison3, J. Rhodes57, H.-W. Rix1, M. Roncarelli64,24, E. Rossetti64, R. Saglia75,4, B. Sartoris76,49, R. Scaramella33,77, P. Schneider63, A. Secroun23, S. Serrano12,11, C. Sirignano78,48, G. Sirri65, L. Stanco48, P. Tallada-Crespí79,32, A.N. Taylor40, H.I. Teplitz6, I. Tereno45,80, R. Toledo-Moreo81, F. Torradeflot79,32, M. Trifoglio82, E.A. Valentijn83, L. Valenziano24,65, Y. Wang6, J. Weller3,4, G. Zamorani24, J. Zoubian23, S. Andreon53, S. Bardelli24, A. Boucaud16, S. Camera84,26,85, R. Farinelli82, J. Graciá-Carpio3, D. Maino52,30,54, E. Medinaceli24, S. Mei16, N. Morisset13, G. Polenta86, A. Renzi78,48, E. Romelli49, M. Tenti65, T. Vassallo4, A. Zacchei49, E. Zucca24, C. Baccigalupi87,88,76,49, A. Balaguera-Antolínez89,90, A. Biviano76,49, A. Blanchard91, S. Borgani92,76,49,87, E. Bozzo13, C. Burigana93,94,95, R. Cabanac91, A. Cappi67,24, C.S. Carvalho80, S. Casas2, G. Castignani64,24, C. Colodro-Conde90, A.R. Cooray96, H.M. Courtois97, M. Crocce11,12, J.-G. Cuby18, S. Davini98, S. de la Torre18, D. Di Ferdinando93, J.A. Escartin3, M. Farina99, P.G. Ferreira100, F. Finelli24,93, S. Fotopoulou101, S. Galeotta49, J. Garcia-Bellido102, E. Gaztanaga11,103, K. George4, G. Gozaliasl104, I.M. Hook105, S. Ilić106,16, V. Kansal2, A. Kashlinsky107, E. Keihanen104, C.C. Kirkpatrick61, V. Lindholm104,108, G. Mainetti109, R. Maoli110,33, M. Martinelli102, N. Martinet18, M. Maturi111,112,113, N. Mauri36,65, H.J. McCracken17,69, R.B. Metcalf64,24, P. Monaco92,76,49,87, G. Morgante24, J. Nightingale66, L. Patrizii65, A. Peel44, V. Popa74, C. Porciani63, D. Potter114, P. Reimberg17, G. Riccio29, A.G. Sánchez3,4, D. Sapone115, V. Scottez17, E. Sefusatti76,49,87, R. Teyssier116, I. Tutusaus12,11, C. Valieri65, J. Valiviita117,108, M. Viel76,49,87,88, H. Hildebrandt112

Euclid: Cosmological forecasts from the void size function

Abstract: The Euclid mission – with its spectroscopic galaxy survey covering a sky area over 15000 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 o ffi cial 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 di ff erent 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 coe ffi cients w 0 and w a . We forecast 1 σ errors on w lower than 10% and we estimated an expected figure of merit (FoM) for the dynamical DE scenario FoM w 0 ,w a = 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.

Euclid preparation. XXI. Intermediate-redshift contaminants in the search for z > 6 galaxies within the Euclid Deep Survey

Abstract: (Abridged) The Euclid mission is expected to discover thousands of z>6 galaxies in three Deep Fields, which together will cover a ~40 deg2 area. However, the limited number of Euclid bands and availability of ancillary data could make the identification of z>6 galaxies challenging. In this work, we assess the degree of contamination by intermediate-redshift galaxies (z=1-5.8) expected for z>6 galaxies within the Euclid Deep Survey. This study is based on ~176,000 real galaxies at z=1-8 in a ~0.7 deg2 area selected from the UltraVISTA ultra-deep survey, and ~96,000 mock galaxies with 25.3$\leq$H<27.0, which altogether cover the range of magnitudes to be probed in the Euclid Deep Survey. We simulate Euclid and ancillary photometry from the fiducial, 28-band photometry, and fit spectral energy distributions (SEDs) to various combinations of these simulated data. Our study demonstrates that identifying z>6 with Euclid data alone will be very effective, with a z>6 recovery of 91(88)% for bright (faint) galaxies. For the UltraVISTA-like bright sample, the percentage of z=1-5.8 contaminants amongst apparent z>6 galaxies as observed with Euclid alone is 18%, which is reduced to 4(13)% by including ultra-deep Rubin (Spitzer) photometry. Conversely, for the faint mock sample, the contamination fraction with Euclid alone is considerably higher at 39%, and minimized to 7% when including ultra-deep Rubin data. For UltraVISTA-like bright galaxies, we find that Euclid (I-Y)>2.8 and (Y-J)<1.4 colour criteria can separate contaminants from true z>6 galaxies, although these are applicable to only 54% of the contaminants, as many have unconstrained (I-Y) colours. In the most optimistic scenario, these cuts reduce the contamination fraction to 1% whilst preserving 81% of the fiducial z>6 sample. For the faint mock sample, colour cuts are infeasible.

Euclid: Testing the Copernican principle with next-generation surveys

Abstract: The Copernican principle, the notion that we are not at a special location in the Universe, is one of the cornerstones of modern cosmology and its violation would invalidate the Friedmann-Lema\^{\i}tre-Robertson-Walker (FLRW) metric, causing a major change in our understanding of the Universe. Thus, it is of fundamental importance to perform observational tests of this principle. We determine the precision with which future surveys will be able to test the Copernican principle and their ability to detect any possible violations. We forecast constraints on the inhomogeneous Lema\^{\i}tre-Tolman-Bondi model with a cosmological constant $\Lambda$ ($\Lambda$LTB), basically a cosmological constant $\Lambda$ and cold dark matter ($\Lambda$CDM) model, but endowed with a spherical inhomogeneity. We consider combinations of currently available data and simulated Euclid data, together with external data products, based on both $\Lambda$CDM and $\Lambda$LTB fiducial models. These constraints are compared to the expectations from the Copernican principle. When considering the $\Lambda$CDM fiducial model, we find that Euclid data, in combination with other current and forthcoming surveys, will improve the constraints on the Copernican principle by about $30\%$, with $\pm10\%$ variations depending on the observables and scales considered. On the other hand, when considering a $\Lambda$LTB fiducial model, we find that future Euclid data, combined with other current and forthcoming data sets, will be able to detect Gpc-scale inhomogeneities of contrast $-0.1$. Next-generation surveys, such as Euclid, will thoroughly test homogeneity at large scales, tightening the constraints on possible violations of the Copernican principle.

Euclid: Forecasts from the void-lensing cross-correlation

Abstract: The Euclid space telescope will survey a large dataset of cosmic voids traced by dense samples of galaxies. In this work we estimate its expected performance when exploiting angular photometric void clustering, galaxy weak lensing and their cross-correlation. To this aim, we implement a Fisher matrix approach tailored for voids from the Euclid photometric dataset and present the first forecasts on cosmological parameters that include the void-lensing correlation. We examine two different probe settings, pessimistic and optimistic, both for void clustering and galaxy lensing. We carry out forecast analyses in four model cosmologies, accounting for a varying total neutrino mass, $M_ u$, and a dynamical dark energy (DE) equation of state, $w(z)$, described by the CPL parametrisation. We find that void clustering constraints on $h$ and $\Omega_b$ are competitive with galaxy lensing alone, while errors on $n_s$ decrease thanks to the orthogonality of the two probes in the 2D-projected parameter space. We also note that, as a whole, the inclusion of the void-lensing cross-correlation signal improves parameter constraints by $10-15\%$, and enhances the joint void clustering and galaxy lensing Figure of Merit (FoM) by $10\%$ and $25\%$, in the pessimistic and optimistic scenarios, respectively. Finally, when further combining with the spectroscopic galaxy clustering, assumed as an independent probe, we find that, in the most competitive case, the FoM increases by a factor of 4 with respect to the combination of weak lensing and spectroscopic galaxy clustering taken as independent probes. The forecasts presented in this work show that photometric void-clustering and its cross-correlation with galaxy lensing deserve to be exploited in the data analysis of the Euclid galaxy survey and promise to improve its constraining power, especially on $h$, $\Omega_b$, the neutrino mass, and the DE evolution.

Euclid preparation: XXIII. Derivation of galaxy physical properties with deep machine learning using mock fluxes and H-band images

Abstract: Next generation telescopes, like Euclid, Rubin/LSST, and Roman, will open new windows on the Universe, allowing us to infer physical properties for tens of millions of galaxies. Machine learning methods are increasingly becoming the most efficient tools to handle this enormous amount of data, because they are often faster and more accurate than traditional methods. We investigate how well redshifts, stellar masses, and star-formation rates (SFR) can be measured with deep learning algorithms for observed galaxies within data mimicking the Euclid and Rubin/LSST surveys. We find that Deep Learning Neural Networks and Convolutional Neutral Networks (CNN), which are dependent on the parameter space of the training sample, perform well in measuring the properties of these galaxies and have a better accuracy than methods based on spectral energy distribution fitting. CNNs allow the processing of multi-band magnitudes together with $H_{\scriptscriptstyle \rm E}$-band images. We find that the estimates of stellar masses improve with the use of an image, but those of redshift and SFR do not. Our best results are deriving i) the redshift within a normalised error of less than 0.15 for 99.9${{\%}}$ of the galaxies with S/N>3 in the $H_{\scriptscriptstyle \rm E}$-band; ii) the stellar mass within a factor of two ($\sim 0.3 \rm dex$) for 99.5${{\%}}$ of the considered galaxies; iii) the SFR within a factor of two ($\sim 0.3 \rm dex$) for $\sim 70{{\%}}$ of the sample. We discuss the implications of our work for application to surveys as well as how measurements of these galaxy parameters can be improved with deep learning.

Euclid preparation XX. The Complete Calibration of the Color–Redshift Relation survey: LBT observations and data release (cid:63)

Abstract: The Complete Calibration of the Color–Redshift Relation survey (C3R2) is a spectroscopic program designed to empirically calibrate the galaxy color–redshift relation to the Euclid depth ( I E = 24 . 5), a key ingredient for the success of Stage IV dark energy projects based on weak lensing cosmology. A spectroscopic calibration sample that is as representative as possible of the galaxies in the Euclid weak lensing sample is being collected, selecting galaxies from a self-organizing map (SOM) representation of the galaxy color space. Here, we present the results of a near-infrared H - and K -band spectroscopic campaign carried out using the LUCI instruments at the LBT. For a total of 251 galaxies, we present new highly reliable redshifts in the 1 . 3 ≤ z ≤ 1 . 7 and 2 ≤ z ≤ 2 . 7 ranges. The newly-determined redshifts populate 49 SOM cells that previously contained no spectroscopic measurements and almost twice the occupation numbers of an additional 153 SOM cells. A final optical ground-based observational e ff ort is needed to calibrate the missing cells, in particular in the redshift range 1 . 7 ≤ z ≤ 2 . 7, which lack spectroscopic calibration. In the end, Euclid itself will deliver telluric-free near-IR spectra that can complete the calibration.

Euclid: Calibrating photometric redshifts with spectroscopic cross-correlations

Abstract: Cosmological constraints from key probes of the Euclid imaging survey rely critically on the accurate determination of the true redshift distributions, $n(z)$, of tomographic redshift bins. We determine whether the mean redshift, $$, of ten Euclid tomographic redshift bins can be calibrated to the Euclid target uncertainties of $\sigma()<0.002\,(1+z)$ via cross-correlation, with spectroscopic samples akin to those from the Baryon Oscillation Spectroscopic Survey (BOSS), Dark Energy Spectroscopic Instrument (DESI), and Euclid's NISP spectroscopic survey. We construct mock Euclid and spectroscopic galaxy samples from the Flagship simulation and measure small-scale clustering redshifts up to redshift $z<1.8$ with an algorithm that performs well on current galaxy survey data. The clustering measurements are then fitted to two $n(z)$ models: one is the true $n(z)$ with a free mean; the other a Gaussian Process modified to be restricted to non-negative values. We show that $$ is measured in each tomographic redshift bin to an accuracy of order 0.01 or better. By measuring the clustering redshifts on subsets of the full Flagship area, we construct scaling relations that allow us to extrapolate the method performance to larger sky areas than are currently available in the mock. For the full expected Euclid, BOSS, and DESI overlap region of approximately 6000 deg$^{2}$, the uncertainties attainable by clustering redshifts exceeds the Euclid requirement by at least a factor of three for both $n(z)$ models considered, although systematic biases limit the accuracy. Clustering redshifts are an extremely effective method for redshift calibration for Euclid if the sources of systematic biases can be determined and removed, or calibrated-out with sufficiently realistic simulations. We outline possible future work, in particular an extension to higher redshifts with quasar reference samples.

The PAU Survey and Euclid: Improving broadband photometric redshifts with multi-task learning

Abstract: Current and future imaging surveys require photometric redshifts (photo-zs) to be estimated for millions of galaxies. Improving the photo-z quality is a major challenge but is needed 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 broadband photometric redshifts. We used a multi-task learning (MTL) network to improve broadband photo-z estimates by simultaneously predicting the broadband photo-z and the narrow-band photometry from the broadband photometry. The narrow-band photometry is only required in the training field, which also enables better photo-z predictions for the galaxies without narrow-band photometry in the wide field. This technique was tested with data from the Physics of the Accelerating Universe Survey (PAUS) in the COSMOS field. We find that the method predicts photo-zs that are 13% more precise down to magnitude i_{AB}<23; the outlier rate is also 40% lower when compared to the baseline network. Furthermore, MTL 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 such as \Euclid or LSST. For simulated data, training on a sample with i_{AB}<23, the method reduces the photo-z scatter by 16% for all galaxies with i_{AB}<25. We also studied the effects of extending the training sample with photometric galaxies using PAUS high-precision photo-zs, which reduces the photo-z scatter by 20% in the COSMOS field.

Euclid preparation. XXIV. Calibration of the halo mass function in $\Lambda(\nu)$CDM cosmologies

Abstract: 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 Einstein--de Sitter and standard $\Lambda$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 $\Lambda$CDM model including massive neutrinos cosmologies. The calibration systematic uncertainty is largely sub-dominant with respect to the expected precision of future mass-observation relations; with the only notable exception of the effect due to the halo finder, that could lead to biased cosmological inference.

Euclid preparation. XX. The Complete Calibration of the Colour--Redshift Relation survey: LBT observations and data release

Abstract: The Complete Calibration of the Color–Redshift Relation survey (C3R2) is a spectroscopic program designed to empirically calibrate the galaxy color–redshift relation to the Euclid depth ( I E = 24 . 5), a key ingredient for the success of Stage IV dark energy projects based on weak lensing cosmology. A spectroscopic calibration sample that is as representative as possible of the galaxies in the Euclid weak lensing sample is being collected, selecting galaxies from a self-organizing map (SOM) representation of the galaxy color space. Here, we present the results of a near-infrared H - and K -band spectroscopic campaign carried out using the LUCI instruments at the LBT. For a total of 251 galaxies, we present new highly reliable redshifts in the 1 . 3 ≤ z ≤ 1 . 7 and 2 ≤ z ≤ 2 . 7 ranges. The newly-determined redshifts populate 49 SOM cells that previously contained no spectroscopic measurements and almost twice the occupation numbers of an additional 153 SOM cells. A final optical ground-based observational e ff ort is needed to calibrate the missing cells, in particular in the redshift range 1 . 7 ≤ z ≤ 2 . 7, which t lack spectroscopic calibration. In the end, Euclid itself will deliver telluric-free near-IR spectra that can complete the calibration.

Euclid: Fast two-point correlation function covariance through linear construction

Abstract: We present a method for fast evaluation of the covariance matrix for a two-point galaxy correlation function (2PCF) measured with the Landy– Szalay estimator. The standard way of evaluating the covariance matrix consists in running the estimator on a large number of mock catalogs, and evaluating their sample covariance. With large random catalog sizes (random-to-data objects’ ratio M (cid:29) 1) the computational cost of the standard method is dominated by that of counting the data-random and random-random pairs, while the uncertainty of the estimate is dominated by that of data-data pairs. We present a method called Linear Construction (LC), where the covariance is estimated for small random catalogs with a size of M = 1 and M = 2, and the covariance for arbitrary M is constructed as a linear combination of the two. We show that the LC covariance estimate is unbiased. We validated the method with PINOCCHIO simulations in the range r = 20 − 200 h − 1 Mpc. With M = 50 and with 2 h − 1 Mpc bins, the theoretical speedup of the method is a factor of 14. We discuss the impact on the precision matrix and parameter estimation, and present a formula for the covariance of covariance.

The SAMI -- Fornax Dwarfs Survey II: The Stellar Mass Fundamental Plane and the Dark Matter fraction of Dwarf Galaxies

Abstract: We explore the kinematic scaling relations of 38 dwarf galaxies in the Fornax Cluster using observations from the SAMI integral field spectrograph. We focus on the Fundamental Plane (FP), defined by the physical properties of the objects (scale length, surface brightness and velocity dispersion) and the Stellar Mass (Fundamental) Plane, where surface brightness is replaced by stellar mass, and investigate their dynamical-to-stellar-mass ratio. We confirm earlier results that the Fornax dEs are significantly offset above the FP defined by massive, hot stellar systems. For the Stellar Mass (Fundamental) Plane, which shows much lower scatter, we find that young and old dwarf galaxies lie at about the same distance from the plane, all with comparable scatter. We introduce the perpendicular deviation of dwarf galaxies from the Stellar Mass Plane defined by giant early-types as a robust estimate of their DM fraction, and find that the faintest dwarfs are systematically offset above the plane, implying that they have a higher dark matter fraction. This result is confirmed when estimating the dynamical mass of our dEs using a virial mass estimator, tracing the onset of dark matter domination in low mass stellar systems. We find that the position of our galaxies on the Stellar Mass FP agrees with the galaxies in the Local Group. This seems to imply that the processes determining the position of dwarf galaxies on the FP depend on the environment in the same way, whether the galaxy is situated in the Local Group or in the Fornax Cluster.