arXiv subjects

E. Branchini

Publications and source records attributed to E. Branchini.

At least 289 records · Page 16Linked to original sources

arXiv2021

Euclid preparation: I. The Euclid Wide Survey

Euclid is an ESA mission designed to constrain the properties of dark energy and gravity via weak gravitational lensing and galaxy clustering. It will carry out a wide area imaging and spectroscopy survey (EWS) in visible and near-infrared, covering roughly 15,000 square degrees of extragalactic sky on six years. The wide-field telescope and instruments are optimized for pristine PSF and reduced straylight, producing very crisp images. This paper presents the building of the Euclid reference survey: the sequence of pointings of EWS, Deep fields, Auxiliary fields for calibrations, and spacecraft movements followed by Euclid as it operates in a step-and-stare mode from its orbit around the Lagrange point L2. Each EWS pointing has four dithered frames; we simulate the dither pattern at pixel level to analyse the effective coverage. We use up-to-date models for the sky background to define the Euclid region-of-interest (RoI). The building of the reference survey is highly constrained from calibration cadences, spacecraft constraints and background levels; synergies with ground-based coverage are also considered. Via purposely-built software optimized to prioritize best sky areas, produce a compact coverage, and ensure thermal stability, we generate a schedule for the Auxiliary and Deep fields observations and schedule the RoI with EWS transit observations. The resulting reference survey RSD_2021A fulfills all constraints and is a good proxy for the final solution. Its wide survey covers 14,500 square degrees. The limiting AB magnitudes ($5σ$ point-like source) achieved in its footprint are estimated to be 26.2 (visible) and 24.5 (near-infrared); for spectroscopy, the H$_α$ line flux limit is $2\times 10^{-16}$ erg cm$^{-2}$ s$^{-1}$ at 1600 nm; and for diffuse emission the surface brightness limits are 29.8 (visible) and 28.4 (near-infrared) mag arcsec$^{-2}$.

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arXiv2021

Euclid: Forecasts for $k$-cut $3 \times 2$ 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 {\it 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 $3 \times 2$ point statistics and estimate the loss of information for different $k$-cuts in a $3 \times 2$ point analysis of the {\it Euclid} data. Extending the Fisher matrix analysis of~\citet{blanchard2019euclid}, we assess the degradation in constraining power for different $k$-cuts. We work in the idealised case and assume the galaxy bias is linear, the covariance is Gaussian, while neglecting uncertainties due to photo-z errors and baryonic feedback. We find that taking a $k$-cut at $2.6 \ h \ {\rm Mpc} ^{-1}$ yields a dark energy Figure of Merit (FOM) of 1018. This is comparable to taking a weak lensing cut at $\ell = 5000$ and a galaxy clustering and galaxy-galaxy lensing cut at $\ell = 3000$ in a traditional $3 \times 2$ 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.

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arXiv2021

A joint 2- and 3-point clustering analysis of the VIPERS PDR2 catalogue at z~1: breaking the degeneracy of cosmological parameters

We measure the galaxy 2- and 3-point correlation functions at $z=[0.5,0.7]$ and $z=[0.7, 0.9]$, from the final data release of the VIPERS survey (PDR2). We model the two statistics including a nonlinear 1-loop model for the 2-point function and a tree-level model for the 3-point function, and perform a joint likelihood analysis. The entire process and nonlinear corrections are tested and validated through the use of the 153 highly realistic VIPERS mock catalogues, showing that they are robust down to scales as small as 10 $h^{-1} \, \mathrm{Mpc}$. The mocks are also adopted to compute the covariance matrix that we use for the joint 2- and 3-point analysis. Despite the limited statistics of the two (volume-limited) sub-samples analysed, we demonstrate that such a combination successfully breaks the degeneracy existing at 2-point level between clustering amplitude $σ_8$, linear bias $b_1$ and the linear growth rate of fluctuations $f$. For the latter, in particular, we measure $f(z=0.61)=0.64^{+0.55}_{-0.37}$ and $f(z=0.8)=1.0\pm1.0$, while the amplitude of clustering is found to be $σ_8(z=0.61)=0.50\pm 0.12$ and $σ_8(z=0.8)=0.39^{+0.11}_{-0.13}$. These values are in excellent agreement with the extrapolation of a Planck cosmology.

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arXiv2021

Euclid: constraining dark energy coupled to electromagnetism using astrophysical and laboratory data

In physically realistic scalar-field based dynamical dark energy models (including, e.g., quintessence) one naturally expects the scalar field to couple to the rest of the model's degrees of freedom. In particular, a coupling to the electromagnetic sector leads to a time (redshift) dependence of the fine-structure constant and a violation of the Weak Equivalence Principle. Here we extend the previous Euclid forecast constraints on dark energy models to this enlarged (but physically more realistic) parameter space, and forecast how well Euclid, together with high-resolution spectroscopic data and local experiments, can constrain these models. Our analysis combines simulated Euclid data products with astrophysical measurements of the fine-structure constant, $α$, and local experimental constraints, and includes both parametric and non-parametric methods. For the astrophysical measurements of $α$ we consider both the currently available data and a simulated dataset representative of Extremely Large Telescope measurements and expected to be available in the 2030s. Our parametric analysis shows that in the latter case the inclusion of astrophysical and local data improves the Euclid dark energy figure of merit by between $8\%$ and $26\%$, depending on the correct fiducial model, with the improvements being larger in the null case where the fiducial coupling to the electromagnetic sector is vanishing. These improvements would be smaller with the current astrophysical data. Moreover, we illustrate how a genetic algorithms based reconstruction provides a null test for the presence of the coupling. Our results highlight the importance of complementing surveys like Euclid with external data products, in order to accurately test the wider parameter spaces of physically motivated paradigms.

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arXiv2021

Euclid: Estimation of the impact of correlated readout noise for flux measurements with the Euclid NISP instrument

The Euclid satellite, to be launched by ESA in 2022, will be a major instrument for cosmology for the next decades. \Euclid\ is composed of two instruments: the Visible (VIS) instrument and the Near Infrared Spectromete and Photometer (NISP). In this work we estimate the implications of correlated readout noise in the NISP detectors for the final in-flight flux measurements. Considering the multiple accumulated (MACC) readout mode, for which the UTR (Up The Ramp) exposure frames are averaged in groups, we derive an analytical expression for the noise covariance matrix between groups in the presence of correlated noise. We also characterize the correlated readout noise properties in the NISP engineering grade detectors using long dark integrations. For this purpose, we assume a $(1/f)^{\, α}$-like noise model and fit the model parameters to the data, obtaining typical values of $σ= 19.7^{+1.1}_{-0.8}$ e$^{-} \rm{Hz}^{-0.5}$, $f_{\rm{knee}} = (5.2^{+1.8}_{-1.3}) \times 10^{-3} \, \rm{Hz}$ and $α= 1.24 ^{+0.26}_{-0.21}$. Furthermore, via realistic simulations and using a maximum likelihood flux estimator we derive the bias between the input flux and the recovered one. We find that using our analytical expression for the covariance matrix of the correlated readout noise we diminish this bias by up to a factor of four with respect to the white noise approximation for the covariance matrix. Finally, we conclude that the final bias on the in-flight NISP flux measurements should still be negligible even in the white noise approximation, which is taken as a baseline for the Euclid\on-board processing

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arXiv2021

Euclid preparation: XII. Optimizing the photometric sample of the Euclid survey for galaxy clustering and galaxy-galaxy lensing analyses

The accuracy of photometric redshifts (photo-zs) particularly affects the results of the analyses of galaxy clustering with photometrically-selected galaxies (GCph) and weak lensing. In the next decade, space missions like Euclid will collect photometric measurements for millions of galaxies. These data should be complemented with upcoming ground-based observations to derive precise and accurate photo-zs. In this paper, we explore how the tomographic redshift binning and depth of ground-based observations will affect the cosmological constraints expected from Euclid. We focus on GCph and extend the study to include galaxy-galaxy lensing (GGL). We add a layer of complexity to the analysis by simulating several realistic photo-z distributions based on the Euclid Consortium Flagship simulation and using a machine learning photo-z algorithm. We use the Fisher matrix formalism and these galaxy samples to study the cosmological constraining power as a function of redshift binning, survey depth, and photo-z accuracy. We find that bins with equal width in redshift provide a higher Figure of Merit (FoM) than equipopulated bins and that increasing the number of redshift bins from 10 to 13 improves the FoM by 35% and 15% for GCph and its combination with GGL, respectively. For GCph, an increase of the survey depth provides a higher FoM. But the addition of faint galaxies beyond the limit of the spectroscopic training data decreases the FoM due to the spurious photo-zs. When combining both probes, the number density of the sample, which is set by the survey depth, is the main factor driving the variations in the FoM. We conclude that there is more information that can be extracted beyond the nominal 10 tomographic redshift bins of Euclid and that we should be cautious when adding faint galaxies into our sample, since they can degrade the cosmological constraints.

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arXiv2021

Euclid: Effect of sample covariance on the number counts of galaxy clusters

Aims. We investigate the contribution of shot-noise and sample variance to the uncertainty of cosmological parameter constraints inferred from cluster number counts in the context of the Euclid survey. Methods. By analysing 1000 Euclid-like light-cones, produced with the PINOCCHIO approximate method, we validate the analytical model of Hu & Kravtsov 2003 for the covariance matrix, which takes into account both sources of statistical error. Then, we use such covariance to define the likelihood function that better extracts cosmological information from cluster number counts at the level of precision that will be reached by the future Euclid photometric catalogs of galaxy clusters. We also study the impact of the cosmology dependence of the covariance matrix on the parameter constraints. Results. The analytical covariance matrix reproduces the variance measured from simulations within the 10 per cent level; such difference has no sizeable effect on the error of cosmological parameter constraints at this level of statistics. Also, we find that the Gaussian likelihood with cosmology-dependent covariance is the only model that provides an unbiased inference of cosmological parameters without underestimating the errors.

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arXiv2021

Euclid: Forecast constraints on the cosmic distance duality relation with complementary external probes

In metric theories of gravity with photon number conservation, the luminosity and angular diameter distances are related via the Etherington relation, also known as the distance-duality relation (DDR). A violation of this relation would rule out the standard cosmological paradigm and point at the presence of new physics. We quantify the ability of Euclid, in combination with contemporary surveys, to improve the current constraints on deviations from the DDR in the redshift range $0<z<1.6$. We start by an analysis of the latest available data, improving previously reported constraints by a factor of 2.5. We then present a detailed analysis of simulated Euclid and external data products, using both standard parametric methods (relying on phenomenological descriptions of possible DDR violations) and a machine learning reconstruction using Genetic Algorithms. We find that for parametric methods Euclid can (in combination with external probes) improve current constraints by approximately a factor of six, while for non-parametric methods Euclid can improve current constraints by a factor of three. Our results highlight the importance of surveys like Euclid in accurately testing the pillars of the current cosmological paradigm and constraining physics beyond the standard cosmological model.

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arXiv2021

Euclid preparation: XI. Mean redshift determination from galaxy redshift probabilities for cosmic shear tomography

The analysis of weak gravitational lensing in wide-field imaging surveys is considered to be a major cosmological probe of dark energy. Our capacity to constrain the dark energy equation of state relies on the accurate knowledge of the galaxy mean redshift $\langle z \rangle$. We investigate the possibility of measuring $\langle z \rangle$ with an accuracy better than $0.002\,(1+z)$, in ten tomographic bins spanning the redshift interval $0.2 99.8\%$. The zPDF approach could also be successful if we debias the zPDF using a spectroscopic training sample. This approach requires deep imaging data, but is weakly sensitive to spectroscopic redshift failures in the training sample. We improve the debiasing method and confirm our finding by applying it to real-world weak-lensing data sets (COSMOS and KiDS+VIKING-450).

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arXiv2020

Euclid preparation: VII. Forecast validation for Euclid cosmological probes

The Euclid space telescope will measure the shapes and redshifts of galaxies to reconstruct the expansion history of the Universe and the growth of cosmic structures. Estimation of the expected performance of the experiment, in terms of predicted constraints on cosmological parameters, has so far relied on different methodologies and numerical implementations, developed for different observational probes and for their combination. In this paper we present validated forecasts, that combine both theoretical and observational expertise for different cosmological probes. This is presented to provide the community with reliable numerical codes and methods for Euclid cosmological forecasts. We describe in detail the methodology adopted for Fisher matrix forecasts, applied to galaxy clustering, weak lensing and their combination. We estimate the required accuracy for Euclid forecasts and outline a methodology for their development. We then compare and improve different numerical implementations, reaching uncertainties on the errors of cosmological parameters that are less than the required precision in all cases. Furthermore, we provide details on the validated implementations that can be used by the reader to validate their own codes if required. We present new cosmological forecasts for Euclid. We find that results depend on the specific cosmological model and remaining freedom in each setup, i.e. flat or non-flat spatial cosmologies, or different cuts at nonlinear scales. The validated numerical implementations can now be reliably used for any setup. We present results for an optimistic and a pessimistic choice of such settings. We demonstrate that the impact of cross-correlations is particularly relevant for models beyond a cosmological constant and may allow us to increase the dark energy Figure of Merit by at least a factor of three.

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arXiv2020

Euclid preparation: X. The Euclid photometric-redshift challenge

Forthcoming large photometric surveys for cosmology require precise and accurate photometric redshift (photo-z) measurements for the success of their main science objectives. However, to date, no method has been able to produce photo-$z$s at the required accuracy using only the broad-band photometry that those surveys will provide. An assessment of the strengths and weaknesses of current methods is a crucial step in the eventual development of an approach to meet this challenge. We report on the performance of 13 photometric redshift code single value redshift estimates and redshift probability distributions (PDZs) on a common set of data, focusing particularly on the 0.2--2.6 redshift range that the Euclid mission will probe. We design a challenge using emulated Euclid data drawn from three photometric surveys of the COSMOS field. The data are divided into two samples: one calibration sample for which photometry and redshifts are provided to the participants; and the validation sample, containing only the photometry, to ensure a blinded test of the methods. Participants were invited to provide a redshift single value estimate and a PDZ for each source in the validation sample, along with a rejection flag that indicates sources they consider unfit for use in cosmological analyses. The performance of each method is assessed through a set of informative metrics, using cross-matched spectroscopic and highly-accurate photometric redshifts as the ground truth. We show that the rejection criteria set by participants are efficient in removing strong outliers, sources for which the photo-z deviates by more than 0.15(1+z) from the spectroscopic-redshift (spec-z). We also show that, while all methods are able to provide reliable single value estimates, several machine-learning methods do not manage to produce useful PDZs. [abridged]

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arXiv2020

Euclid: impact of nonlinear prescriptions on cosmological parameter estimation from weak lensing cosmic shear

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 by the 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 nonlinear corrections lead to biased parameter estimates, especially when the analysis is extended into the highly nonlinear regime, with both the Hubble constant, $H_0$, and the clustering amplitude, $σ_8$, affected the most. Improvements in the modelling of nonlinear scales will therefore be needed if we are to resolve the current tension with more and better data. For a given prescription for the nonlinear 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 nonlinear structure formation, as well as the modelling of the impact of astrophysical processes that redistribute the baryons.

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arXiv2020

Euclid preparation: IX. EuclidEmulator2 -- Power spectrum emulation with massive neutrinos and self-consistent dark energy perturbations

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. Percent-level accurate emulation is now supported in the eight-dimensional parameter space of $w_0w_a$CDM$+\sum m_ν$models between redshift $z=0$ and $z=3$ for spatial scales within the range 0.01 $h$/Mpc $\leq k \leq$ 10 $h$/Mpc. 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: (1) we use self-consistent linear evolution of non-dark matter species such as massive neutrinos, photons, dark energy and the metric field, (2) we perform the simulations in the so-called N-body gauge, which allows one to interpret the results in the framework of general relativity, (3) we run over 250 high-resolution simulations with $3000^3$ particles in boxes of 1 (Gpc/$h$)${}^3$ volumes based on paired-and-fixed initial conditions and (4) 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 $w_a$ 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% or better for 0.01 $h$/Mpc $\leq k \leq$ 10 $h$/Mpc and $z\leq3$ compared to high-resolution dark matter only simulations. EuclidEmulator2 is publicly available at https://github.com/miknab/EuclidEmulator2 .

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arXiv2020

Extended Fast Action Minimisation method: application to SDSS-DR12 Combined Sample

We present the first application of the extended Fast Action Minimization method (eFAM) to a real dataset, the SDSS-DR12 Combined Sample, to reconstruct galaxies orbits back-in-time, their two-point correlation function (2PCF) in real-space, and enhance the baryon acoustic oscillation (BAO) peak. For this purpose, we introduce a new implementation of eFAM that accounts for selection effects, survey footprint, and galaxy bias. We use the reconstructed BAO peak to measure the angular diameter distance, D_A(z)r^{fid}_s/r_s, and the Hubble parameter, H(z)r_s/r^{fid}_s, normalized to the sound horizon scale for a fiducial cosmology r^{fid}_s, at the mean redshift of the sample z=0.38, obtaining D_A(z=0.38)r^{fid}_s/r_s=1090 +/- 29 (Mpc)^{-1}, and H(z=0.38)r_s}/r^{fid}_s=83 +/- 3 (km s^{-1}Mpc^{-1}), in agreement with previous measurements on the same dataset. The validation tests, performed using 400 publicly available SDSS-DR12 mock catalogues, reveal that eFAM performs well in reconstructing the 2PCF down to separations of 25h^{-1}Mpc$, i.e. well into the non-linear regime. Besides, eFAM successfully removes the anisotropies due to redshift-space distortion at all redshifts including that of the survey, allowing us to decrease the number of free parameters in the model and fit the full-shape of the back-in-time reconstructed 2PCF well beyond the BAO peak. Recovering the real-space 2PCF, eFAM improves the precision on the estimates of the fitting parameters. When compared with the no-reconstruction case, eFAM reduces the uncertainty of the Alcock-Paczynski distortion parameters of about 40% and that on the non-linear damping scale of about 70%. These results show that eFAM can be successfully applied to existing redshift galaxy catalogues and should be considered as a reconstruction tool for next-generation surveys alternative to popular methods based on the Zel'dovich approximation.

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arXiv2020

Euclid preparation: VIII. The Complete Calibration of the Colour-Redshift Relation survey: VLT/KMOS observations and data release

The Complete Calibration of the Colour-Redshift Relation survey (C3R2) is a spectroscopic effort involving ESO and Keck facilities designed to empirically calibrate the galaxy colour-redshift relation - P(z|C) to the Euclid depth (i_AB=24.5) and is intimately linked to upcoming Stage IV dark energy missions based on weak lensing cosmology. The aim is to build a spectroscopic calibration sample that is as representative as possible of the galaxies of the Euclid weak lensing sample. In order to minimise the number of spectroscopic observations to fill the gaps in current knowledge of the P(z|C), self-organising map (SOM) representations of the galaxy colour space have been constructed. Here we present the first results of an ESO@ VLT Large Programme approved in the context of C3R2, which makes use of the two VLT optical and near-infrared multi-object spectrographs, FORS2 and KMOS. This paper focuses on high-quality spectroscopic redshifts of high-z galaxies observed with the KMOS spectrograph in the H- and K-bands. A total of 424 highly-reliable z are measured in the 1.3<=z<=2.5 range, with total success rates of 60.7% in the H-band and 32.8% in the K-band. The newly determined z fill 55% of high and 35% of lower priority empty SOM grid cells. We measured Halpha fluxes in a 1."2 radius aperture from the spectra of the spectroscopically confirmed galaxies and converted them into star formation rates. In addition, we performed an SED fitting analysis on the same sample in order to derive stellar masses, E(B-V), total magnitudes, and SFRs. We combine the results obtained from the spectra with those derived via SED fitting, and we show that the spectroscopic failures come from either weakly star-forming galaxies (at z<1.7, i.e. in the H-band) or low S/N spectra (in the K-band) of z>2 galaxies.

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arXiv2019

Euclid preparation: V. Predicted yield of redshift 7<z<9 quasars from the wide survey

We provide predictions of the yield of $7 8$ may be selected from Euclid $OYJH$ photometry alone, but selection over the redshift interval $7 7.5$ should be found in the DR1 data release, expected in 2024. It will be possible to determine the bright-end slope of the QLF, $7<z<8$, $M_{1450}<-25$, using 8m class telescopes to confirm candidates, but follow-up with JWST or E-ELT will be required to measure the faint-end slope. Contamination of the candidate lists is predicted to be modest even at $J_{AB}\sim23$. The precision with which $k$ can be determined over $7<z<8$ depends on the value of $k$, but assuming $k=-0.72$ it can be measured to a 1 sigma uncertainty of 0.07.

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arXiv2019

Euclid preparation: VI. Verifying the Performance of Cosmic Shear Experiments

Our aim is to quantify the impact of systematic effects on the inference of cosmological parameters from cosmic shear. We present an end-to-end approach that introduces sources of bias in a modelled weak lensing survey on a galaxy-by-galaxy level. Residual biases are propagated through a pipeline from galaxy properties (one end) through to cosmic shear power spectra and cosmological parameter estimates (the other end), to quantify how imperfect knowledge of the pipeline changes the maximum likelihood values of dark energy parameters. We quantify the impact of an imperfect correction for charge transfer inefficiency (CTI) and modelling uncertainties of the point spread function (PSF) for Euclid, and find that the biases introduced can be corrected to acceptable levels.

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arXiv2019

Estimating the galaxy two-point correlation function using a split random catalog

The two-point correlation function of the galaxy distribution is a key cosmological observable that allows us to constrain the dynamical and geometrical state of our Universe. To measure the correlation function we need to know both the galaxy positions and the expected galaxy density field. The expected field is commonly specified using a Monte-Carlo sampling of the volume covered by the survey and, to minimize additional sampling errors, this random catalog has to be much larger than the data catalog. Correlation function estimators compare data-data pair counts to data-random and random-random pair counts, where random-random pairs usually dominate the computational cost. Future redshift surveys will deliver spectroscopic catalogs of tens of millions of galaxies. Given the large number of random objects required to guarantee sub-percent accuracy, it is of paramount importance to improve the efficiency of the algorithm without degrading its precision. We show both analytically and numerically that splitting the random catalog into a number of subcatalogs of the same size as the data catalog when calculating random-random pairs, and excluding pairs across different subcatalogs provides the optimal error at fixed computational cost. For a random catalog fifty times larger than the data catalog, this reduces the computation time by a factor of more than ten without affecting estimator variance or bias.

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