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O. Mansutti

Publications and source records attributed to O. Mansutti.

At least 37 records · Page 2Linked to original sources

Euclid: Precise inference of defocus wavefront error from image diffraction spike measurements

The success of the Euclid cosmological weak lensing measurements requires unprecedented knowledge of the point spread function (PSF) shape. Defocus wavefront errors induce variations in PSF size that directly bias inferred galaxy shapes. We present a rapid, model-independent estimator of the Euclid visible instrument defocus based on measuring subpixel shifts in diffraction spikes from bright stars, arising from the non-mirror-symmetric placement of the telescope spiders. This estimate requires no a-priori PSF model and can be directly inferred from individual survey exposures within seconds. We express defocus as the secondary mirror displacement along the optical axis, $Δz$, achieving a per-exposure precision of $σ(Δz) = 0.022\,μ\text{m}$ in standard Euclid wide-survey images, corresponding to a peak-to-valley optical-path difference of $0.75\,\text{nm}$. This sensitivity resolves thermally induced shifts, typically 0.1-0.3$\,μ\text{m}$, and enables tracking of temporal evolution and field-of-view variations when combining exposures within periods of stability. Since July 2024, the Euclid telescope has been exceptionally stable, while changes to defocus are effectively homogeneous across the field of view. By correlating defocus with PSF size, we find that the Euclid DR3 requirement of a fractional PSF size bias of $\left|ΔR_\mathrm{PSF}^2/R_\mathrm{PSF}^2\right|<10^{-3}$ corresponds to field-averaged secondary mirror displacements exceeding $\langle Δz_\mathrm{thr}\rangle = (0.0683 \pm 0.0024)\,μ\text{m}$. Our estimator provides a robust real-time monitoring tool, supplies a stringent prior for computationally intensive PSF model fitting, and is applicable not only to the Euclid telescope, but to other telescopes whose spider vanes are not mirror-symmetrically arranged.

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The PAU Survey and Euclid: Analysing photometric redshifts from realistically simulated narrow-band photometry with Flagship 2

The study of the large-scale structure of the Universe and the distribution of galaxies has been greatly advanced by the application of various types of photometric redshift estimation techniques. The Physics of the Accelerating Universe Survey (PAUS) is a state-of-the-art imaging survey, designed to provide high-quality photometric data in 40 optical narrow-band filters. In this paper, we present an in-depth analysis of the photometric redshifts obtained from PAUS using realistic simulations. Based on the Euclid Flagship 2 catalogue, we generate PAUS-like simulations with realistic photometric noise and target selection. The mock catalogue is used to explore the accuracy and precision of photometric redshifts of PAUS, investigating the impact of noise and depth, and combinations of broad- and narrow-band data. The simulations reproduce the observed PAUS performance well, with a robust photometric redshift scatter of $σ_{NMAD}/(1+z)\!=\!0.011$ for a mock subsample resembling the spectroscopic validation sample of the data. For the complete PAUS-like sample, which can only be evaluated in the simulation, we find $σ_{NMAD}/(1+z)\!=\!0.028$ for $i_{\rm AB}\!\lesssim\!23$ and outlier fractions below 10%. Forecasts indicate that including Euclid photometry in a joint analysis could further reduce scatter and outlier fractions, especially for faint galaxy populations. The hypothetical case of deeper PAUS observations over a limited sky area, forecasting the potential for future narrow- or medium-band surveys, in combination with Euclid's deep photometry, achieves scatter as low as $σ_{NMAD}/(1+z)\!=\!0.011$ and outlier fractions below 4% for $i_{\rm AB}\!<\!23.5$.

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Euclid Quick Data Release (Q1): The geometry of dark matter halos from extragalactic streams

Wide-field surveys like Euclid mark a new era of extragalactic stellar stream studies. With a large number of streams, it is now possible to constrain the dark matter halos of galaxies in a cosmological volume and draw comparisons to theoretical expectations for the geometry of dark matter halos. This study combines Euclid imaging with visual detection and segmentation annotations to analyse streams. We use projected stream morphologies to constrain the shape and centre-of-mass position (CoM) of each host galaxy's potential, jointly probing baryonic and dark matter distributions. These inferences complement weak lensing methods, with sensitivity to halo profile and geometry on sub-virial scales. The method enables both stacked, population-level constraints on halo flattening and CoM position, and constraints on these quantities for individual halos. We also present a novel method for transforming segmentation maps of stellar streams into smooth, curvature-preserving tracks optimised for fast and robust dynamical inference. This approach enables rapid modelling of stream morphology, supports a statistically rigorous combination of constraints across multiple streams within a single galaxy, and enables joint inference across galactic hosts. From our study of 13 galaxies with prominent tidal streams, we find agreement with spherical halos, albeit a mild preference for flattening with $q = 0.95^{+0.05}_{-0.10}$ at 68\% confidence. This is promising early agreement with $Λ$CDM predictions. With thousands more discovered streams expected across \Euclid's mission, our programme will enable precise measurements of halo shapes and CoM positions across large samples and redshifts, offering constraints on the geometry of dark matter halos.

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Euclid: Quick Data Release (Q1) -- LensMC shear measurement catalogue for cluster lensing science

We present a LensMC lensing analysis of Euclid Quick Release 1 images that were made available in March 2025. We measured shapes, positions, weights, and other morphological parameters of galaxies with a surface number density of $26\;\text{arcmin}^{-2}$ for $I_{\scriptscriptstyle\rm E}<24.5$, achieving 75 arcmin$^{-2}$ for $I_{\scriptscriptstyle\rm E}<27$, in 63 deg$^2$ of Euclid VIS images. This is the first shear measurement catalogue produced with \lensmc in anticipation of the Euclid Data Release 1. To within the scope of this work and availability of survey volume, we found no spatial dependency in the additive biases. However, we developed an empirical bias correction based jointly on galaxy sizes and magnitudes, which was applied to the measurement of the lensing signal over the whole area. In order to validate the quality of our measurements, we calculated two-point statistics and cluster profile measurements, and cross-checked results with external cluster catalogues from WISE and the Dark Energy Survey. Additionally, by stacking shear profiles of random clusters we found that the low-redshift, large radii bins may be still contaminated by residual systematic effects. Thanks to Euclid image resolution and depth and overall good control of systematic errors, we are able to constrain the lensing profiles of clusters with masses of $10^{14}M_\odot$ out to $z\approx2$ over nearly 10 Gyr of evolution history.

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Euclid preparation. CIV. Impact of galaxy intrinsic alignment modelling choices on Euclid 3x2pt cosmology

The Euclid galaxy survey will provide unprecedented constraints on cosmology, but achieving unbiased results will require an optimal characterisation and mitigation of systematic effects. The intrinsic alignments (IAs) of galaxies are one of the dominant contaminants of the weak lensing (WL) and galaxy-galaxy lensing (GGL) probes. In this work, we assess IA modelling choices for Euclid DR1 3x2pt analyses by using synthetic data vectors and comparing the performance of the two most commonly used IA models, non-linear alignment (NLA) and tidal alignment tidal torquing (TATT), along with several variations. Our analyses combine three perspectives: (i) the constraining power on the IA and cosmological parameters for each IA model, (ii) the bias that results when the IA analysis model differs from the model used to generate the synthetic data vector, and (iii) the degeneracies between IAs and photometric redshift (photo-z) nuisance parameters. Amongst the IA models analysed, the redshift-dependent TATT model (zTATT) provides the most flexible description of IAs, with a constraining power similar to simpler IA models, making it a suitable choice for Euclid DR1 3x2pt analyses.

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Euclid preparation. CII. Non-Gaussianity of 2-pt statistics likelihood: Parameter inference with a non-Gaussian likelihood in Fourier and configuration space

In this work we account for this skewness in parameter inference by modelling the likelihood through an Edgeworth expansion which involves the complete skewness tensor, composed of 1-point, 2-point, and 3-point correlators. To simplify the calculations of this expansion we perform a change of basis which reduces the precision matrix to the identity. In this basis, the off-diagonal elements of the skewness tensor are consistent with zero, while the amplitude of its diagonal match the level expected for a Gaussian underlying field. We perform parameter inference with this likelihood model and find that including only the diagonal part of the skewness is sufficient, while incorporating the full skewness tensor injects noise without improving accuracy. Despite the estimated excess skewness in the original basis, the cosmological constraints remain effectively unchanged when adopting a Gaussian likelihood or considering the more complete Edgeworth expansion, with variations in the figure of merit of cosmological parameters between the two cases below $5\%$. This result remains unchanged against variations of the survey volume and geometry, scale-cut, and 2-point statistic (power spectrum or correlation function). Using $10\, 000$ cloned \Euclid large mocks based on realistic galaxy catalogues with characteristics close to future \Euclid data, we find no detectable excess skewness on intermediate scales, due to the level of shot noise expected for the \Euclid spectroscopic sample. We conclude that the Gaussian likelihood assumption is robust for \Euclid 2-point statistics analyses in both Fourier and configuration space.

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Euclid: Photometric redshift calibration with the clustering redshifts technique

Aims: The precision of cosmological constraints from imaging surveys hinges on accurately estimating the redshift distribution $ n(z) $ of tomographic bins, especially their mean redshifts. We assess the effectiveness of the clustering redshifts technique in constraining Euclid tomographic redshift bins to meet the target uncertainty of $ σ( \langle z \rangle ) < 0.002 (1 + z) $. In this work, these mean redshifts are inferred from the small-scale angular clustering of Euclid galaxies, which are distributed into bins with spectroscopic samples localised in narrow redshift slices. Methods: We generate spectroscopic mocks from the Flagship2 simulation for the Baryon Oscillation Spectroscopic Survey (BOSS), the Dark Energy Spectroscopic Instrument (DESI), and Euclid's Near-Infrared Spectrometer and Photometer (NISP) spectroscopic survey. We evaluate and optimise the clustering redshifts pipeline, introducing a new method for measuring photometric galaxy bias (clustering), which is the primary limitation of this technique. Results: We have successfully constrained the means and standard deviations of the redshift distributions for all of the tomographic bins (with a maximum photometric redshift of 1.6), achieving precision beyond the required thresholds. We have identified the main sources of bias, particularly the impact of the 1-halo galaxy distribution, which imposed a minimal separation scale of 1.5 Mpc for evaluating cross-correlations. These results demonstrate the potential of clustering redshifts to meet the precision requirements for Euclid, and we highlight several avenues for future improvements.

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Euclid: Early Release Observations -- The formation of peanutty dwarf galaxies in Perseus

Dwarf galaxies in dense cluster environments are susceptible to tidal interactions that can alter their morphology and kinematics. Boxy isophotes are well studied in massive galaxies but remain poorly understood in dwarfs. We aim to identify and characterise boxy/peanutty dwarf galaxies in the Perseus cluster and determine the origin of their isophotal shapes. Using Euclid Early Release Observations of the Perseus cluster, we present a cumulative light fraction method for robustly measuring the isophotal shape parameter $c_4$, particularly suited to low surface brightness regimes. From ~1100 cataloged dwarfs, we select a clean sample of ~190 early-type systems with reliable $c_4$ measurement. Observed trends are interpreted through comparison with mock Euclid observations of $N$-body simulations of tidally transformed dwarfs. We identify 13 dwarfs with significantly boxy isophotes ($c_4 < -0.0175$). These galaxies lack visible thin disks, lie on the cluster red sequence, and show no preferential spatial concentration within Perseus. We find a significant anticorrelation between $c_4$ and effective radius: larger galaxies exhibit more boxy isophotes. An analogous size-shape anticorrelation is recovered in the simulations, where inner regions are dominated by box orbits associated with a triaxial peanut structure and outer regions by short-axis tube orbits. The boxy dwarfs in Perseus are tidally transformed remnants of moderately rotating progenitors, with boxy isophotes tracing inner box-orbit-dominated peanut structures. The size-shape correlation arises from viewing geometry: face-on orientations reveal the rectangular profile of the elongated triaxial structure (large and boxy), while edge-on views yield rounder, compact morphologies. Our sample represents an orientation-selected subset of tidally transformed, peanutty dwarfs in the cluster.

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Euclid preparation: Testing multi-field inflation with galaxy power spectrum and bispectrum

Primordial non-Gaussianity (PNG) is a powerful probe of the origin of cosmic structure. Stage-IV surveys like \Euclid will measure galaxy $2$- and $3$-point clustering at high signal-to-noise, whose exploitation requires robust joint analysis. We prepare for Euclid's spectroscopic sample by validating a redshift-space power-spectrum and bispectrum pipeline (one-loop $P_\ell$, tree-level $B_\ell$) on Euclid-like mocks from Abacus-PNG $N$-body simulations with Gaussian and local-PNG initial conditions, using a halo occupation distribution (HOD) tuned to Euclid Flagship 2. We stress-test analysis choices -- PNG-bias parametrisation, priors, and scale cuts -- and perform null tests without PNG. In a `prior-agnostic setup', detection of the dominant PNG term $\propto f_{\rm NL} \, b_ϕ$ in single redshift bins is difficult; nevertheless, the bispectrum provides constraints on other PNG combinations that partially lift degeneracies. We propose a physically motivated prior on $b_ϕ$ that yields unbiased $f_{\rm NL}$ while accounting for theory uncertainty, and determine scale cuts that give unbiased $Λ$CDM and $f_{\rm NL}$. With $V_{\rm eff}=16\,h^{-3}\,{\rm Gpc}^3$ across four snapshots ($0.8\le z\le1.7$), our likelihood analyses recover $<1σ$ bias in $f_{\rm NL}$ and $Λ$CDM. At fixed cuts, $B_\ell$ alone reduces $σ({f_{\rm NL}})$ by $\sim29$--$46\%$ relative to $P_\ell$, and joint power spectrum-bispectrum analysis tightens a further $\sim8$--$13\%$; the cumulative gain from $z=0.8$ to $1.7$ is $\sim2.3$ for the joint case. The bispectrum quadrupole is key. Our strongest results are at $z=1.7$: $1.9σ$ for $f_{\rm NL} \, b_ϕ$ (prior-agnostic) and $2.35σ$ for $f_{\rm NL}$ (prior-based). Joint analyses thus offer strong prospects for testing multi-field inflation, pending end-to-end validation in the full Euclid geometry with observational systematics.

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Euclid preparation. Decomposing components of the extragalactic background light using multi-band intensity mapping cross-correlations

The extragalactic background light (EBL) fluctuations in the optical/near-IR encode the cumulative integrated galaxy light (IGL), diffuse intra-halo light (IHL), and high-$z$ sources from the epoch of reionisation (EoR), but they are difficult to disentangle with auto-spectra alone. We aim to decompose the EBL into its principal constituents using multi-band intensity mapping combined with cosmic shear and galaxy clustering. We develop a joint halo-model framework in which IHL follows a mass- and redshift-dependent luminosity scaling, IGL is set by an evolving Schechter luminosity function, and EoR emission is modelled with Pop II/III stellar emissivities and a binned star-formation efficiency. Using mock surveys in a flat $Λ$CDM cosmology with ten spectral bands spanning 0.75-5.0$\rm μm$ in the NEP deep fields over about 100$°^2$ with source detections down to AB=20.5 for masking, and six redshift bins to $z=2.5$, we fit auto- and cross-power spectra using a MCMC method. The combined SPHEREx$\times$Euclid analysis recovers all fiducial parameters within 1$σ$ and reduces 1$σ$ uncertainties on IHL parameters by 10-35% relative to SPHEREx EBL-only, while EoR star-formation efficiency parameters improve by 20-35%. Cross-correlations reveal a stronger coupling of IHL than IGL to the shear field, enhancing component separation; conversely, the EoR contribution shows negligible correlation with cosmic shear and galaxy clustering, aiding its isolation in the EBL. Relative to the SPHEREx EBL-only case, the inferred IHL fraction as a function of halo mass is significantly tightened over $10^{11}-10^{14} M_{\odot}$, with uncertainties reduced by 5-30%, and the resulting star-formation rate density constraints extend to $z\sim 11$, with uncertainty reductions of 22-31%.

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Euclid preparation. Three-dimensional galaxy clustering in configuration space: Three-point correlation function estimation

Higher-order correlation functions are firmly established as a fundamental tool for the statistical analysis of clustering in modern galaxy surveys. It was demonstrated that they greatly enrich the information content extracted by two-point statistics, allowing us to break the degeneracies between model parameters and constrain departures from Gaussianity. This paper presents the statistical estimators adopted to evaluate the galaxy three-point correlation function and its numerical implementation within the data analysis pipeline of the Euclid Science Ground Segment. Two different algorithms are adopted to count triplets: a direct and exact counting method capable of providing a robust three-point correlation function measurement for any triangular configuration, and a more efficient method based on spherical harmonic decomposition, designed to address the computational challenges of measuring the three-point statistics for data sets as large as those of the final Euclid survey. The spherical harmonic decomposition estimates the Legendre coefficients of the three-point correlation function up to a finite expansion order. Despite being an approximation, the three-point function measured with this approach satisfies the scientific requirements of the mission. We also introduce, implement, and validate the random split technique, which reduces the computational cost of counting triplets in the reference random sample by a factor of 10, without significantly compromising numerical accuracy. We evaluated the robustness, precision, and accuracy of the numerical estimates through an extensive campaign of validation tests, the results of which are presented. Finally, we quantify the computational requirements and their scaling with the expected size of Euclid data set, showing that a complete three-point analysis of the final Euclid survey is within computational reach.

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Euclid preparation. Refining input galaxy shape distributions for shear calibration simulations

The Euclid Wide Survey (EWS) will cover the majority of the extragalactic sky with a resolution similar to the Hubble Space Telescope. This unprecedented data set will introduce a new era of precision cosmology. However, systematic effects need to be controlled better than ever. One of the sources of systematic uncertainties in weak gravitational lensing are biases introduced during the shear measurement. Determining these biases precisely allows the calibration of cosmological measurements to within Euclid's required accuracy. The simulations that are used to determine such biases, need to resemble the real observations. In this work, we aim to learn distributions of galaxy shape parameters from real Euclid data and use the new information to augment the morphological information in the Flagship galaxy mock catalogue. The morphology is extracted using single and double-Sérsic model fits to the real data, for which we use SourceXtractor++. We train our pipeline on deep Euclid observations of a field with rich auxiliary data and then use it to simulate EWS-like data. In these simulations we compare the multiplicative bias between the morphology from the Flagship catalogue, the trained single-Sérsic morphology, and the trained double-Sérsic morphology. We find that the image simulations with the updated morphology result in a percent-level change in the multiplicative shear bias compared to the original morphology from Flagship. This bias exceeds Euclid's tight error budget by a factor of five and underlines the need for this work. Furthermore, we study the sensitivity of the multiplicative bias to key morphological parameters and show that our approach satisfies the requirements for the cosmology analysis with the first data release of Euclid.

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Euclid: Asteroid rotation periods from the Euclid Ecliptic Survey

The Euclid Ecliptic Survey was conducted during the calibration phase of the mission, 23-31 December 2023, as a campaign to study Solar System objects. We used data from this survey to analyse more than 23 000 appeareances of 2321 known asteroids. Due to their high apparent angular motion relative to the background stars (5-$60^{\prime\prime}\,\mathrm{h}^{-1}$), these objects appear as streaks in VIS long-exposure images. We set out to estimate their spin periods, since only $7\%$ of them have periods published in the literature. We used multiple apertures along each streak to increase the time resolution of our light curves. Our method combines a Lomb-Scargle approach with a Markov chain Monte Carlo (MCMC) algorithm to characterise the posterior distributions. Some asteroids show multimodality in the MCMC search, indicating period aliases; in these cases, we report all aliases and their likelihoods. We validate our pipeline by comparing our fitted periods with 48 published periods, including period harmonics. We find that $44\%$ of our periods are within $1\%$ of those published and $98\%$ are within $15\%$, and we establish that with $98\%$ confidence the best solution can be found among the first three aliases. All reliable periods reported agree with our current understanding of the spin-period distribution for asteroids. We find 16 periods below the spin barrier of 2.2 h with absolute magnitudes below 19, and thus 16 candidate super-fast rotators. We provide light curves for all 2321 objects observed and 889 high-quality periods in an open-access catalogue. The asteroids with reported periods include five Mars crossers, four Cybeles, four Hildas, three Hungarias, and 877 asteroids in other regions of the main belt. Our results represent the first batch of spin periods extracted from Euclid light curves and include the first-ever period measurements for $93\%$ of the objects.

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Euclid: Quick Data Release (Q1) -- Dual AGN in low-mass galaxies

Dual active galactic nuclei (AGNs) are expected in hierarchical galaxy evolution models, in which low-mass galaxies merge to build more massive ones. While observational evidence for dual AGNs is growing in massive galaxies, no clear detection has yet been found in the low-mass regime. We used photometry and spectroscopy from the first \Euclid Quick Data Release, combined with a collection of multi-wavelength data from the Dark Energy Spectroscopic Instrument (DESI), the LOw-Frequency ARray (LOFAR) high band antenna, and counterparts in X-ray and mid-infrared catalogues to identify dual AGNs at redshift $z \lesssim 1$. Focusing on low-mass galaxies with stellar masses below 10$^{10}$ M$_{\odot}$, we find nine dual AGN candidates with projected separations ranging from $\sim$20 to 51 kpc. We also find 49 dual AGN candidates in more massive galaxies. We derive a dual AGN fraction of 0.1\% for the low-mass galaxies and estimate that these systems likely trace a population of progenitor black hole pairs that may evolve into bound binaries and eventually coalesce, emitting gravitational waves in the LISA band. These results constitute the first sample of spectroscopically confirmed dual AGN candidates in low-mass galaxies and have important implications for models in which supermassive black holes grow from lower-mass black holes located in low-mass galaxies, as well as for predictions of gravitational waves from low-mass binary black holes.

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Euclid: A blue galaxy population and a brightest cluster galaxy in the making in a $z\sim1.74$ MaDCoWS2 galaxy cluster candidate

We present an example cluster follow-up study with Euclid. Our target, a $z\sim 1.74$ candidate cluster nicknamed the 'Puddle', was initially discovered by the Massive and Distant Clusters of WISE Survey 2 as a $z_\mathrm{phot}\sim 1.65$ candidate cluster. It was also detected independently as a $z_\mathrm{phot}\sim 1.5$ candidate with the two cluster-finding algorithms in Euclid Quick Release 1 (Q1). A Keck MOSFIRE spectrum shows the brightest nucleus is at $z=1.74$ and is dominated by an active galactic nucleus. Our analysis focused on the galaxy population and the brightest cluster galaxy (BCG), and is based on Euclid and ancillary photometry. Compared to similar fields, we measured an overdensity of $110\pm 14$ galaxies with $H_\mathrm{E}\leq 22.25$ in a 2' radius around the BCG. About $18\pm 4$% of the completeness-corrected galaxy population is red, which is consistent with some clusters at $z>1.5$ but lower than others. Euclid imaging revealed that six or seven galaxies appear to be assembling to form the future BCG. Spectral energy distribution fitting suggests that the merging BCG has a stellar mass of $5.7\pm 0.3\times 10^{11}\,M_\odot$ and that it experienced a short burst of star formation $\sim 300\,$Myr ago. Its morphology and star-formation history suggest that the proto-BCG is a more evolved version of the merging core of SPT2349$-$56. These systems indicate that multiobject mergers might be a common BCG formation process. Assuming a similar density of mergers in the Euclid Wide Survey, we expect that Euclid will discover approximately 400 assembling BCGs by the end of its mission.

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Euclid preparation. LXXXIX. Accurate and precise data-driven angular power spectrum covariances

We develop techniques for generating accurate and precise internal covariances for measurements of clustering and weak-lensing angular power spectra. These methods have been designed to produce non-singular and unbiased covariances for Euclid's large anticipated data vector and will be critical for validation against observational systematic effects. We constructed jackknife segments that are equal in area to a high precision by adapting the binary space partition algorithm to work on arbitrarily shaped regions on the unit sphere. Jackknife estimates of the covariances are internally derived and require no assumptions about cosmology or galaxy population and bias. Our covariance estimation, called DICES (Debiased Internal Covariance Estimation with Shrinkage), first estimated a noisy covariance through conventional delete-1 jackknife resampling. This was followed by linear shrinkage of the empirical correlation matrix towards the Gaussian prediction, rather than linear shrinkage of the covariance matrix. Shrinkage ensures the covariance is non-singular and therefore invertible, which is critical for the estimation of likelihoods and validation. We then applied a delete-2 jackknife bias correction to the diagonal components of the jackknife covariance that removed the general tendency for jackknife error estimates to be biased high. We validated internally derived covariances, which used the jackknife resampling technique, on synthetic Euclid-like lognormal catalogues. We demonstrate that DICES produces accurate, non-singular covariance estimates, with the relative error improving by 33% for the covariance and 48% for the correlation structure in comparison to jackknife estimates. These estimates can be used for highly accurate regression and inference.

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Euclid preparation. Impact of redshift distribution uncertainties on the joint analysis of photometric galaxy clustering and weak gravitational lensing

One of the $\textit{Euclid}$ mission's key projects is the so-called 3$\times$2pt analysis, that is, the combination of cosmic shear, photometric galaxy clustering, and galaxy-galaxy lensing. Although $\textit{Euclid}$ has established quality requirements for the photo-$z$ accuracy needed for the weak lensing galaxy sample, no such requirements have been set for the photometric clustering sample. In this paper, we investigate the impact of redshift uncertainties on $\textit{Euclid}$'s photometric galaxy clustering analysis and its combination with weak gravitational lensing, focusing on data release 1 (DR1). In particular, we study whether having precise knowledge of the mean of the redshift distributions per bin is sufficient to avoid biases in the resulting cosmological constraints or whether accuracy in the higher-order moments of the distribution is required. We evaluate the results based on their constraining power on $w_{\mathrm{0}}$ and $w_{a}$ and define thresholds for the precision and accuracy of $\textit{Euclid}$'s redshift distribution of the photometric clustering sample. We find that the redshift distributions of the photometric clustering sample must be known at an accuracy of 0.004(1+$z$) in the mean in order to recover 80$\%$ of the constraining power in $\textit{Euclid}$'s DR1 $w_{\mathrm{0}}w_{a}$CDM 3$\times$2pt analysis. The impact of the uncertainty on the width is negligible, provided the mean redshift is constrained with sufficient accuracy. For most sources of redshift distribution error, attaining the requirement on the mean will also reduce uncertainty in the width well below the required level.

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Euclid preparation. XCII. Controlling angular systematics in the Euclid spectroscopic galaxy sample

We present the strategy used to identify and mitigate potential sources of angular systematics in the \textit{Euclid} spectroscopic galaxy survey, and we quantify their impact on galaxy clustering measurements and cosmological parameter estimation. We first surveyed the \textit{Euclid} processing pipeline to identify all evident, potential sources of systematics, and classified them into two broad classes: angular systematics, which modulate the galaxy number density across the sky, and catastrophic redshift errors, which lead to interlopers in the galaxy sample. We then used simulated spectroscopic surveys to test our ability to mitigate angular systematics by constructing a random catalogue that represents the `visibility mask' of the survey; this is a dense set of intrinsically unclustered objects, subject to the same selection effects as the data catalogue. The construction of this random catalogue relies on a detection model, which gives the probability of reliably measuring the galaxy redshift as a function of the signal-to-noise ratio (S/N) of its emission lines. We demonstrate that, in the ideal case of a perfect knowledge of the visibility mask, the galaxy power spectrum in the presence of systematics is recovered, to within sub-per cent accuracy, by convolving a theory power spectrum with a window function obtained from the random catalogue itself. In the case of only approximate knowledge of the visibility mask, we test the stability of power spectrum measurements and cosmological parameter posteriors by using perturbed versions of the random catalogue. We find that significant effects are limited to very large scales, and parameter estimation remains robust; the most impacting effects are connected to the calibration of the detection model.

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