arXiv subjects

C. Padilla

Publications and source records attributed to C. Padilla.

At least 19 recordsLinked to original sources

arXiv2026

Euclid: Inferring star-formation history via cross-correlations of photometric clustering and shear with the cosmic infrared background

The cosmic infrared background, sourced by dust heated by star-forming activity, encodes the integrated history of the star-formation distribution over a large swathe of cosmic time. Decomposing the contribution from galaxies at different redshifts to the observed CIB maps provides a powerful tool for probing the large-scale star-formation history across cosmic times. To this end, we perform a forecast tomographic cross-correlation analysis using simulated photometric galaxy clustering and weak lensing data based on the Euclid mission survey specifications, combined with Planck CIB observations. The analysis adopts templates constructed from the halo occupation distribution model to measure the bias-weighted star-formation-rate density, $\langle b \rho_{\rm SFRD}\rangle$, as a function of redshift. We present forecasts for the $\langle b \rho_{\rm SFRD}\rangle$ constraints based on these simulations and quantify the expected constraining power using Fisher information matrix methods. Compared with results obtained using the same dataset as in previous works, we find that Euclid will tighten the constraints on $\langle b \rho_{\rm SFRD}\rangle$ across all redshift bins by a factor of about $2$ and provide more measurements over a deeper redshift range. This leads to improved constraints on all HOD parameters, typically reducing the marginalized uncertainties by a factor of about $2.5$, while also breaking parameter degeneracies.

astro-ph.CO↗

arXiv2026

Euclid: Measuring the intrinsic alignment of galaxies around cosmic voids in the \Euclid Flagship simulation\

We present a methodology to measure the intrinsic alignment (IA) signal of galaxies in the vicinity of cosmic voids using the \Euclid-like Flagship cosmological simulation from the Euclid Consortium. The IA signal is quantified and compared with the predictions of the linear alignment (LA) model, providing one of the first detailed investigations of this effect in underdense large-scale environments. While the IA signal around cosmic voids has received little attention to date, it may constitute a non-negligible systematic in forthcoming cosmological analyses that exploit void-lensing measurements. Our analysis examines red and blue galaxy populations separately, enabling a comparison of their alignment behaviour in void environments with the corresponding trends measured in galaxy-galaxy correlations. We find that the redshift evolution of the IA amplitude in cosmic voids is broadly consistent with that measured in the general galaxy population for both colour-selected samples. Additionally, our modelling allows us to estimate the linear bias of voids, $b_{\rm V}(z)$ which characterises how cosmic voids trace the underlying dark-matter density field, for voids with radii in the range $10 < R_{\rm V}/(h^{-1} {\rm Mpc}) < 15$. The measured bias exhibits a positive trend with redshift, consistent with theoretical predictions for the clustering of underdense regions. These results highlight the importance of accurately modelling IA in void studies, both to mitigate systematic effects in void-lensing cosmology and to further improve our understanding of galaxy-environment interactions in low-density regions of the Universe.

astro-ph.CO↗

arXiv2026

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, $\Delta z$, achieving a per-exposure precision of $\sigma(\Delta z) = 0.022\,\mu\text{m}$ 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$\,\mu\text{m}$, 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 $\left|\Delta R_\mathrm{PSF}^2/R_\mathrm{PSF}^2\right|<10^{-3}$ corresponds to field-averaged secondary mirror displacements exceeding $\langle \Delta z_\mathrm{thr}\rangle = (0.0683 \pm 0.0024)\,\mu\text{m}$. 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.

astro-ph.CO↗

arXiv2026

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 $\sigma_{NMAD}/(1+z)\!=\!0.011$ 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 $\sigma_{NMAD}/(1+z)\!=\!0.028$ 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 $\sigma_{NMAD}/(1+z)\!=\!0.011$ and outlier fractions below 4% for $i_{\rm AB}\!<\!23.5$.

astro-ph.CO↗

arXiv2026

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.

astro-ph.CO↗

arXiv2026

Euclid: Early Release Observations -- Internal kinematics and the convective-transition gap of NGC 6397

We present a 'multiple-pass' data-reduction tool designed for Euclid, based on software developed for the Hubble Space Telescope (HST), which improves the astrometric and photometric precision for faint sources and in crowded fields. In this work, we apply it to Euclid Early Release Observations of the Galactic globular cluster NGC 6397. By combining our new catalogue with archival HST data, separated by a time span of approximately 20 years, we were able to measure high-precision proper motions and investigate the radial variations in the energy equipartition and velocity anisotropy of the cluster. The combination of deep and wide-field observations also allowed us to derive the present-day local mass function of NGC 6397 and to study the radial dependence of mass segregation and binary fraction. Finally, we report the discovery of a subtle under-density of stars in the colour-magnitude diagram of NGC 6397 around a stellar mass of 0.35 M$_\odot$ with a more than 5$\sigma$ confidence level. This feature is consistent with the Gaia M-dwarf gap discovered in Galactic field stars, but it has never previously been observed in a globular cluster. The gap is caused by the onset of full convection in stellar interiors. We demonstrate that the properties of the gap provide tight constraints on the distance to NGC 6397 and its intrinsic metallicity dispersion, offering a new benchmark for stellar evolution models.

astro-ph.GA↗

arXiv2026

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.

astro-ph.GA↗

arXiv2026

Euclid preparation. CosmoPostProcess: A simulation calibrated framework for weak lensing selection bias in richness-selected galaxy clusters

We present \texttt{CosmoPostProcess}, a simulation-based forward-modelling algorithm calibrated to reproduce Euclid optical cluster observables. Its main deliverable is a correction for stacked surface-density profiles, binned in richness and redshift, accounting for selection systematics in richness-selected samples relative to unbiased references. We focus on the Euclid richness definition foreseen for cosmological analyses, which does not apply a colour selection; red-sequence richness is not considered. The algorithm processes $N$-body simulations by painting galaxies with a halo-occupation model and emulating survey detection and richness assignment. We also implement a novel estimate of optical cluster centres from projected galaxy densities, validated against Euclid pipelines. Baryonic effects are included through a correction calibrated on hydrodynamical simulations; the baryon-corrected excess surface density agrees within $2\,\%$ over $r\in[0.1,\,5]\,h^{-1}\,\mathrm{Mpc}$. Selection-bias contributions are assessed by varying cosmology and the mass--richness relation. Projection-induced selection bias follows a robust pattern: correlated large-scale structure projected along the line of sight enhances the stacked profile near the one-halo to two-halo transition, peaking at about $1\,h^{-1}\,\mathrm{Mpc}$ with an amplitude of $20\!-\!40\,\%$, depending on richness and redshift. The effect is mild at low and intermediate redshift ($z\lesssim0.7$), at the few-percent level, but becomes more relevant at higher redshift ($z\gtrsim0.7$). Baryonic modifications remain sub-dominant outside the core, at about $2\,\%$ beyond $r\gtrsim0.3\,h^{-1}\,\mathrm{Mpc}$. The framework delivers radial profile corrections with uncertainties, combining projection-induced selection bias, baryonic physics, and miscentring, to control systematics in Euclid DR1 cluster cosmology. (abridged)

astro-ph.CO↗

arXiv2026

Euclid preparation. Testing template-fitting models for the multipoles of the two-point clustering of galaxy clusters

The Euclid satellite will deliver a catalogue of optically selected galaxy clusters spanning from around 2000 deg$^2$ in Data Release (DR) 1 to around $14\,000$ deg$^2$ in DR3. In this work, we assess the validity of cluster clustering (CC) models for template-fitting, which complements the full-shape methodology by providing cosmological information from the anisotropy of the redshift-space two-point correlation function (2PCF). Both methods will be used to analyse the cluster 2PCF multipoles with Euclid. We examined the multipoles of the two-point redshift-space clustering of galaxy clusters simulated with the semi-analytic PINOCCHIO code using third-order Lagrangian perturbation theory, assuming a Euclid DR1-like footprint of 500 deg$^2$ in the northern hemisphere and 1400 deg$^2$ in the southern hemisphere. We estimated the first three even multipoles of the 2PCF and associated covariance matrix from 1000 DR1-like synthetic catalogues. We studied the impact of modelling the relevant non-linearities, halo bias, and photometric redshift uncertainties on the 2PCF. We applied three clustering models to the mock catalogues at 0 10^{14}\;h^{-1}\,M_\odot$ under realistic and optimistic photometric redshift uncertainty scenarios. We formulated a set of permissive and conservative criteria that ought to be fulfilled by the multipole cut-off scales and validated them against 100 mock catalogues via an inference of the growth rate multiplied by the matter power spectrum normalisation parameter, $f\sigma_8$. We tested the dispersion, Scoccimarro, and Taruya-Nishimichi-Saito models. We find that the dispersion model yields unbiased inferences on $f\sigma_8$ from CC down to 10 $h^{-1}$ Mpc in a DR1-like setting. All clustering models provide similar goodness-of-fit metrics in the presence of DR1-like cluster redshift uncertainties.

astro-ph.CO↗

arXiv2026

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.

astro-ph.CO↗

arXiv2026

Euclid: The linear-construction covariance and cosmology

We study the properties of galaxy cluster 2-point correlation function covariance matrices estimated using the linear-construction (LC) method, which is computationally up to 20 times faster than the standard sample-covariance method. Our goal is to assess how well the LC method performs in cosmological parameter estimation compared to the sample covariance. We use a set of 1000 mock dark matter halo catalogues to compute both the LC-covariance and the sample-covariance estimates in four redshift shells. These numerical matrices are used to fit a theoretical four-parameter model for the covariance. We then use the two fitted covariance models in a likelihood function to estimate two cosmological parameters - the matter density parameter $\Omega_{\rm m}$ and the amplitude of the matter density fluctuations $\sigma_8$ - from the simulated mock catalogues. The purpose of this is to validate the LC-covariance-based model against the sample-covariance model. The catalogues were simulated assuming the spatially flat $\Lambda$CDM cosmology, with $\Omega_{\rm m} = 0.30711$ and $\sigma_8=0.8288$. We find that the parameter posteriors obtained using the sample- and LC-covariance models agree well with each other and with the simulation cosmology. The two pairs of marginalized constraints are $\Omega_{\rm m} = 0.307 \pm 0.003$ and $\sigma_8 = 0.826\pm 0.009$ (sample covariance), and $\Omega_{\rm m} = 0.308 \pm 0.003$ and $\sigma_8 = 0.825 \pm 0.009$ (LC covariance). The posterior widths are the same, and the difference in the median values is less than $0.16\,\sigma$ for both parameters.

astro-ph.CO↗

arXiv2026

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 $\Lambda$CDM cosmology with ten spectral bands spanning 0.75-5.0$\rm \mu m$ in the NEP deep fields over about 100$\deg^2$ 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$\sigma$ and reduces 1$\sigma$ 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%.

astro-ph.CO↗

arXiv2025

\textit{Euclid}: From Galaxies to Gravitational Waves -- Forecasting Stochastic Gravitational Wave Background Anisotropies and Their Cross-Correlation

We estimate the amplitude and spatial anisotropy in the stochastic gravitational wave background (SGWB) energy density due to compact binary coalescence (CBC) events: binary black holes (BBH), binary neutron stars (BNS), and black hole-neutron star (BHNS) mergers. Our starting point is the Flagship Simulation Galaxy Catalogue developed by the Euclid Consortium. For each galaxy in the Catalogue, we use the simulated mass and starformation to constrain the galaxy's star-formation history, and predict its contribution to the gravitational-wave energy density through CBC mergers. Combining such contributions from all galaxies in the Catalogue results in a prediction for the frequency spectrum and spatial anisotropy of the CBC SGWB. We also compare this prediction to semi-analytical models of SGWB generated by compact binaries. We identify a set of effective parameters that capture the key features of these models, and we apply a Bayesian framework to infer these parameters assuming an ideal scenario of cosmic variance-limited search. This represents the first step toward developing a comprehensive framework that will eventually enable the correlation of SGWB anisotropy and \textit{Euclid} galaxy data, potentially allowing us to extract valuable astrophysical information from this new observable.

gr-qc↗

arXiv2025

Euclid preparation: The flat-sky approximation for the clustering of Euclid's photometric galaxies

We compare the performance of the flat-sky approximation and Limber approximation for the clustering analysis of the photometric galaxy catalogue of Euclid. We study a 6 bin configuration representing the first data release (DR1) and a 13 bin configuration representative of the third and final data release (DR3). We find that the Limber approximation is sufficiently accurate for the analysis of the wide bins of DR1. Contrarily, the 13 bins of DR3 cannot be modelled accurately with the Limber approximation. Instead, the flat-sky approximation is accurate to below $5\%$ in recovering the angular power spectra of galaxy number counts in both cases and can be used to simplify the computation of the full power spectrum in harmonic space for the data analysis of DR3.

astro-ph.CO↗

arXiv2025

Euclid: Methodology for derivation of IPC-corrected conversion gain of nonlinear CMOS APS

We introduce a fast method to measure the conversion gain in Complementary Metal-Oxide-Semiconductors (CMOS) Active Pixel Sensors (APS), which accounts for nonlinearity and interpixel capacitance (IPC). The standard 'mean-variance' method is biased because it assumes pixel values depend linearly on signal, and existing methods to correct for nonlinearity are still introducing significant biases. While current IPC correction methods are prohibitively slow for a per-pixel application, our new method uses separate measurements of the IPC kernel to make an almost instantaneous calculation of gain. Validated using test data from a flight detector from the ESA Euclid mission, the IPC correction recovers the results of slower methods within 0.1% accuracy. Meanwhile the nonlinearity correction ensures an estimation of the gain that is independent of signal, correcting a bias of more than 2.5% on gain estimation.

physics.ins-det↗

arXiv2025

Euclid: Quick Data Release (Q1) -- Watching ICM-selected galaxy clusters with Euclid eyes -- prospects of Euclid data in the context of large SZ and X-ray based surveys

Galaxy clusters detected through their X-ray emission or Sunyaev--Zeldovich effect (SZE), both produced by the intra-cluster medium (ICM), are key probes in cosmological and astrophysical studies. To maximise the scientific return of such surveys, complementary data are required for cluster confirmation and redshift estimation. This is typically provided by wide-field optical and infrared surveys, which are increasingly challenged by ongoing and future ICM-selected samples. In particular, at high redshifts ($z>1$) probed by upcoming SZE-selected samples, current large surveys may be insufficient for reliable confirmation. Deep, high-resolution infrared surveys like Euclid will thus be essential for confirming most high-redshift clusters. We present an analysis of the first sizeable Euclid dataset (Q1), overlapping with several ICM-selected cluster samples. We apply an adaptation of the MCMF cluster confirmation tool to estimate key properties, including redshift and richness, and to predict Euclid's capabilities for high-redshift cluster confirmation. We find promising performance, particularly at high redshifts, while richness estimates at low redshifts ($z<0.4$) are currently limited by Q1 data quality but should improve with future releases. Using MCMF runs on random lines of sight, we predict that Euclid will confirm clusters at $1<z<2$ as effectively as current optical surveys at $z<0.6$, significantly enhancing high-redshift confirmation. SZE-selected samples will thus greatly benefit from Euclid overlap. Among five known high-$z$ SZE clusters in Q1, we identify the highest-redshift jellyfish galaxy candidate to date, EUCLJ035330.86$-$504347.6 in SPT-CLJ0353$-$5043 ($z=1.32$), two massive star-forming galaxies near ACT-CLJ0350.0$-$4819 ($z=1.46$), and strong lensing features in SPT-CLJ0353$-$5043 and SPT-CLJ0421$-$4845.

astro-ph.CO↗

arXiv2025

Euclid preparation: The NISP spectroscopy channel, on ground performance and calibration

ESA's Euclid cosmology mission relies on the very sensitive and accurately calibrated spectroscopy channel of the Near-Infrared Spectrometer and Photometer (NISP). With three operational grisms in two wavelength intervals, NISP provides diffraction-limited slitless spectroscopy over a field of $0.57$ deg$^2$. A blue grism $\text{BG}_\text{E}$ covers the wavelength range $926$--$1366$\,nm at a spectral resolution $R=440$--$900$ for a $0.5''$ diameter source with a dispersion of $1.24$ nm px$^{-1}$. Two red grisms $\text{RG}_\text{E}$ span $1206$ to $1892$\,nm at $R=550$--$740$ and a dispersion of $1.37$ nm px$^{-1}$. We describe the construction of the grisms as well as the ground testing of the flight model of the NISP instrument where these properties were established.

astro-ph.IM↗

arXiv2025

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.

astro-ph.CO↗