arXiv subjects

M. Moresco

Publications and source records attributed to M. Moresco.

At least 19 recordsLinked to original sources

arXiv2026

Euclid. A two-point correlation approach to diagnosing star-related systematics in the Euclid spectroscopic survey

The Euclid spectroscopic survey will measure galaxy clustering with unprecedented precision, requiring stringent control of observational and instrumental systematics. Star-related effects may contaminate spectroscopic images through photometric persistence and imperfect masking of stars. We characterized their impact on galaxy clustering analyses, focusing on angular features identifiable in the data. We used angular and spatial auto- and cross-correlation statistics. For galaxies, we used mock spectroscopic catalogues from the EuclidLargeMocks in a 330 deg2 region of the Euclid Wide Survey (EWS). For stars, we used Gaia and 2MASS catalogues in the same area. To simulate photometric persistence, we implemented a simplified detector-level model calibrated on spectroscopic measurements and varied its strength to introduce different interloper fractions. For stellar masking, we modelled inconsistencies between the mask applied to the data and to the random catalogue. We measured star-star, galaxy-galaxy, and star-galaxy angular correlation functions using the Landy--Szalay estimator, and quantified deviations from the expected null star-galaxy correlation. We also evaluated the large-scale impact of such systematics through the three-dimensional two-point correlation function (2PCF). Photometric persistence produces a characteristic feature in the star-galaxy angular cross-correlation at scales of order 100", corresponding to the Euclid dithering pattern and grism dispersion geometry, and a spurious positive signal approximately constant up to 1{\deg}. Star-galaxy cross-correlation can detect residual persistence at contamination levels as low as 10% in a Data Release 1 spectroscopic catalogue. In contrast, stellar-mask mismatches produce strong small-scale angular signatures but have negligible impact on the large-scale 2PCF under realistic EWS conditions.

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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.

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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.

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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.

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arXiv2026

Euclid preparation. First investigation of the impact of cross-contamination on spectroscopic redshift measurements with pixel-level simulations

We present a study on simulated data focused on understanding the performance of the spectroscopic redshift measurements with the Near-Infrared Spectrometer and Photometer (NISP) instrument on Euclid. Simulations include scenarios with different levels of cross-contamination arising from overlapping spectra of nearby sources, which represents one of the main drawbacks of slitless spectroscopy. We present a new analysis based on pixel-level simulations of the NISP images, with the data processed using the Euclid spectroscopic pipeline. We first consider an idealised case with non-overlapping spectra to assess the accuracy and reliability of the redshift measurement as a function of the flux of the H-alpha emission line and galaxy size. We then introduce more realistic contamination scenarios, distinguishing between two contributions: contamination from H-alpha emitters, which are the Euclid targets for cosmological analyses, and contamination from all other galaxies. In the second case, we analyse the impact of cross-contamination with an increasing number of contaminants, from the brighter to the fainter galaxies. Given that our results show no clear evidence that sources fainter than magnitude 20 degrade redshift measurements, we conservatively restrict our analysis to galaxies with magnitudes up to 24. In particular, we provide a preliminary estimate that contamination from galaxies within the same redshift range as the target sample contributes to about 4% of the total degradation due to cross-contamination from all galaxies.

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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.

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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.

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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.

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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)

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arXiv2026

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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arXiv2026

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-S\'ersic 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-S\'ersic morphology, and the trained double-S\'ersic 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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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.

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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.

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arXiv2026

Euclid preparation. Simulated galaxy catalogues for non-standard cosmological models

Stage-IV galaxy surveys will provide the opportunity to test cosmological models and the underlying theory of gravity with unparalleled precision. In this context, it is crucial for the Euclid mission to leverage its spectroscopic and photometric probes to systematically investigate and incorporate non-standard cosmological models, including modified gravity, alternative dark energy scenarios, massive neutrinos, and primordial non-Gaussianity. We produce and release publicly simulated galaxy catalogues from a broad suite of non-standard cosmological simulations, which we processed through a model-independent analytical pipeline, making use of Rockstar for halo identification, and a modified version of the SciPic library for the galaxy-halo connection using the halo occupation distribution framework. We investigate their galaxy-clustering characteristics via the multipoles of the 2PCF in redshift space and VDG, a highly performant model for galaxy clustering. Across a wide range of models, the linear growth rate multiplied by the matter density within spheres of radius 12,Mpc, fs12, exhibits a notable robustness to the choice of cosmological template. Compared to previous works, our study extends this result to numerous scenarios with markedly distinct gravitational or dark energy dynamics. We find that the most of the scatter in cosmological parameter inference already appears when using the cosmological model of the simulations as templates. Using a `wrong' template can also introduce an additional scatter, although with smaller amplitude. Often, we find deviations much larger than error bars, meaning that the Gaussian approximation for the covariance might need to be further studied. Future cosmological investigations must broaden their scope to include a diverse array of non-standard theoretical frameworks, extending beyond LCDM and rudimentary dynamic dark energy models.

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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.

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arXiv2026

Euclid: An automated system to match Rubin transient alerts to Euclid observations

The Vera C. Rubin observatory is expected to produce 10 million transient alerts per night in ugrizy filters, whilst Euclid is a visible to near-infrared space telescope engaged in a wide field survey. We present a prototype system to automatically match the transient alerts from Rubin to Euclid observations. The system produces joint light-curves containing both visible and near-infrared photometry, and joint image cutouts. Using Zwicky Transient Facility alerts as a proxy for Rubin, we demonstrate the system in use in cases where Euclid did and did not detect the transient and highlight the value that can be added in each case. For transients detected by Euclid these benefits include identifying the supernovae (SNe) in observations taken prior to ground-based detection, thereby better constraining the explosion time, such as SN 2024pvw detected ~3 d prior to ground based detections. In cases where Euclid did not detect the transient, we demonstrate the benefit of adding Euclid observations to improve host morphology measurements and associations.

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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↗

arXiv2026

Euclid preparation. Galaxy 2-point correlation function modelling in redshift space

The Euclid satellite will measure spectroscopic redshifts for tens of millions of emission-line galaxies. In the context of Stage-IV surveys, the 3-dimensional clustering of galaxies plays a key role in providing cosmological constraints. In this paper, we conduct a model comparison for the multipole moments of the galaxy 2-point correlation function (2PCF) in redshift space. We test state-of-the-art models, in particular the effective field theory of large-scale structure (EFT), one based on the velocity difference generating function (VDG$_{\infty}$), and different variants of Lagrangian perturbation theory (LPT) models, such as convolutional LPT (CLPT) and its effective-field-theory extension (CLEFT). We analyse the first three even multipoles of the 2PCF in the Flagship 1 simulation, which consists of four snapshots at $z\in\{0.9,1.2,1.5,1.8\}$. We study both template-fitting and full-shape approaches and find that with the template-fitting approach, only the VDG$_{\infty}$ model is able to reach a minimum fitting scale of $s_{\rm min}=20\,h^{-1}\,{\rm Mpc}$ at $z=0.9$ without biasing the recovered parameters. Indeed, the EFT model becomes inaccurate already at $s_{\rm min}=30\,h^{-1}\,{\rm Mpc}$. Conversely, in the full-shape analysis, the CLEFT and VDG$_{\infty}$ models perform similarly well, but only the CLEFT model can reach $s_{\rm min}=20\,h^{-1}\,{\rm Mpc}$ while the VDG$_{\infty}$ model is unbiased down to $s_{\rm min}=25\,h^{-1}\,{\rm Mpc}$ at the lowest redshift. Overall, in order to achieve the accuracy required by Euclid, non-perturbative modelling such as in the VDG$_{\infty}$ or CLEFT models should be considered. At $z=1.8$, the CLPT model is sufficient to describe the data with high figure of merit. This comparison selects baseline models that perform best in ideal conditions and sets the stage for an optimal analysis of Euclid data in configuration space.

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