arXiv subjects

P. Fosalba

Publications and source records attributed to P. Fosalba.

At least 55 records · Page 3Linked to original sources

arXiv2026

Euclid Quick Data Release (Q1). The first Euclid view of Planck galaxy protocluster candidates at cosmic noon

[ABRIGED ABSTRACT] A large catalogue of candidate galaxy protoclusters with high star-formation rates was produced by the Planck collaboration. We search, in the first data release (Q1) of the Euclid survey, for the visible and infrared counterparts of the Planck galaxy protocluster candidates expected to be above $z > 1.5$. Eight of them are in Euclid Q1. Our goal is to investigate the optical nature of these overdensities previously detected in the submillimetre wavelength range. We search for overdensities using the DETECTIFz algorithm, an overdensity finder based on Delaunay tessellation that uses photometric redshift probability distributions through Monte Carlo simulations. Focusing our search on the eight high-star forming Planck protocluster candidates, we find that two of them have one Euclid counterpart, and six have between two and four Euclid counterparts, which amounts to a total of 20 Euclid counterparts. These Euclid counterparts lie at photometric redshifts $1.4<z_{\rm ph} < 2.7$ and 12 of them also have partial Herschel coverage. All detections have also been confirmed by at least one other independent protocluster detection algorithm. We study the colours, derived stellar masses and star-formation rates (SFRs) of the detected member galaxies of those protocluster candidate counterparts. We also estimate the total stellar masses, SFRs, and the halo mass lower limits for all Euclid protocluster candidates. We find that in the dark matter halo mass ($M_{\rm h}$) / redshift plane, these Planck and Euclid overdense regions lie in the region $12.6 <\log_{10} (M_{\rm h}/M_\odot)< 13.4$, $1.4<z< 2.7$. This means that the halos of our objects are expected to have experienced a transition between cold flows in hot media to accretion of hot material.

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arXiv2026

Euclid Quick Data Release (Q1). The Strong Lensing Discovery Engine F -- Bright and low-redshift strong lenses

We present 72 additional galaxy-galaxy strong lenses that complement the sample discovered in the Euclid Quick Release 1 data (63.1 deg^2) of the Strong Lens Discovery Engine (SLDE) papers A-E. It is shown that previous pre-selection of potential lenses, which excluded objects from the Gaia catalogue, led to missing several bright and low-redshift strong lenses, adding more than 10% new strong lens candidates compared to the previous search. In total, the catalogue includes 38 "grade A" (confident) and 34 "grade B" (probable) candidates. These lenses are identified through a combination of two independent searches for bright nearby objects: one based on machine-learning models followed by expert visual inspection, and the other based solely on expert visual inspection, targeting objects not included in the initial machine-learning selection (a limitation identified only after extensive visual inspection). With these additional strong lens candidates, we augment the expected number of high-confidence candidates in the Euclid Wide Survey from previous forecasts to 120000. Detailed semi-automated lens modelling confirms at least 41 systems out of 72, a fraction consistent with that found in SLDE A (315 out of 488). These include: multiple edge-on disc lenses; sources with arcs near the lens centre; "red sources"; and an edge-on disk galaxy lensing a galaxy merger, producing two sets of lensed features, an Einstein ring and a doubly imaged component. The median redshift of these systems is $Δ$ z ~ 0.3 lower than that of the SLDE A sample.

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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 $Ω_{\rm m}$ and the amplitude of the matter density fluctuations $σ_8$ - 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 $Λ$CDM cosmology, with $Ω_{\rm m} = 0.30711$ and $σ_8=0.8288$. 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 $Ω_{\rm m} = 0.307 \pm 0.003$ and $σ_8 = 0.826\pm 0.009$ (sample covariance), and $Ω_{\rm m} = 0.308 \pm 0.003$ and $σ_8 = 0.825 \pm 0.009$ (LC covariance). The posterior widths are the same, and the difference in the median values is less than $0.16\,σ$ for both parameters.

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arXiv2026

Euclid preparation. Galaxy power spectrum modelling in redshift space

Accurate modelling of redshift-space distortions (RSD) is essential for maximizing the cosmological information extracted from large galaxy redshift surveys. In preparation for the forthcoming analysis of the Euclid spectroscopic data, we investigate three approaches to modelling RSD effects on the power spectrum multipoles of mock H$α$ emission line galaxies. We focus on two one-loop perturbation theory models -- the effective field theory (EFT) and velocity difference generator (${\rm VDG_ \infty}$) -- which differ in their treatment of the real-to-redshift space mapping on small scales, and a third approach, the BACCO emulator, which adopts a hybrid strategy combining perturbation theory with high-resolution N-body simulations. We assess the ability of these models to recover key cosmological parameters, including the expansion rate $h$, the cold dark matter density parameter $ω_{\rm c}$, and the scalar amplitude $A_{\rm s}$, across four redshift bins spanning $0.9 \leq z \leq 1.8$. In each bin, we find that ${\rm VDG_ \infty}$ and BACCO outperform the EFT model across all scales up to $k_{max} \lesssim 0.35 h\,Mpc^{-1} $. While BACCO saturates in constraining power at intermediate scales and higher redshift, the ${\rm VDG_ \infty}$ model continues to improve parameter constraints beyond $k_{max} \gtrsim 0.30 h\,Mpc^{-1}$. The EFT model, although robust on large scales, exhibits significant parameter biases for $k_{max} \gtrsim 0.25 h\,Mpc^{-1}$, limiting its applicability to Euclid-like H$α$ samples. Among the full perturbation theory-based models, the enhanced treatment of small-scale RSD effects in ${\rm VDG_ \infty}$ improves cosmological parameter constraints by up to a factor of two.

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arXiv2026

Euclid Quick Data Release (Q1): Euclid spectroscopy of quasars. 1. Identification and redshift determination of 3500 bright quasars

The slitless spectroscopy mode of the NISP onboard Euclid has enabled efficient spectroscopy of objects within a large FoV. We present a large and homogeneous sample of bright quasars identified from the Euclid Quick Data Release (Q1) by combining high-purity candidate selections from Gaia and WISE with the NISP spectra. Through visual inspection of the Euclid spectra of these quasar candidates, we identify approximately 3500 quasars with reliable redshifts at $0<z\lesssim 4.8$. Of these, 2686 are new spectroscopic identifications relative to existing public compilations. We generate the first Euclid composite spectrum of quasars covering rest-frame NUV to NIR wavelengths without telluric lines, which will be pivotal to NIR quasar spectral analysis. We obtain an empirical spectroscopic depth of $J_{\rm E}\lesssim 21.5$ and $H_{\rm E}\lesssim 21.3$ at the sensitivity of the Wide Field Survey, beyond which the number of securely identified quasars declines sharply. We analyse VIS morphologies using Sersic and CAS metrics, and a deep-learning PSF fraction to track nuclear dominance. At low redshift ($z<0.5$), obvious host structures are common and a single Sersic model fits about half of the sources; at intermediate redshift ($0.5<z<2$), the nuclear component dominates, with 90% of the Sersic fits saturating at the upper index limit. In this intermediate redshift regime, $f_{\rm PSF}$ is available, and we use it as a more reliable compactness measure than the single-Sersic and CAS parameters to quantify nuclear versus host emission. We also explore the novel Euclid NIR colour space and discuss the role of these quasars in refining AGN selection techniques for future Euclid data releases. The spectroscopic bright quasar catalogue of this work, and the composite quasar spectrum, will be available at https://cdsarc.cds.unistra.fr/. (abridged)

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arXiv2026

Euclid: Discovery of bright $z\simeq7$ Lyman-break galaxies in UltraVISTA and Euclid COSMOS

We present a search for $z\simeq7$ Lyman-break galaxies using the $1.72 \, \rm{deg}^2$ near-infrared UltraVISTA survey in the COSMOS field, reaching $5\,σ$ depths in $Y$ of 26.2. We incorporate deep optical and Spitzer imaging for a full spectral energy distribution (SED) fitting analysis. We find 289 candidate galaxies at $6.5\leq z \leq 7.5$ covering $-22.6 \leq M_{\rm UV} \leq -20.2$, faint enough to overlap with Hubble Space Telescope studies. We conduct a separate selection by including complementary Euclid performance verification imaging (reaching $5\,σ$ depths of $26.3$), yielding 140 galaxies in $0.65 \, \rm{deg}^2$, with 38 sources unique to this sample. We compute the rest-frame UV luminosity function (UV LF) from our samples, extending below the knee ($M^*=-21.14^{+0.28}_{-0.25}$). We find that the shape of the UV LF is consistent with both a Schechter function and double-power law (DPL) at the magnitudes probed by this sample, with a DPL preferred at $M_{\rm UV}<-22.5$ when bright-end results are included. The UltraVISTA+Euclid sample provides a clean measurement of the LF due to the overlapping near-infrared filters identifying molecular absorption features in the SEDs of ultra-cool dwarf interlopers, and additional faint galaxies are recovered. A comparison with JWST LFs at $z>7$ suggests a gentle evolution in the bright-end slope, although this is limited by a lack of robust bright-end measurements at $z>9$. We forecast that in the Euclid Deep Fields, the removal of contaminant ultra-cool dwarfs as point sources will be possible at $J_{\rm E} < 24.5$. Finally, we present a high-equivalent-width Lyman-$α$ emitter candidate identified by combining HSC, VISTA, and Euclid broadband photometry, highlighting the synergistic power these instruments will have in the Euclid Auxiliary Fields for identifying extreme sources in the Epoch of Reionisation.

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arXiv2026

Dark Energy Survey Year 6 Results: Clustering-redshifts and importance sampling of Self-Organised-Maps $n(z)$ realizations for $3\times2$pt samples

This work is part of a series establishing the redshift framework for the $3\times2$pt analysis of the Dark Energy Survey Year 6 (DES Y6). For DES Y6, photometric redshift distributions are estimated using self-organizing maps (SOMs), calibrated with spectroscopic and many-band photometric data. To overcome limitations from color-redshift degeneracies and incomplete spectroscopic coverage, we enhance this approach by incorporating clustering-based redshift constraints (clustering-z, or WZ) from angular cross-correlations with BOSS and eBOSS galaxies, and eBOSS quasar samples. We define a WZ likelihood and apply importance sampling to a large ensemble of SOM-derived $n(z)$ realizations, selecting those consistent with the clustering measurements to produce a posterior sample for each lens and source bin. The analysis uses angular scales of 1.5-5 Mpc to optimize signal-to-noise while mitigating modeling uncertainties, and marginalizes over redshift-dependent galaxy bias and other systematics informed by the N-body simulation Cardinal. While a sparser spectroscopic reference sample limits WZ constraining power at $z>1.1$, particularly for source bins, we demonstrate that combining SOMPZ with WZ improves redshift accuracy and enhances the overall cosmological constraining power of DES Y6. We estimate an improvement in $S_8$ of approximately 10\% for cosmic shear and $3\times2$pt analysis, primarily due to the WZ calibration of the source samples.

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arXiv2026

Dark Energy Survey Year 3 results: Simulation-based $w$CDM inference from weak lensing and galaxy clustering maps with deep learning: Analysis design

Data-driven approaches using deep learning are emerging as powerful techniques to extract non-Gaussian information from cosmological large-scale structure. This work presents the first simulation-based inference (SBI) pipeline that combines weak lensing and galaxy clustering maps in a realistic Dark Energy Survey Year 3 (DES Y3) configuration and serves as preparation for a forthcoming analysis of the survey data. We develop a scalable forward model based on the CosmoGridV1 suite of N-body simulations to generate over one million self-consistent mock realizations of DES Y3 at the map level. Leveraging this large dataset, we train deep graph convolutional neural networks on the full survey footprint in spherical geometry to learn low-dimensional features that approximately maximize mutual information with target parameters. These learned compressions enable neural density estimation of the implicit likelihood via normalizing flows in a ten-dimensional parameter space spanning cosmological $w$CDM, intrinsic alignment, and linear galaxy bias parameters, while marginalizing over baryonic, photometric redshift, and shear bias nuisances. To ensure robustness, we extensively validate our inference pipeline using synthetic observations derived from both systematic contaminations in our forward model and independent Buzzard galaxy catalogs. Our forecasts yield significant improvements in cosmological parameter constraints, achieving $2-3\times$ higher figures of merit in the $Ω_m - S_8$ plane relative to our implementation of baseline two-point statistics and effectively breaking parameter degeneracies through probe combination. These results demonstrate the potential of SBI analyses powered by deep learning for upcoming Stage-IV wide-field imaging surveys.

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arXiv2026

Dark Energy Survey Year 6 Results: Cosmological Constraints from Cosmic Shear

We present legacy cosmic shear measurements and cosmological constraints using six years of Dark Energy Survey imaging data. From these data, we study ~140 million galaxies (8.29 galaxies/arcmin$^2$) that are 50% complete at i=24.0 and extend beyond z=1.2. We divide the galaxies into four redshift bins, and obtain cosmic shear measurement with a signal-to-noise of 83, a factor of 2 higher than the Year 3 analysis. We model the uncertainties due to shear and redshift calibrations, and discard measurements on small angular scales to mitigate baryon feedback and other small-scale uncertainties. We consider two fiducial models to account for the intrinsic alignment (IA) of the galaxies. We conduct a blind analysis in the context of the $Λ$CDM model and find $S_8 \equiv σ_8(Ω_m/0.3)^{0.5}=0.798^{+0.014}_{-0.015}$ (marginalized mean with 68% CL) when using the non-linear alignment model (NLA) and $S_{8} = 0.783^{+0.019}_{-0.015}$ with the tidal alignment and tidal torque model (TATT), providing 1.8% and 2.5% uncertainty on $S_8$. Compared to constraints from the cosmic microwave background from Planck 2018, ACT DR6 and SPT-3G DR1, we find consistency in the full parameter space at 1.1$σ$ (1.7$σ$) and in $S_8$ at 2.0$σ$ (2.3$σ$) for NLA (TATT). The result using the NLA model is preferred according to the Bayesian evidence. We find that the model choice for IA and baryon feedback can impact the value of our $S_8$ constraint up to $1σ$. For our fiducial model choices, the resultant uncertainties in $S_8$ are primarily degraded by the removal of scales, as well as the marginalization over the IA parameters. We demonstrate that our result is internally consistent and robust to different choices in calibrating the data, owing to methodological improvements in shear and redshift measurement, laying the foundation for next-generation cosmic shear programs.

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arXiv2026

Dark Energy Survey Year 6 Results: Cosmological Constraints from Galaxy Clustering and Weak Lensing

We present cosmology results combining galaxy clustering and weak gravitational lensing measured in the full six years (Y6) of observations by the Dark Energy Survey (DES) covering $\sim$5000 deg$^2$. We perform a large-scale structure analysis using three two-point correlation functions (3$\times$2pt): (i) cosmic shear from 140 million source galaxy shapes, (ii) galaxy clustering of 9 million lens galaxy positions, and (iii) galaxy-galaxy lensing from their cross-correlation. We model the data in flat $Λ$CDM and $w$CDM cosmologies. The combined analysis yields $S_8\equiv σ_8 (Ω_{\rm m}/0.3)^{0.5} = 0.789^{+0.012}_{-0.012}$ and matter density $Ω_{\rm m} = 0.333^{+0.023}_{-0.028}$ in $Λ$CDM (68\% CL), where $σ_8$ is the clustering amplitude. These constraints show a (full-space) parameter difference of 1.8$σ$ from a combination of cosmic microwave background (CMB) primary anisotropy datasets from Planck 2018, ACT-DR6, and SPT-3G DR1. Projected only into $S_8$ the difference is $2.6σ$. In $w$CDM the Y6 3$\times$2pt results yield $S_8 = 0.782^{+0.021}_{-0.020}$, $Ω_{\rm m} = 0.325^{+0.032}_{-0.035}$, and dark energy equation-of-state parameter $w = -1.12^{+0.26}_{-0.20}$. For the first time, we combine all DES dark-energy probes: 3$\times$2pt, SNe Ia, BAO and Clusters. In $Λ$CDM this combination yields a $2.8σ$ parameter difference from the CMB. When combining DES 3$\times$2pt with other low-redshift datasets (DESI DR2 BAO, DES SNe Ia, SPT clusters), we find a 2.3$σ$ parameter difference with CMB. A joint fit of Y6 3$\times$2pt, CMB, and those low-redshift datasets produces the tightest $Λ$CDM constraints to date: $S_8 = 0.806^{+0.006}_{-0.007}$, $Ω_{\rm m} = 0.302^{+0.003}_{-0.003}$, $h = 0.683^{+0.003}_{-0.002}$, and $\sum m_ν< 0.14$ eV (95\% CL). In $w$CDM, this combination yields $w = -0.981^{+0.021}_{-0.022}$.

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arXiv2026

Dark Energy Survey Year 6 Results: Galaxy-galaxy lensing

We present galaxy--galaxy lensing (GGL) measurements from the full six years of data from the Dark Energy Survey (DES Y6), covering $4031\,\mathrm{deg}^2$ and used in the DES Y6 $3\times2$pt cosmological analysis. We use the MagLim++ lens sample, containing $\sim 9$ million galaxies divided into six redshift bins, and the Metadetection source catalog, including $\sim 140$ million galaxies divided into four redshift bins. The mean tangential shear signal achieves a total signal-to-noise ratio (S/N) of $173$, corresponding to a $17\%$ improvement over DES Y3. After applying the scale cuts used in the cosmological analysis, with $R_{\min}=6\,\mathrm{Mpc}/h$ ($4\,\mathrm{Mpc}/h$) for the linear (nonlinear) galaxy-bias model, the S/N is reduced to $75$ (90). A comprehensive suite of validation tests demonstrates that the measurement is robust against observational and astrophysical systematics at the statistical precision required for the DES Y6 analysis. Although not used in the main cosmological analysis, we extract high--signal-to-noise geometric shear-ratio measurements from the galaxy--galaxy lensing signal on small angular scales. These measurements provide an internal consistency check on the photometric redshift distributions and shear calibration used in the $3\times2$pt analysis.

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arXiv2026

Euclid: An emulator for baryonic effects on the matter bispectrum

Understanding the impact of baryonic processes such as star formation and active galactic nuclei (AGN) feedback on matter clustering is crucial to ensure precise and unbiased cosmological inference. Most theoretical models of baryonic effects to date focus on two-point statistics, neglecting higher-order contributions. This work develops a fast and accurate emulator for baryonic effects on the matter bispectrum, a key non-Gaussian statistic in the nonlinear regime. We employ high-resolution $N$-body simulations from the BACCO suite and apply a combination of cutting-edge techniques such as cosmology scaling and baryonification to efficiently span a large cosmological and astrophysical parameter space. A deep neural network is trained to emulate baryonic effects on the matter bispectrum measured in simulations, capturing modifications across various scales and redshifts relevant to Euclid. We validate the emulator accuracy and robustness using an analysis of \Euclid mock data, employing predictions from the state-of-the-art FLAMINGO hydrodynamical simulations. The emulator reproduces baryonic suppression in the bispectrum to better than 2$\%$ for the $68\%$ percentile across most triangle configurations for $k \in [0.01, 20]\,\mathrm{i}h\mathrm{Mpc}^{-1}$ and ensures consistency between cosmological posteriors inferred from second- and third-order weak lensing statistics. These results demonstrate that our emulator meets the high-precision requirements of the Euclid mission for at least the first data release and provides reliable forecasts of the cosmological information contained in the small-scale matter bispectrum. This underscores the potential of emulation techniques to bridge the gap between complex baryonic physics and observational data, maximising the scientific output of Euclid.

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arXiv2026

Euclid preparation. 3D reconstruction of the cosmic web with simulated Euclid Deep spectroscopic samples

The ongoing Euclid mission aims to measure spectroscopic redshifts for approximately two million galaxies using the H $α$ line emission detected in near-infrared slitless spectroscopic data from the Euclid Deep Fields (EDFs). These measurements will reach a flux limit of $5\times 10^{-17}\,{\rm erg}\,{\rm cm}^{-2}\,{\rm s}^{-1}$ in the redshift range $0.4<z<1.8$, opening the door to numerous investigations involving galaxy evolution, extending well beyond the mission's core objectives. The achieved H $α$ luminosity depth will lead to a sufficiently high sampling, enabling the reconstruction of the large-scale galaxy environment. We assess the quality of the reconstruction of the galaxy cosmic web environment with the expected spectroscopic dataset in EDFs. The analysis is carried out on the Flagship and GAEA galaxy mock catalogues. The quality of the reconstruction is first evaluated using geometrical and topological statistics measured on the cosmic web, namely the length of filaments, the area of walls, the volume of voids, and its connectivity and multiplicity. We then quantify how accurately gradients in galaxy properties with distance from filaments can be recovered. As expected, the small-scale redshift-space distortions, have a strong impact on filament lengths and connectivity, but can be mitigated by compressing galaxy groups before skeleton extraction. The cosmic web reconstruction is biased when relying solely on H $α$ emitters. This limitation can be mitigated by applying stellar mass weighting during the reconstruction. However, this approach introduces non-trivial biases that need to be accounted for when comparing to theoretical predictions. Redshift uncertainties pose the greatest challenge in recovering the expected dependence of galaxy properties, though the well-established stellar mass transverse gradients towards filaments can still be observed.

astro-ph.GA↗

arXiv2026

Euclid preparation. Testing analytic models of galaxy intrinsic alignments in the Euclid Flagship simulation

We model intrinsic alignments (IA) in Euclid's Flagship simulation to investigate its impact on Euclid's weak lensing signal. Our IA implementation in the Flagship simulation takes into account photometric properties of galaxies as well as their dark matter host halos. We compare simulations against theory predictions, determining the parameters of two of the most widely used IA models: the Non Linear Alignment (NLA) and the Tidal Alignment and Tidal Torquing (TATT) models. We measure the amplitude of the simulated IA signal as a function of galaxy magnitude and colour in the redshift range $0.1<z<2.1$. We find that both NLA and TATT can accurately describe the IA signal in the simulation down to scales of $6$-$7 \,h^{-1}\,$Mpc. We measure alignment amplitudes for red galaxies comparable to those of the observations, with samples not used in the calibration procedure. For blue galaxies, our constraints are consistent with zero alignments in our first redshift bin $0.1 < z < 0.3$, but we detect a non-negligible signal at higher redshift, which is, however, consistent with the upper limits set by observational constraints. Additionally, several hydrodynamical simulations predict alignment for spiral galaxies, in agreement with our findings. Finally, the evolution of alignment with redshift is realistic and comparable to that determined in the observations. However, we find that the commonly adopted redshift power-law for IA fails to reproduce the simulation alignments above $z=1.1$. A significantly better agreement is obtained when a luminosity dependence is included, capturing the intrinsic luminosity evolution with redshift in magnitude-limited surveys. We conclude that the Flagship IA simulation is a useful tool for translating current IA constraints into predictions for IA contamination of Euclid-like samples.

astro-ph.CO↗

arXiv2026

Euclid preparation. Calibrated intrinsic galaxy alignments in the Euclid Flagship simulation

Intrinsic alignments of galaxies are potentially a major contaminant of cosmological analyses of weak gravitational lensing. We construct a semi-analytic model of galaxy ellipticities and alignments in the \Euclid Flagship simulation to predict this contamination in Euclid's weak lensing observations. Galaxy shapes and orientations are determined by the corresponding properties of the host haloes in the underlying $N$-body simulation, as well as the relative positions of galaxies within their halo. Alignment strengths are moderated via stochastic misalignments, separately for central and satellite galaxies and conditional on the galaxy's redshift, luminosity, and rest-frame colour. The resulting model is calibrated against galaxy ellipticity statistics from the COSMOS Survey, selected alignment measurements based on Sloan Digital Sky Survey samples, and galaxy orientations extracted from the Horizon-AGN hydrodynamic simulation at redshift $z=1$. The best-fit model has a total of 12 alignment parameters and generally reproduces the calibration data sets well within the $1σ$ statistical uncertainties of the observations and the \flagship simulation, with notable exceptions for the most luminous sub-samples on small physical scales. The statistical power of the calibration data and the volume of the single \flagship realisation are still too small to provide informative prior ranges for intrinsic alignment amplitudes in relevant galaxy samples. As a first application, we predict that \Euclid end-of-mission tomographic weak gravitational lensing two-point statistics are modified by up to order $10\,\%$ due to intrinsic alignments.

astro-ph.CO↗

arXiv2026

The PAU Survey: Measuring intrinsic galaxy alignments in deep wide fields as a function of colour, luminosity, stellar mass and redshift

We present the measurements and constraints of intrinsic alignments (IA) in the Physics of the Accelerating Universe Survey (PAUS) deep wide fields, which include the W1 and W3 fields from the Canada-France-Hawaii Telescope Legacy Survey (CFHTLS) and the G09 field from the Kilo-Degree Survey (KiDS). Our analyses cover 51deg$^{2}$, in the photometric redshift (photo-$z$) range $0.1 < z_{\mathrm{b}} < 1$ and a magnitude limit $i_{\mathrm{AB}}<22$. The precise photo-$z$s and the luminosity coverage of PAUS enable robust IA measurements, which are key for setting informative priors for upcoming stage-IV surveys. For red galaxies, we detect an increase in IA amplitude with both luminosity and stellar mass, extending previous results towards fainter and less massive regimes. As a function of redshift, we observe strong IA signals at intermediate ($z_{\mathrm{b}}\sim0.55$) and high ($z_{\mathrm{b}}\sim0.75$) redshift bins. However, we find no significant trend of IA evolution with redshift after accounting for the varying luminosities across redshift bins, consistent with the literature. For blue galaxies, no significant IA signal is detected, with $A_{1}=0.68_{-0.51}^{+0.53}$ when splitting only by galaxy colour, yielding some of the tightest constraints to date for the blue population and constraining a regime of very faint and low-mass galaxies.

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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