arXiv subjects

Euclid Collaboration

Publications and source records attributed to Euclid Collaboration.

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 preparation. The shape of halo profiles in $\Lambda$CDM and non-standard cosmologies

We study the shape of three-dimensional and projected dark-matter halo profiles extracted from cosmological $N$-body simulations in $\Lambda$CDM and non-standard cosmologies, using the \texttt{DUSTGRAIN-PF} and \texttt{DEMNUni} suites. The models considered include massive neutrinos, $f(\mathcal{R})$ gravity, and dynamical dark energy. By comparing density, mass, velocity-dispersion, and excess-surface-density profiles up to $5\,r_{500{\rm c}}$, we quantify the differential imprint of non-standard physics on halo structure in view of \textit{Euclid} cluster WL studies. Our main analysis is performed at $z=1.1$, a high-redshift regime where the weak-lensing signal-to-noise starts to degrade, providing a conservative stress test for detectability; for \texttt{DUSTGRAIN-PF} we additionally analyse $z=0.5$ and $z=0.3$ snapshots. In low-mass haloes ($M_{\rm 200c}<7\times10^{13}\,M_\odot$), $f(\mathcal{R})$ gravity produces deviations of order $10\,\%$ in projected and three-dimensional profiles, especially in the outskirts where screening is less efficient. Massive neutrinos partially reduce this signal, reflecting the competition between free streaming and fifth-force-enhanced growth. Dynamical dark energy and massive-neutrino cosmologies generally induce smaller, few-percent deviations, with the largest effects again found in low-mass haloes and at large radii. Under simplified assumptions for \Euclid WL, detecting such profile differences at $z=1.1$ requires stacks of $\sim10^5$ haloes, while a few thousands haloes may be sufficient at $z\lesssim0.5$. This further calls for the need of integrating such precise modelling of non-standard effects -- along with other observational effects -- in any likelihood involving \textit{Euclid} WL masses to avoid non-negligible systematic biases. Concentration--mass relations show weaker cosmology dependence, typically at the $\sim5\,\%$ level. [...]

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arXiv2026

Euclid Quick Data Release (Q1). Searching for radio-selected \Euclid-dark galaxies in the EDF-N

We present and investigate the properties of a sample of radio-selected, Euclid-dark galaxies, identified from LOFAR HBA observations at 144 MHz within the Euclid Deep Field-North (EDF-N). Starting from radio sources lacking optical counterparts in previous surveys, but detected with Spitzer/IRAC, we identified 166 galaxies with no emission at a more than $3\sigma$ level in Euclid Quick Release 1 (Q1) images, and no matches in the Euclid Q1 catalogue. To minimise contamination from nearby sources, we selected a sub-sample of 88 isolated galaxies. By exploiting multi-band images and catalogues available for the EDF-N, we inferred the physical properties of our sample via SED fitting. The resulting redshift distribution spans $0.4 \leq z_\mathrm{ph} \leq 5.0$. We used recent sub-arcsecond imaging from the International LOFAR Telescope to constrain the nature of the compact radio emission through brightness temperature estimates. By combining this information with the radio excess relative to the infrared/radio correlation (IRRC), we searched for possible active galactic nuclei (AGN) activity. Approximately 40% of our sources show evidence of AGN activity. The Euclid-dark sources detected in the far-infrared are consistent with a population of heavily obscured, massive star-forming galaxies with high star formation rates. Their location above the star-forming main sequence is consistent with similar near-infrared-dark galaxy populations reported in the literature. We also performed a UV-to-radio median stacking analysis, finding that the two subsamples exhibit similar global physical properties and differ primarily in their radio emission. These preliminary results indicate that the wide area covered by Euclid enables the identification of a higher fraction of systems in which intense star formation and AGN activity coexist, likely capturing a key phase of galaxy--black hole co-evolution.

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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): The geometry of dark matter halos from extragalactic streams

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

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arXiv2026

Euclid Quick Data Release (Q1): The impact of AGN emission on SED-derived physical properties

The Euclid Quick Data Release (Q1) is a powerful dataset to study active galactic nuclei (AGN) and their host galaxies. Deriving their physical properties through multi-component spectral energy distribution (SED) fitting is a challenging task for AGN, but it is greatly aided by the Euclid near-infrared photometry. Here we present a new method to quantify the reliability of SED-derived parameters, such as AGN bolometric and monochromatic luminosities, host's stellar mass $M_\star$, star-formation rate (SFR) and specific star-formation rate (sSFR), by using mock SEDs of AGN built by combining observed SEDs of QSOs and galaxies. We apply this methodology to the ${\sim}1$ million Q1 AGN candidates, constructing a catalogue of AGN and host galaxy properties, alongside their respective reliability values. With a reliability threshold at 0.5, we find 88\% of sources with robust stellar masses and 76\% with reliable AGN luminosities. Moreover, through SED fitting we also measure the AGN fraction $f_{\rm AGN}$ of the total mid-infrared flux and we use its lower-limit to select AGN. A $f_{\rm AGN, \, low} > 0.075$ threshold yields 85\% completeness and purity. Comparable to colour-colour AGN selections, this method has the advantage of being less affected by redshift evolution and exploring fainter magnitudes. Additionally, by comparing the AGN and host galaxy parameters across different identification methods, we find that the probed range in stellar mass and AGN luminosity can be quite different. This highlights the importance of combining different approaches and accounting for their selection biases when studying AGN and their role in galaxy evolution. Finally, for the X-ray detected sample, we present the X-ray to mid-IR luminosity relation, and the correlation between stellar mass and bolometric luminosity as a function of redshift, in good agreement with previous results.

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arXiv2026

Euclid preparation. Probing galaxy evolution within cosmic voids in Euclid-like simulations

The evolution of galaxies is profoundly influenced by the environment in which they reside. Cosmic voids serve as pristine laboratories for studying galaxy evolution in the relative absence of the complex physical processes that dominate denser environments. In this study, we investigate galaxy properties and merger histories as a function of environment using the GAlaxy Evolution and Assembly (GAEA) mock-observation lightcone replicating the Euclid Deep Survey as foreseen for the first Euclid data release. The H$\alpha$-selected galaxy sample spans the redshift range $0.4 < z < 1.8$, corresponding to the interval over which H$\alpha$ is accessible to Euclid slitless spectroscopy. We classify galaxies based on their void-centric distance and local density contrast, and compare their stellar mass, specific star formation rate, bulge-to-total stellar mass ratio, and halo mass across different environments. We further analyse the merger histories of these galaxies to study their assembly evolution. We find that galaxies located closer to void centres ($d_{\rm cc} \lesssim 0.7 R_{\rm v}$) are less massive, more actively star-forming, and more disc-dominated than galaxies in denser regions. Merger histories indicate that void galaxies do not experience fewer mergers, but rather that mergers occur later relative to galaxies in high-density regions. These results support a scenario in which the environment regulates the timing and nature of mergers rather than their overall frequency, producing a slower evolutionary path in low-density regions. We conclude by discussing the extent to which these trends are shaped by environmental parametrisation methods and observational selection effects. Our analysis provides a framework for interpreting forthcoming Euclid data and demonstrates Euclid's potential to identify cosmic voids and probe environmental effects on galaxy evolution.

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arXiv2026

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

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

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arXiv2026

\textit{Euclid} preparation. Baryon acoustic oscillations extraction techniques: comparison and optimisation

We present the first end-to-end validation of the Euclid baryon acoustic oscillation (BAO) analysis pipeline, encompassing density-field reconstruction, two-point correlation function measurement, and cosmological-parameter inference. Using eight Euclid-like mock catalogues from each of four Flagship I snapshots, designed to reproduce the expected statistical properties of the first Euclid data release (DR1), we assess the two standard BAO reconstruction methods based on the Zel'dovich approximation, RecSym and RecIso, across $0.9 \leq z \leq 1.8$. The pipeline introduces several methodological advances: an emulator-based model evaluator (Bora.jl) combined with a Hamiltonian Monte Carlo sampler (NUTS), achieving more than a 500-fold speed-up relative to standard Markov chain Monte Carlo, and a semi-analytical covariance estimator (BeXiCov+WinCov) that enables robust error estimates from only eight mock realisations while remaining stable under fiducial-cosmology variations. These components ensure computational efficiency while reducing the risk of underestimating parameter uncertainties. Both reconstruction schemes yield unbiased BAO measurements across all redshifts and analysis choices, including smoothing scale and fiducial cosmology. In each snapshot, reconstruction enhances the figure of merit for $\{\Omega_m, H_0 r_s\}$ by $\sim3$, equivalent to tripling the effective survey volume. Combining the four redshift bins, the improvement remains substantial, with BAO-only constraints reaching $\sim10\%$ precision on $\Omega_m$ and $\sim3\%$ on $H_0 r_s$. Results from RecSym and RecIso are consistent within uncertainties, though we recommend RecSym during testing due to its lower sensitivity to covariance variations. These findings establish the accuracy, robustness, and scalability of the Euclid BAO pipeline for DR1, providing a solid foundation for future cosmological analyses.

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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 Quick Data Release (Q1). AstroVink: A vision transformer approach to find strong gravitational lens systems

We present AstroVink, a vision transformer classifier designed for automated identification of strong lens candidates in Euclid imaging. We build upon the DINOv2 encoder, fine tuned to distinguish between lens and non-lens galaxies. Our base model, trained on simulated strong lens systems and labelled non lenses, recovers 88 of the 110 lens candidates within the top 500 ranked candidates, corresponding to an inspection efficiency of one lens per 5.7 inspected objects in our test set. After the Q1 data release, which yielded about 500 lens candidates, we retrained the model using high confidence lens candidates and new negatives, initially flagged as potential lenses by other classifiers but rejected during visual inspection. The retrained network further improves performance, achieving recovery of all 110 systems within the same ranking and reducing the inspection effort to one lens per 4.5 inspected objects, demonstrating that incorporating real examples significantly enhances model generalisation. An analysis of training subsets revealed that the inclusion of realistic negative examples played a key role in this improvement. Finally, we applied the retrained model to the Q1 original selection of 1.08M targets, followed by a new round of Space Warps citizen science inspection and expert vetting, where we identified a total of eight Grade A and 26 Grade B new lens candidates. These results demonstrate that transformer based architectures can recover strong lens candidates with high efficiency in real Euclid data, while substantially reducing the number of candidates requiring visual inspection.

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arXiv2026

Euclid: Scaled-up little red dots and other sources with v-shaped spectral energy distributions at z>4

Little Red Dots (LRDs) are some the most intriguing galaxy populations recently identified at z>~4 with JWST. They constitute the most extreme class of a more abundant population of sources with `V-shaped' spectral energy distributions (SEDs) and compact morphologies, which includes also Little Blue Dots (LBDs). Finding brighter analogues to these sources requires surveying sky areas which are significantly larger than those covered with JWST. Euclid deep images are ideally suited for this purpose. We make use of Euclid near-infrared images, complemented by Spitzer Infrared Array Camera (IRAC) data, over 0.75 sq. deg. of the COSMOS field to select a sample of 233 sources with `V-shaped' SEDs at z>4. Out of those, we identify 16 sources with compactness >1sigma above the median of all z>4 galaxies, which we consider robust LRD/LBD candidates in our sample. The stellar masses of these 16 sources are in the range 10^{8.5} - 10^{10.5} Msun, so they are significantly more massive than typical JWST-selected LRDs/LBDs. Interestingly, half of them are about as old as the Universe at their redshifts. In addition, we find that the median photometric properties of the Euclid LRDs/LBDs are similar to those of the so-called Blue Dust-Obscured Galaxies (Blue DOGs). Less than 10% of all our `V-shaped' SED sources, including only one of the Euclid LBDs, correspond to known AGN. The latter mostly constitute a population disjoint to the `V-shaped' SED sources. Spectroscopic follow up of the Euclid LRDs/LBD candidates remains necessary to probe whether they host BLAGN as fainter analogues do and whether constitute a transition phase from these fainter sources to standard AGN.

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arXiv2026

Euclid. Populating a dark universe with galaxies using SciPIC

High-fidelity galaxy mocks are crucial for validating analysis pipelines and for cosmological inference. In this context, the Science Pipeline at PIC (SciPIC) is a pipeline specifically designed for the fast generation of synthetic galaxy catalogues from the halo properties identified in cosmological simulations. SciPIC delivers galaxy catalogues that aim to reproduce the observed luminosity function and clustering above a given flux detection limit over a wide redshift range. In this work, we introduce SciPICal, an automated pipeline that calibrates the parameters that set the main mock galaxy properties, namely number density, luminosities, colours, and positions. The pipeline is applied to the Euclid Flagship 2 Wide and Deep halo catalogues, specifically built to support the \textit{Euclid} wide and deep surveys. Compared to the recently released Flagship 2 Wide mock, our calibrated version improves the clustering predictions by approximately 50\% based on chi-squared values. Furthermore, we produce the Euclid Deep mock catalogue, which reaches up to $z = 10$ by populating a light-cone and a complementary snapshot at $z = 0$. We validate these catalogues using measurements from spectroscopic and photometric galaxy surveys, as well as with results from a hydrodynamical simulation. The obtained good agreement (within $15\%$ for most of the samples) in the clustering predictions across the different galaxy samples considered, validates our calibration strategy and demonstrates the strong predictive power of the generated mocks. This pipeline will allow us to improve the methodology applied in assigning the galaxy properties and ensures that the galaxy mocks remain up-to-date by incorporating constraints from upcoming observational data in the calibration procedure.

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arXiv2026

Euclid Quick Data Release (Q1). AgileLens: A scalable CNN-based pipeline for strong gravitational lens identification

We present an end-to-end, iterative pipeline for efficient identification of strong galaxy--galaxy lensing systems, applied to the Euclid Q1 imaging data. Starting from VIS catalogues, we reject point sources, apply a magnitude cut (I$_E$ $\leq$ 24) on deflectors, and run a pixel-level artefact/noise filter to build 96 $\times$ 96 pix cutouts; VIS+NISP colour composites are constructed with a VIS-anchored luminance scheme that preserves VIS morphology and NISP colour contrast. A VIS-only seed classifier supplies clear positives and typical impostors, from which we curate a morphology-balanced negative set and augment scarce positives. Among the six CNNs studied initially, a modified VGG16 (GlobalAveragePooling + 256/128 dense layers with the last nine layers trainable) performs best; the training set grows from 27 seed lenses (augmented to 1809) plus 2000 negatives to a colour dataset of 30,686 images. After three rounds of iterative fine-tuning, human grading of the top 4000 candidates ranked by the final model yields 441 Grade A/B candidate lensing systems, including 311 overlapping with the existing Q1 strong-lens catalogue, and 130 additional A/B candidates (9 As and 121 Bs) not previously reported. Independently, the model recovers 740 out of 905 (81.8%) candidate Q1 lenses within its top 20,000 predictions, considering off-centred samples. Candidates span I$_E$ $\simeq$ 17--24 AB mag (median 21.3 AB mag) and are redder in Y$_E$--H$_E$ than the parent population, consistent with massive early-type deflectors. Each training iteration required a week for a small team, and the approach easily scales to future Euclid releases; future work will calibrate the selection function via lens injection, extend recall through uncertainty-aware active learning, explore multi-scale or attention-based neural networks with fast post-hoc vetters that incorporate lens models into the classification.

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arXiv2026

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

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

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