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G. Mainetti

Publications and source records attributed to G. Mainetti.

At least 19 recordsLinked to original sources

Euclid Quick Data Release (Q1). Data processing for intracluster light measurements

The Euclid survey provides images with extraordinary potential for studies of the low-surface-brightness Universe, including intracluster light (ICL). However, to realise this promise, the data must be carefully treated to minimise background variations while preserving the signal from diffuse structures. In this work, we describe the post-processing and measurement procedures used for studies of ICL with Euclid. We demonstrate that we are able to substantially reduce background variations without resorting to a small-scale background subtraction. By injecting simulated clusters into the real images, we show that our approach preserves the faint outskirts of extended sources. On scales of several arcminutes, we can reliably detect surface-brightness levels around 27.5 mag arcsec$^{-2}$ in $Y_\textrm{E}$, $J_\textrm{E}$, $H_\textrm{E}$, and 29 mag arcsec$^{-2}$ in $I_\textrm{E}$. As a result, we can obtain accurate measurements of the ICL in individual clusters from the local Universe out to z~0.8 with uncertainties on the order of 10% in surface brightness, 10 degrees in position angle, and 0.1 in ellipticity. Our ability to measure the diffuse light with Euclid is thus set to meet expectations and revolutionise our understanding of the ICL.

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Euclid Quick Data Release (Q1). A systematic study of the intracluster light fraction at 0.2 < z < 1.5

We present a homogeneous analysis of the intracluster light (ICL) in approximately 300 galaxy clusters spanning $0.2 10^{10}\,M_\odot$). The inferred ICL fraction also depends systematically on wavelength, while remaining largely insensitive to the adopted outer integration radius of 200-600 kpc. These results highlight the importance of homogeneous ICL analyses and constrain the evolution of diffuse stellar components in clusters.

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Euclid Bypass end-to-end simulations for spectroscopic galaxy clustering performance assessment

We present a simulation framework for Euclid galaxy clustering measurements that reproduces the essential behaviour of the spectroscopic reduction chain, bypassing the computation required by full pixel-level simulations. The framework comprises two complementary tools, FastSpec, which simulates 1-dimensional slitless spectra with a simplified instrument and noise model, and Pypelid, which computes detection probabilities on input catalogues, accounting for the survey dithering sequence and spatially varying noise. We develop calibrated prescriptions for the survey selection function, redshift errors, and redshift interloper populations. Applied to the Euclid Wide Survey, the baseline selection yields a redshift purity of 74% and a sample completeness of 45%, which improves with the use of Euclid photometric colours. The redshift error distribution is found to have a Gaussian core of width $σ_z = 9.4 \times 10^{-4}$, with no significant trend over $0.9 < z < 1.8$. Emission lines [OIII]5008 and [SIII]9530 misidentified as H$α$ contribute a few to ten per cent depending on redshift, while catastrophic redshift measurement failures dominate at low signal-to-noise ratio. Simulating the Data Release 1 footprint, we find that complex survey selection effects can be corrected with a forward-modelled random catalogue, recovering the monopole and quadrupole of the galaxy 2-point correlation function. The simplified noise model does not include residual contamination from overlapping spectra, or other artefacts seen in early Euclid data; this will be revisited with DR1 data. The framework provides an efficient route for characterising the Euclid spectroscopic selection function at the precision required for galaxy clustering science, and is the basis for systematic error assessments in Euclid galaxy clustering analyses.

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Euclid: Impact of halo mass-conversion model assumptions on galaxy cluster number-count analyses

The large catalogues of galaxy clusters expected from the Euclid survey will enable cosmological analyses of cluster number counts that require accurate cosmological model predictions. One possibility is to use parametric fits calibrated against $N$-body simulations, that capture the cosmological parameter dependence of the halo mass function. Several studies have shown that this can be obtained through a calibration against haloes with spherical masses defined at the virial overdensity. In contrast, if different mass definitions are used for the HMF and the scaling relation, a mapping between them is required. Here, we investigate the impact of such a mapping on the cosmological parameter constraints inferred from galaxy cluster number counts. Using synthetic data from $N$-body simulations, we show that the standard approach, which relies on assuming a concentration-mass relation, can introduce significant systematic bias. In particular, depending on the mass definition and the relation assumed, this can lead to biased constraints at more than 2$σ$ level. In contrast, we find that in all the cases we have considered, the mass conversion based on the halo sparsity statistics result in a systematic bias smaller than the statistical error.

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Euclid preparation CIX. Baryon acoustic oscillation analysis of photometric galaxy clustering in configuration space

With about 1.5 billion galaxies expected to be observed, the very large number of objects in the Euclid photometric survey will allow for precise studies of galaxy clustering from a single survey, over a large range of redshifts $0.2 < z < 2.5$. In this work, we use photometric redshifts to extract the baryon acoustic oscillation signal (BAO) from the Flagship galaxy mock catalogue with a tomographic approach to constrain the evolution of the Universe and infer its cosmological parameters. We measured the two-point angular correlation function in 13 redshift bins. A template-fitting approach was applied to the measurement to extract the shift of the BAO peak through the transverse Alcock-Paczynski parameter $α$. A joint analysis of all redshift bins was performed to constrain $α$ at the effective redshift $z_\mathrm{eff}=0.77$ with MCMC and profile likelihood techniques. We also extracted one $α_i$ parameter per redshift bin to quantify its evolution as a function of time. From these 13 $α_i$, which are directly proportional to the ratio $D_\mathrm{A}/r_\mathrm{d}$, we constrain the product $h\,r_\mathrm{d}$ and $Ω_\mathrm{m}$. From the joint analysis, we constrain $D_\mathrm{A}/r_\mathrm{d}=10.764^{+0.0839}_{-0.0849}$, a three-fold improvement over current constraints from the Dark Energy Survey. As expected, the constraining power in the analysis of each redshift bin is lower, with an uncertainty ranging from $\pm\,1.23$ to $\pm\,0.289$. From these results, we constrain $Ω_\mathrm{m}=0.296^{+0.074}_{-0.059}$ and $h\,r_\mathrm{d}=99.35^{+4.29}_{-4.55}\,\mathrm{Mpc}$. We quantify the influence of analysis choices such as the template, scale cuts, redshift bins, and systematic effects such as redshift-space distortions, over our constraints, both at the level of the extracted $α_i$ parameters and at the level of cosmological inference.

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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.

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Euclid Quick Data Release (Q1): Disc breaks highlight the structural evolution of galaxies through time

Changes in the slope of the radial surface brightness profiles of disc galaxies, or disc breaks, encode valuable information about the processes driving disc formation and growth. Until now, due to the resolution and depth required, statistical studies of break types have been limited mostly to the local Universe. We aim to study the structural properties and redshift evolution of disc breaks in a large and statistically representative sample of galaxies out to redshift z=1 using the superb depth and resolution of Euclid. We develop an automatic pipeline to extract and analyse surface brightness profiles of 8748 disc galaxies selected from the Euclid Q1 dataset. The pipeline includes advanced masking, surface brightness profile extraction, integrated photometry and structural parameter measurements, and piecewise modelling to classify galaxies into Types I (pure exponential), Type II (down-bending), Type III (up-bending), and composite break (e.g., Type~II+III, Type~II+II, etc) profiles. We quantify structural parameters such as scale lengths, break radii, and surface brightness levels, and analyse their distributions and redshift dependence. Our automatic method produces reliable masks and deep surface brightness profiles, and classifies galaxy profiles with an estimated accuracy of 70%. Using a subsample of 4385 galaxies with reliable classifications, we find that the most common profiles are Types II, II+III, I, and III. We find substantial evolution in the fraction of disc breaks with time. Type II profiles dominate at low redshift (50%), while Types III and II+III profiles increase in frequency with lookback time, reaching 30% each at z~1. Our study provides the first statistically robust measurement of the evolution of disc break types over 5 Gyr. The observed trends support a scenario in which secular processes replace environmental influences as galaxies mature.

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Euclid: Quick Data Release (Q1) -- Optical hotspots in powerful radio galaxies

The hotspots of powerful radio galaxies are the sites of high-energy particle acceleration, but radio observations give us limited information on the electron energy distributions that they generate, which affects our overall understanding of their physics and energetics. Optical synchrotron counterparts to radio galaxy hotspots, which probe high electron energies, have been known for many years, but have only been studied in a small number of objects selected as being very bright in the radio. By combining Low-Frequency Array (LOFAR) observations with the Euclid Q1 data release in the Euclid Deep Field North, we identify 77 powerful radio galaxies with hotspots and show that a small but significant fraction of them, 7--15\%, may have detected infrared and optical counterparts to their hotspots. The hotspot spectral energy distributions in our clearest cases are consistent with particle acceleration up to (but not beyond) 1\,TeV in energy on the assumption of field strengths close to equipartition, whereas non-detected hotspots either do not reach such high electron energies or would have to have very different electron energy spectra or significantly sub-equipartition magnetic field strengths. Two new candidate optical hotspots are clearly detected matching high-resolution LOFAR data; one is remarkable as both the highest-redshift optical hotspot known to date ($z \approx 1.6$) and also the first optical detection of the hotspot of the inner lobe of a restarting source. We discuss approaches to performing a large-scale study of hotspots with the full wide-area Euclid surveys, particularly when combined with the international baselines of LOFAR, enabling for the first time a statistical analysis of high-energy particle acceleration in hotspots.

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Euclid Quick Data Release (Q1) Euclid spectroscopy of quasars. 2. Physical properties from spectral fitting

A substantial volume of spectroscopic data has become available with the Euclid Data Release (Q1), which represents a unique opportunity to study quasars (QSOs) in the Euclid Deep Fields, provide spectroscopic measurements, and estimates of their physical properties. We present results from a spectroscopic analysis of QSOs with HE < = 22.5 using Q1. We use external catalogues from surveys such as the Dark Energy Spectroscopic Instrument (DESI), Gaia, Wide-field Infrared Survey Explorer (WISE), and the QUasars as BRIght beacons for Cosmology in the Southern hemisphere (QUBRICS) for the QSO selection and redshift determination, totaling 5489 QSOs. We provide measurements of the line fluxes, full widths at half-maximum, and respective uncertainties for the emission lines of Euclid spectra based on fitting statistica and signal-to-noise ratio (S/N). Of the total 5489 QSOs, 5387 are successfully fitted. We find that 45% of the total number of successfully fitted spectra are free of problematic artefacts allowing for trustworthy measurements. Our final Euclid QSO sample spans a redshift range of 0.01 < = z < = 4.8 and shows a median spectral index of αλ = - 1.17. Finally, we estimate black hole masses with single epoch methods for 1213 sources, using the He I λ10830, Pa β, H α, H β, and Mg II emission lines, obtainning a mean logarithmc mass of log10 (MBH / Msolar) = 8.7 and mean Edigton ratio of λEdd = 0.34. The catalogue with the physical properties of this sample together with the software developed for the analysis is available online for scientific exploitation.

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Euclid: Quick Data Release (Q1) -- Exploring the detailed visual morphology of galaxies in clusters

Galaxy clusters provide unique laboratories for studying environmental effects on galaxy evolution. The morphology--density ($T$--$Σ$) and morphology--cluster-centric radius ($T$--$R$) relations trace how galaxy morphology is influenced by the environment, but previous studies at intermediate redshifts have been limited in both sample size and radial coverage. We use the Euclid Quick Data Release 1 (Q1) visual morphology catalogue to measure the $T$--$Σ$ and $T$--$R$ relations for smooth, featured-or-disc, and barred galaxies in known clusters at $0.2\leq z\leq 0.5$, extending this analysis to large cluster-centric distances ($3 R_{500c}$) and studying their dependence on stellar mass. Using photometric redshifts and stellar masses provided by Euclid, we identify 1754 cluster members within $1.5 R_{500c}$, distributed across 71 clusters. We classify the identified galaxies as smooth, featured-or-disc, or barred using the predicted vote fractions provided by the Zoobot deep learning foundation model in the Q1 visual morphology catalogue. We confirm the $T$--$Σ$ relation in all the stellar mass ranges studied, with a stronger influence of the cluster environment on galaxy morphology in the densest parts of the cluster and closer to the cluster centre. Beyond $1.5 R_{500c}$, the morphological segregation weakens, with featured-or-disc galaxies overtaking smooth galaxies at the lowest densities, consistent with the growing contribution of field interlopers in the cluster outskirts. For barred galaxies, we find a tentative decline of the bar fraction toward lower densities that is most pronounced for the most massive galaxies. In conclusion, our results show that the cluster environment drives a progressive transformation of galaxy morphology, with the loss of disc structure becoming more pronounced towards the cluster core, where environmental processes act most efficiently.

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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°. 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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Euclid preparation. The shape of halo profiles in $Λ$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 $Λ$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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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, $fσ_8$. We tested the dispersion, Scoccimarro, and Taruya-Nishimichi-Saito models. We find that the dispersion model yields unbiased inferences on $fσ_8$ 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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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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Euclid: Optimising tomographic redshift binning for 3$\times$2pt power spectrum constraints on dark energy

We present a simulation-based method to explore the optimum tomographic redshift binning strategy for 3x2pt analyses with Euclid, focusing on the expected configuration of its first major data release (DR1). To do this, we 1) simulate a Euclid-like observation and generate mock shear catalogues from multiple realisations of the 3x2pt fields on the sky, and 2) measure the 3x2pt Pseudo-Cl power spectra for a given tomographic configuration and derive the constraints that they place on the standard dark energy equation of state parameters (w0, wa). For a simulation including Gaussian-distributed photometric redshift uncertainty and shape noise under a LambdaCDM cosmology, we find that bins equipopulated with galaxies yield the best constraints on (w0, wa) for an analysis of the full 3x2pt signal, or the angular clustering component only. For the cosmic shear component, the optimum (w0, wa) constraints are achieved by bins equally spaced in fiducial comoving distance. However, the advantage with respect to alternative binning choices is only a few percent in the size of the $1\,σ\,$(w0, wa) contour, and we conclude that the cosmic shear is relatively insensitive to the binning methodology. We find that the information gain extracted on (w0, wa) for any 3x2pt component starts to saturate at $\gtrsim$ 7-8 bins. Any marginal gains resulting from a greater number of bins is likely to be limited by additional uncertainties present in a real measurement, and the increasing demand for accuracy of the covariance matrix. Finally, we consider a 5% contamination from catastrophic photometric redshift outliers and find that, if these errors are not mitigated in the analysis, the bias induced in the 3x2pt signal for 10 equipopulated bins results in dark energy constraints that are inconsistent with the fiducial LambdaCDM cosmology at $>5\,σ$.

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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, $\langle b ρ_{\rm SFRD}\rangle$, as a function of redshift. We present forecasts for the $\langle b ρ_{\rm SFRD}\rangle$ 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 $\langle b ρ_{\rm SFRD}\rangle$ 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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Euclid Quick Data Release (Q1). The average far-infrared properties of Euclid-selected star-forming galaxies

The first Euclid Quick Data Release contains millions of galaxies with excellent optical and near-infrared (IR) coverage. To complement this dataset, we investigate the average far-IR properties of Euclid-selected main sequence (MS) galaxies using existing Herschel and SCUBA-2 data. We use 17.6deg$^2$ (2.4deg$^2$) of overlapping Herschel (SCUBA-2) data, containing 2.6 million (240000) MS galaxies. We bin the Euclid catalogue by stellar mass and photometric redshift and perform a stacking analysis following SimStack, which takes into account galaxy clustering and bin-to-bin correlations. We detect stacked far-IR flux densities across a significant fraction of the bins. We fit modified blackbody spectral energy distributions in each bin and derive mean dust temperatures, dust masses, and star-formation rates (SFRs). We find similar mean SFRs compared to the Euclid catalogue, and we show that the average dust-to-stellar mass ratios decreased from z$\simeq$1 to the present day. Average dust temperatures are largely independent of stellar mass and are well-described by the function $T_2+(T_1-T_2){\rm e}^{-t/τ}$, where $t$ is the age of the Universe, $T_1=79.7\pm7.4$K, $T_2=23.2\pm0.1$K, and $τ=1.6\pm0.1$Gyr. We argue that since the dust temperatures are converging to a non-zero value below $z=1$, the dust is now primarily heated by the existing cooler and older stellar population, as opposed to hot young stars in star-forming regions at higher redshift. We show that since the dust temperatures are independent of stellar mass, the correlation between dust temperature and SFR depends on stellar mass. Lastly, we estimate the contribution of the Euclid catalogue to the cosmic IR background (CIB), finding that it accounts for >60% of the CIB at 250, 350, and 500$μ$m. Forthcoming Euclid data will extend these results to higher redshifts, lower stellar masses, and recover more of the CIB.

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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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