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L. Moscardini

Publications and source records attributed to L. Moscardini.

At least 37 records · Page 2Linked to original sources

AMICO galaxy clusters in KiDS-1000: Splashback radius from weak lensing and cluster-galaxy correlation function

We present the splashback radius analysis of the Adaptive Matched Identifier of Clustered Objects (AMICO) galaxy cluster sample in the fourth data release of the Kilo Degree Survey (KiDS). The sample contains 9049 rich galaxy clusters within $z\in[0.1,0.8]$, with shear measurements available for 8730 of them. We measure and model the stacked reduced shear, $g_{\rm t}$, and the cluster-galaxy correlation function, $w_{\rm cg}$, in bins of observed intrinsic richness, $λ^*$, and redshift, $z$. Building on the methods employed in recent cosmological analyses, we model the average splashback radius, $r_{\rm sp}$, of the underlying dark matter halo distribution, accounting for the known systematic uncertainties affecting measurements and theoretical models. By modelling $g_{\rm t}$ and $w_{\rm cg}$ separately, in the cluster-centric radial range $R\in[0.4,5]$ $h^{-1}$Mpc, we constrain $r_{\rm sp}$, the mass accretion rate, $Γ$, and the relation between $\mathcal{R}_{\rm sp}\equiv r_{\rm sp}/r_{200\rm m}$ and the peak height, $ν_{200\rm m}$, over the mass range $M_{200\rm m}\in[0.4,20]$ $10^{14}h^{-1}$M$_\odot$. The two probes provide consistent results that also agree with $Λ$-cold dark matter model predictions. Our $\mathcal{R}_{\rm sp}$ constraints are consistent with those from previous observations. For $g_{\rm t}$ and $w_{\rm cg}$, we achieve a precision of 14% and 10% per cluster stack, respectively. The higher precision of $w_{\rm cg}$, enabled by its combination with weak-lensing constraints on the mass-richness relation, highlights the complementarity of lensing and clustering in measuring $r_{\rm sp}$ and constraining the properties of the infalling material region.

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Euclid: Early Release Observations -- The formation of peanutty dwarf galaxies in Perseus

Dwarf galaxies in dense cluster environments are susceptible to tidal interactions that can alter their morphology and kinematics. Boxy isophotes are well studied in massive galaxies but remain poorly understood in dwarfs. We aim to identify and characterise boxy/peanutty dwarf galaxies in the Perseus cluster and determine the origin of their isophotal shapes. Using Euclid Early Release Observations of the Perseus cluster, we present a cumulative light fraction method for robustly measuring the isophotal shape parameter $c_4$, particularly suited to low surface brightness regimes. From ~1100 cataloged dwarfs, we select a clean sample of ~190 early-type systems with reliable $c_4$ measurement. Observed trends are interpreted through comparison with mock Euclid observations of $N$-body simulations of tidally transformed dwarfs. We identify 13 dwarfs with significantly boxy isophotes ($c_4 < -0.0175$). These galaxies lack visible thin disks, lie on the cluster red sequence, and show no preferential spatial concentration within Perseus. We find a significant anticorrelation between $c_4$ and effective radius: larger galaxies exhibit more boxy isophotes. An analogous size-shape anticorrelation is recovered in the simulations, where inner regions are dominated by box orbits associated with a triaxial peanut structure and outer regions by short-axis tube orbits. The boxy dwarfs in Perseus are tidally transformed remnants of moderately rotating progenitors, with boxy isophotes tracing inner box-orbit-dominated peanut structures. The size-shape correlation arises from viewing geometry: face-on orientations reveal the rectangular profile of the elongated triaxial structure (large and boxy), while edge-on views yield rounder, compact morphologies. Our sample represents an orientation-selected subset of tidally transformed, peanutty dwarfs in the cluster.

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Euclid preparation. Decomposing components of the extragalactic background light using multi-band intensity mapping cross-correlations

The extragalactic background light (EBL) fluctuations in the optical/near-IR encode the cumulative integrated galaxy light (IGL), diffuse intra-halo light (IHL), and high-$z$ sources from the epoch of reionisation (EoR), but they are difficult to disentangle with auto-spectra alone. We aim to decompose the EBL into its principal constituents using multi-band intensity mapping combined with cosmic shear and galaxy clustering. We develop a joint halo-model framework in which IHL follows a mass- and redshift-dependent luminosity scaling, IGL is set by an evolving Schechter luminosity function, and EoR emission is modelled with Pop II/III stellar emissivities and a binned star-formation efficiency. Using mock surveys in a flat $Λ$CDM cosmology with ten spectral bands spanning 0.75-5.0$\rm μm$ in the NEP deep fields over about 100$°^2$ with source detections down to AB=20.5 for masking, and six redshift bins to $z=2.5$, we fit auto- and cross-power spectra using a MCMC method. The combined SPHEREx$\times$Euclid analysis recovers all fiducial parameters within 1$σ$ and reduces 1$σ$ uncertainties on IHL parameters by 10-35% relative to SPHEREx EBL-only, while EoR star-formation efficiency parameters improve by 20-35%. Cross-correlations reveal a stronger coupling of IHL than IGL to the shear field, enhancing component separation; conversely, the EoR contribution shows negligible correlation with cosmic shear and galaxy clustering, aiding its isolation in the EBL. Relative to the SPHEREx EBL-only case, the inferred IHL fraction as a function of halo mass is significantly tightened over $10^{11}-10^{14} M_{\odot}$, with uncertainties reduced by 5-30%, and the resulting star-formation rate density constraints extend to $z\sim 11$, with uncertainty reductions of 22-31%.

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Deep Learning galaxy cluster's structural parameters from Weak Lensing observations

Galaxy clusters are the most massive gravitationally bound structures in the Universe and key probes of cosmic evolution. The large data volume expected from upcoming surveys requires efficient automated analysis methods for tens of thousands of clusters. We present a study using Convolutional Neural Networks (CNNs) to infer cluster structural parameters from weak gravitational lensing observations. Three architectures (VGG-Net, Inception-v4, Inception-ResNet-v2) were implemented in PyTorch and trained on 75,000 synthetic reduced shear maps generated with MOKA, simulating galaxy clusters at $z = 0.25$. The networks simultaneously predict five parameters: virial mass, NFW concentrations, substructure count, and smooth component mass fraction. Tests on 5000 clusters show high accuracy for primary properties. With realistic noise ($n_{\rm gal}=30$, $σ_ε=0.3$), mass predictions remain robust (RMS $\sim 1.02 \times 10^{14}$ M$_\odot$/h, $\sim20$% deviation). Concentration estimates are stable, with VGG-22 achieving the lowest RMS. Substructure count properties are more challenging, with systematic underestimation across models, while the smooth component mass fraction is consistently well recovered, indicating strong robustness against noise. Comparison with traditional shear profile fitting shows improved CNN performance. VGG-22 achieves near-unbiased mass estimates and significantly better concentration recovery, reducing systematic errors. These results demonstrate that CNNs provide an effective and scalable alternative to traditional methods, particularly suited for large survey datasets.[Abridged]

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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-Sérsic 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-Sérsic morphology, and the trained double-Sérsic 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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Euclid: Asteroid rotation periods from the Euclid Ecliptic Survey

The Euclid Ecliptic Survey was conducted during the calibration phase of the mission, 23-31 December 2023, as a campaign to study Solar System objects. We used data from this survey to analyse more than 23 000 appeareances of 2321 known asteroids. Due to their high apparent angular motion relative to the background stars (5-$60^{\prime\prime}\,\mathrm{h}^{-1}$), these objects appear as streaks in VIS long-exposure images. We set out to estimate their spin periods, since only $7\%$ of them have periods published in the literature. We used multiple apertures along each streak to increase the time resolution of our light curves. Our method combines a Lomb-Scargle approach with a Markov chain Monte Carlo (MCMC) algorithm to characterise the posterior distributions. Some asteroids show multimodality in the MCMC search, indicating period aliases; in these cases, we report all aliases and their likelihoods. We validate our pipeline by comparing our fitted periods with 48 published periods, including period harmonics. We find that $44\%$ of our periods are within $1\%$ of those published and $98\%$ are within $15\%$, and we establish that with $98\%$ confidence the best solution can be found among the first three aliases. All reliable periods reported agree with our current understanding of the spin-period distribution for asteroids. We find 16 periods below the spin barrier of 2.2 h with absolute magnitudes below 19, and thus 16 candidate super-fast rotators. We provide light curves for all 2321 objects observed and 889 high-quality periods in an open-access catalogue. The asteroids with reported periods include five Mars crossers, four Cybeles, four Hildas, three Hungarias, and 877 asteroids in other regions of the main belt. Our results represent the first batch of spin periods extracted from Euclid light curves and include the first-ever period measurements for $93\%$ of the objects.

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Euclid: A blue galaxy population and a brightest cluster galaxy in the making in a $z\sim1.74$ MaDCoWS2 galaxy cluster candidate

We present an example cluster follow-up study with Euclid. Our target, a $z\sim 1.74$ candidate cluster nicknamed the 'Puddle', was initially discovered by the Massive and Distant Clusters of WISE Survey 2 as a $z_\mathrm{phot}\sim 1.65$ candidate cluster. It was also detected independently as a $z_\mathrm{phot}\sim 1.5$ candidate with the two cluster-finding algorithms in Euclid Quick Release 1 (Q1). A Keck MOSFIRE spectrum shows the brightest nucleus is at $z=1.74$ and is dominated by an active galactic nucleus. Our analysis focused on the galaxy population and the brightest cluster galaxy (BCG), and is based on Euclid and ancillary photometry. Compared to similar fields, we measured an overdensity of $110\pm 14$ galaxies with $H_\mathrm{E}\leq 22.25$ in a 2' radius around the BCG. About $18\pm 4$% of the completeness-corrected galaxy population is red, which is consistent with some clusters at $z>1.5$ but lower than others. Euclid imaging revealed that six or seven galaxies appear to be assembling to form the future BCG. Spectral energy distribution fitting suggests that the merging BCG has a stellar mass of $5.7\pm 0.3\times 10^{11}\,M_\odot$ and that it experienced a short burst of star formation $\sim 300\,$Myr ago. Its morphology and star-formation history suggest that the proto-BCG is a more evolved version of the merging core of SPT2349$-$56. These systems indicate that multiobject mergers might be a common BCG formation process. Assuming a similar density of mergers in the Euclid Wide Survey, we expect that Euclid will discover approximately 400 assembling BCGs by the end of its mission.

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Euclid preparation. LXXXIX. Accurate and precise data-driven angular power spectrum covariances

We develop techniques for generating accurate and precise internal covariances for measurements of clustering and weak-lensing angular power spectra. These methods have been designed to produce non-singular and unbiased covariances for Euclid's large anticipated data vector and will be critical for validation against observational systematic effects. We constructed jackknife segments that are equal in area to a high precision by adapting the binary space partition algorithm to work on arbitrarily shaped regions on the unit sphere. Jackknife estimates of the covariances are internally derived and require no assumptions about cosmology or galaxy population and bias. Our covariance estimation, called DICES (Debiased Internal Covariance Estimation with Shrinkage), first estimated a noisy covariance through conventional delete-1 jackknife resampling. This was followed by linear shrinkage of the empirical correlation matrix towards the Gaussian prediction, rather than linear shrinkage of the covariance matrix. Shrinkage ensures the covariance is non-singular and therefore invertible, which is critical for the estimation of likelihoods and validation. We then applied a delete-2 jackknife bias correction to the diagonal components of the jackknife covariance that removed the general tendency for jackknife error estimates to be biased high. We validated internally derived covariances, which used the jackknife resampling technique, on synthetic Euclid-like lognormal catalogues. We demonstrate that DICES produces accurate, non-singular covariance estimates, with the relative error improving by 33% for the covariance and 48% for the correlation structure in comparison to jackknife estimates. These estimates can be used for highly accurate regression and inference.

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

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

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Euclid preparation: LXXXVII. Non-Gaussianity of 2-point statistics likelihood: Precise analysis of the matter power spectrum distribution

We investigate the non-Gaussian features in the distribution of the matter power spectrum multipoles. Using the COVMOS method, we generate 100\,000 mock realisations of dark matter density fields in both real and redshift space across multiple redshifts and cosmological models. We derive an analytical framework linking the non-Gaussianity of the power spectrum distribution to higher-order statistics of the density field, including the trispectrum and pentaspectrum. We explore the effect of redshift-space distortions, the geometry of the survey, the Fourier binning, the integral constraint, and the shot noise on the skewness of the distribution of the power spectrum measurements. Our results demonstrate that the likelihood of the estimated matter power spectrum deviates significantly from a Gaussian assumption on nonlinear scales, particularly at low redshift. This departure is primarily driven by the pentaspectrum contribution, which dominates over the trispectrum at intermediate scales. We also examine the impact of the finiteness of the survey geometry in the context of the Euclid mission and find that both the shape of the survey and the integral constraint amplify the skewness.

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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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Star formation quenching precedes morphological transformation in COSMOS-WEB's richest galaxy groups

We analyzed the 25 richest galaxy groups in COSMOS-Web at z = 0.18-3.65, identified via the AMICO algorithm. These groups contain 20-30 galaxies with high (>75%) membership probability. Our study reveals both passive-density and active-density relations: late-type galaxies (LTGs) prefer higher central overdensities than early-type galaxies (ETGs) across all groups, and many massive LTGs exhibit colors typical of quiescent galaxies. We identify red sequences (RS) in 5 groups, prominently established at z < 1, with early emergence in the RS locus up to z ~ 2.2. This suggests group environments represent a transitional phase where star formation quenching precedes morphological transformation, contrasting with the classical morphology-density relation in rich clusters. In the central regions (~33 arcsec / 100 kpc from centers), we identified 86 galaxies: 23 (~27%) ETGs and 63 (~73%) LTGs. High-mass galaxies (M_star > 10^10.5 M_sun) undergo rapid quenching over ~1 Gyr, becoming predominantly spheroidal ETGs. This indicates morphological transformation accelerates in massive systems during peak cosmic star formation. Intermediate-mass galaxies (10^9 < M_star/M_sun < 10^10.5) show mild quenching, while low-mass galaxies (M_star < 10^9 M_sun) remain largely star-forming; here, environmental processes suppress star formation without destroying disks, suggesting group quenching operates on longer timescales than mass quenching. Overall, mass-dependent quenching dominates the high-mass end, while environment shapes lower-mass systems. The HLAGN fraction for both groups and field increases with redshift, peaking at z ~ 2, with groups consistently showing higher fractions. We suggest AGN feedback partially drives rapid quenching in high-mass galaxies, while mergers may trigger AGN activity.

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The AIDA-TNG project: 3D halo shapes

Context. The shapes of dark matter halos can be used to constrain the fundamental properties of dark matter. In standard Cold Dark Matter (CDM) cosmologies, halos are typically triaxial, with a preference for prolate configurations, particularly at low masses and high redshift. Aims. We focus on the characterization of total matter 3D shape in alternative dark matter models, such as Self-Interacting Dark Matter (SIDM) and Warm Dark Matter (WDM). These scenarios predict different structural properties due to collisional effects or the suppression of small-scale power. Methods. We measure the different halo component shapes - dark matter, stars and gas - at various radii from the center in the AIDA-TNG (Alternative Interacting Dark Matter and Astrophysics - TNG), which is a suite of high-resolution cosmological simulations built upon the IllustrisTNG framework. The intent is to systematically study how different dark matter models - specifically, SIDM and WDM - affect galaxy formation and the structure of dark matter halos, when realistic baryonic physics is also included. Results. SIDM models tend to produce rounder and more isotropic halos, especially in the inner regions, as a result of momentum exchange between dark matter particles. WDM halos are also slightly more spherical than their CDM counterparts, and are typically less concentrated. In all cases, the inclusion of self-consistent baryonic physics makes the central regions of all halos rounder, while still revealing clear distinctions among the various dark matter models. Conclusions. The general framework presented in this work, based on the 3D halo shape, can be useful to interpret multi-wavelength data analyses of galaxies and clusters.

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Euclid: Early Release Observations -- The star cluster systems of the Local Group dwarf galaxies IC 10 and NGC 6822

Star clusters are valuable indicators of galaxy evolution, offering insights into the buildup of stellar populations across cosmic time. Understanding intrinsic star cluster populations of dwarf galaxies is particularly important given their role in the hierarchical growth of larger systems. Using Euclid Early Release Observation data, we study star clusters in two star-forming dwarf irregulars in the Local Group, NGC 6822 and IC 10 [$M_\star \sim$ (1--4) $\times10^8 M_\odot$]. With Euclid, clusters are resolved into individual stars across the main bodies and haloes of both galaxies. Visual inspection of $I_E$ images uncovers 30 new cluster candidates in NGC 6822 and 16 in IC 10, from compact to extended clusters. We re-evaluate literature candidates, producing combined catalogues of 52 (NGC 6822) and 71 (IC 10) clusters with confidence-based classifications. We present homogeneous photometry in $I_E$, $Y_E$, $J_E$, $H_E$, and archival UBVRI data, alongside size measurements and properties from BAGPIPES SED fitting. Synthetic cluster injection shows our sample is $\sim 50$% complete to $M \lesssim 10^3 M_\odot$ for ages $\lesssim 100$ Myr, and to $M \lesssim 3\times10^4 M_\odot$ for $\sim 10$ Gyr. IC 10 has more young clusters than NGC 6822, extending to higher masses, consistent with its starburst nature. Both dwarfs host several old massive ($\gtrsim 10^5 M_\odot$) clusters, including an exceptional $1.3 \times 10^6 M_\odot$ cluster in NGC 6822's outskirts. In NGC 6822, we identify a previously undetected, old, extended cluster ($R_h = 12.4 \pm 0.11$ pc). Using well-defined criteria, we identify 11 candidate GCs in NGC 6822 and eight in IC 10. Both galaxies have high specific frequencies ($S_N$) but remain consistent with known GC scaling relations at low luminosity [abridged].

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Beyond Stage IV: Quasar and Galaxy Clustering and the Fundamental Physics of the 2040s

Stage IV galaxy surveys (DESI, 4MOST, MOONS, Euclid) are establishing precision constraints on cosmological parameters through baryon acoustic oscillations and redshift-space distortions, yet fundamental questions on neutrino masses, inflationary physics, and the nature of gravity remain beyond their reach. We present a science case for next-generation wide-field spectroscopic surveys targeting $1 < z < 6$ with simultaneous observations of thousands of galaxies, quasars, and emission-line galaxies. Such surveys would deliver transformative advances: (i) cosmological constraints on absolute neutrino masses ($Σm_ν\lesssim 0.015\,\mathrm{eV}$), three times more stringent than Stage IV, enabling resolution of the neutrino mass hierarchy; (ii) detection of primordial non-Gaussianity at the level of $f_{\mathrm{NL}} \sim 1$, probing multi-field inflation; (iii) measurements of structure growth $fσ_8(z)$ spanning cosmic time to constrain dark energy and test gravitational modifications. Achieving these goals requires revolutionary advances in spectroscopic multiplexing ($\mathcal{O}(1000)$ simultaneous spectra), sub-$2\times10^{-4}(1+z)$ redshift precision at scale, and field-level inference techniques exploiting higher-order clustering statistics. We demonstrate that the proposed Wide-field Spectroscopic Telescope concept provides a technically feasible and scientifically compelling path to unlock the physics of neutrinos, inflation, and gravity that will remain inaccessible to Stage IV surveys.

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

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

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