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R. J. Massey

Publications and source records attributed to R. J. Massey.

At least 37 records · Page 2Linked to original sources

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 $\propto f_{\rm NL} \, b_ϕ$ 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 $b_ϕ$ that yields unbiased $f_{\rm NL}$ while accounting for theory uncertainty, and determine scale cuts that give unbiased $Λ$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 $<1σ$ bias in $f_{\rm NL}$ and $Λ$CDM. At fixed cuts, $B_\ell$ alone reduces $σ({f_{\rm NL}})$ 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 $z=1.7$: $1.9σ$ for $f_{\rm NL} \, b_ϕ$ (prior-agnostic) and $2.35σ$ 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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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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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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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: Quick Data Release (Q1) -- Dual AGN in low-mass galaxies

Dual active galactic nuclei (AGNs) are expected in hierarchical galaxy evolution models, in which low-mass galaxies merge to build more massive ones. While observational evidence for dual AGNs is growing in massive galaxies, no clear detection has yet been found in the low-mass regime. We used photometry and spectroscopy from the first \Euclid Quick Data Release, combined with a collection of multi-wavelength data from the Dark Energy Spectroscopic Instrument (DESI), the LOw-Frequency ARray (LOFAR) high band antenna, and counterparts in X-ray and mid-infrared catalogues to identify dual AGNs at redshift $z \lesssim 1$. Focusing on low-mass galaxies with stellar masses below 10$^{10}$ M$_{\odot}$, we find nine dual AGN candidates with projected separations ranging from $\sim$20 to 51 kpc. We also find 49 dual AGN candidates in more massive galaxies. We derive a dual AGN fraction of 0.1\% for the low-mass galaxies and estimate that these systems likely trace a population of progenitor black hole pairs that may evolve into bound binaries and eventually coalesce, emitting gravitational waves in the LISA band. These results constitute the first sample of spectroscopically confirmed dual AGN candidates in low-mass galaxies and have important implications for models in which supermassive black holes grow from lower-mass black holes located in low-mass galaxies, as well as for predictions of gravitational waves from low-mass binary black holes.

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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. 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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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 preparation. Far-infrared predictions for Euclid galaxy catalogues: cluster, protocluster, and field

The MAMBO mock galaxy catalogue, based on the Millennium Simulation with empirically assigned galaxy properties, provides predictions of FIR fluxes and physical parameters of Euclid-detectable galaxies. Predicted FIR flux distributions confirm that only the brightest Euclid sources will be detectable in existing FIR surveys. We employ stacking to measure the mean dust properties as a function of stellar mass and redshift. We find dust temperatures and infrared luminosities increase with redshift across all mass bins, while dust masses remain roughly constant. FIR number counts from MAMBO show overall good agreement with observations, and the total infrared luminosity function reproduces published estimates across most redshift ranges, extending to z~10. Comparing the Euclid Wide and Deep Surveys, we find that the EDS recovers the total IRLF to fainter luminosities and higher redshifts (up to z~6 in $I_E$), although its detectability falls below 80% at z>4, whereas the EWS becomes strongly incomplete beyond z~2. We also examine the dependence of the IRLF on environment. Schechter fits indicate that the faint-end slope $α$ flattens with redshift for cluster and protocluster galaxies, while remaining approximately constant for field populations. Imposing additional detection limits from Herschel-PACS and SPIRE shows that only the most luminous ($L_{IR}$ > $10^{12.5}$ $L_{\odot}$) galaxies remain detectable at z~4, but the limited MAMBO area (3.14$deg^2$) is inadequate for statistically robust (>3$σ$) constraints. Survey areas at least 30 times larger are required. Overall, the MAMBO FIR extension reproduces key number count and IRLF trends, provides realistic predictions for FIR-detected Euclid galaxies, and highlights the importance of synergies with current and future FIR/sub-mm facilities to probe environmental dependence with sufficient depth and area.

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

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

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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. Properties and performance of the NISP signal estimator

The Euclid spacecraft, located at the second Lagrangian point of the Sun-Earth system, hosts the Near-Infrared Spectrometer and Photometer (NISP) instrument. NISP is equipped with a mosaic of 16 HgCdTe-based detectors to acquire near-infrared photometric and spectroscopic data. To meet the spacecraft's constraints on computational resources and telemetry bandwidth, the near-infrared signal is processed onboard via a dedicated hardware-software architecture designed to fulfil the stringent Euclid's data-quality requirements. A custom application software, running on the two NISP data processing units, implements the NISP signal estimator: an ad-hoc algorithm which delivers accurate flux measurements and simultaneously estimates the quality of signal estimation through the quality factor parameter. This paper investigates the properties of the NISP signal estimator by evaluating its performance during the early flight operations of the NISP instrument. First, we revisit the assumptions on which the inference of the near-infrared signal is based and investigate the origin of the main systematics of the signal estimator through Monte Carlo simulations. Then, we test the flight performance of the NISP signal estimator. Results indicate a systematic bias lower than 0.01 e/s for 99% of the NISP pixel array, well within the noise budget of the estimated signal. We also derive an analytical expression for the variance of the NISP signal estimator, demonstrating its validity, particularly when the covariance matrix is not pre-computed. Finally, we provide a robust statistical framework to interpret the QF parameter, analyse its dependence on the signal estimator bias, and show its sensitivity to cosmic ray hits on NISP detectors. Our findings corroborate previous results on the NISP signal estimator and suggest a leading-order correction based on the agreement between flight data and simulations.

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Euclid: Galaxy SED reconstruction in the PHZ processing function: impact on the PSF and the role of medium-band filters

Weak lensing surveys require accurate correction for the point spread function (PSF) when measuring galaxy shapes. For a diffraction-limited PSF, as arises in space-based missions, this correction depends on each galaxy SED. In the Euclid mission, galaxy SED reconstruction, a tasks of the photometric-redshift processing function (PHZ PF), relies on broad- and medium-band ancillary photometry. The limited wavelength sampling of the Euclid VIS passband and signal-to-noise ratio may affect the reconstruction accuracy and translate into biases in the weak lensing measurements. In this study, we present the methodology, which is employed in the Euclid PHZ PF, for reconstructing galaxy SEDs at 55 wavelengths, sampling the VIS passband every 10 nm, and we assess whether it fulfils the accuracy requirements imposed on the Euclid PSF model. We employ both physics- and data-driven methods, focusing on a new approach of template-based flux correction and Gaussian processes, and we introduce an SED metric whose bias propagates into PSF quadrupole moment errors. Our findings demonstrate that Gaussian processes and template fitting meet the requirements only in specific, but complementary, redshift intervals. We therefore propose a hybrid approach, which leverages both methods. This solution proves to be effective in meeting the Euclid accuracy requirements for most of the redshift range of the survey. Finally, we investigate the impact on the SED reconstruction of a new set of 16 evenly-spaced medium-band filters for the Subaru telescope, providing quasi-spectroscopic coverage of the VIS passband. This study shows promising results, ensuring accurate SED reconstruction and meeting the mission PSF requirements. This work thus provides not only the methodological foundation of galaxy SED reconstruction in the Euclid PHZ PF, but also a roadmap for future improvements using a new medium-band survey.

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

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

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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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Euclid Quick Data Release (Q1). From simulations to sky: Advancing machine-learning lens detection with real Euclid data

In the era of large-scale surveys like Euclid, machine learning has become an essential tool for identifying rare yet scientifically valuable objects, such as strong gravitational lenses. However, supervised machine-learning approaches require large quantities of labelled examples to train on, and the limited number of known strong lenses has lead to a reliance on simulations for training. A well-known challenge is that machine-learning models trained on one data domain often underperform when applied to a different domain: in the context of lens finding, this means that strong performance on simulated lenses does not necessarily translate into equally good performance on real observations. In Euclid's Quick Data Release 1 (Q1), covering 63 deg2, 500 strong lens candidates were discovered through a synergy of machine learning, citizen science, and expert visual inspection. These discoveries now allow us to quantify this performance gap and investigate the impact of training on real data. We find that a network trained only on simulations recovers up to 92% of simulated lenses with 100% purity, but only achieves 50% completeness with 24% purity on real Euclid data. By augmenting training data with real Euclid lenses and non-lenses, completeness improves by 25-30% in terms of the expected yield of discoverable lenses in Euclid DR1 and the full Euclid Wide Survey. Roughly 20% of this improvement comes from the inclusion of real lenses in the training data, while 5-10% comes from exposure to a more diverse set of non-lenses and false-positives from Q1. We show that the most effective lens-finding strategy for real-world performance combines the diversity of simulations with the fidelity of real lenses. This hybrid approach establishes a clear methodology for maximising lens discoveries in future data releases from Euclid, and will likely also be applicable to other surveys such as LSST.

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