Dating the ages and weighting the stellar populations in galaxies are essential steps when studying galaxy formation through cosmic times. Evolutionary population synthesis models with different input physics are used for this purpose. Moreover, the contribution from the thermally pulsing asymptotic giant branch (TP-AGB) stellar phase, which peaks for intermediate-age 0.6-2 Gyr, has been debated for decades. Here we report the detection of strong cool-star signatures in the rest-frame near-infrared spectra of three young (~1Gyr), massive (~10^10Msun) quiescent galaxies at large look-back time, z=1-2, using JWST/NIRSpec. The coexistence of oxygen- and carbon-type absorption features, spectral edges and features from rare species, such as vanadium and possibly zirconium, reveal a strong contribution from TP-AGB stars. Population synthesis models with a significant TP-AGB contribution reproduce the observations better than those with a weak TP-AGB, which are commonly used. These findings call for revisions of published stellar population fitting results, as they point to populations with lower masses and younger ages and have further implications for cosmic dust production and chemical enrichment. New generations of improved models are needed, informed by these and future observations.

Geospatial Foundation Models (GeoFMs) are transforming Earth Observation (EO), but evaluation lacks standardized protocols. GEO-Bench-2 addresses this with a comprehensive framework spanning classification, segmentation, regression, object detection, and instance segmentation across 19 permissively-licensed datasets. We introduce ''capability'' groups to rank models on datasets that share common characteristics (e.g., resolution, bands, temporality). This enables users to identify which models excel in each capability and determine which areas need improvement in future work. To support both fair comparison and methodological innovation, we define a prescriptive yet flexible evaluation protocol. This not only ensures consistency in benchmarking but also facilitates research into model adaptation strategies, a key and open challenge in advancing GeoFMs for downstream tasks. Our experiments show that no single model dominates across all tasks, confirming the specificity of the choices made during architecture design and pretraining. While models pretrained on natural images (ConvNext ImageNet, DINO V3) excel on high-resolution tasks, EO-specific models (TerraMind, Prithvi, and Clay) outperform them on multispectral applications such as agriculture and disaster response. These findings demonstrate that optimal model choice depends on task requirements, data modalities, and constraints. This shows that the goal of a single GeoFM model that performs well across all tasks remains open for future research. GEO-Bench-2 enables informed, reproducible GeoFM evaluation tailored to specific use cases. Code, data, and leaderboard for GEO-Bench-2 are publicly released under a permissive license.

The Euclid mission aims to measure the positions, shapes, and redshifts of over a billion galaxies to provide unprecedented constraints on the nature of dark matter and dark energy. Achieving this goal requires a continuous reassessment of the mission's scientific performance, particularly in terms of its ability to constrain cosmological parameters, as our understanding of how to model large-scale structure observables improves. In this study, we present the first scientific forecasts using CLOE (Cosmology Likelihood for Observables in Euclid), a dedicated Euclid cosmological pipeline developed to support this endeavour. Using advanced Bayesian inference techniques applied to synthetic Euclid-like data, we sample the posterior distribution of cosmological and nuisance parameters across a variety of cosmological models and Euclid primary probes: cosmic shear, angular photometric galaxy clustering, galaxy-galaxy lensing, and spectroscopic galaxy clustering. We validate the capability of CLOE to produce reliable cosmological forecasts, showcasing Euclid's potential to achieve a figure of merit for the dark energy parameters $w_0$ and $w_a$ exceeding 400 when combining all primary probes. Furthermore, we illustrate the behaviour of the posterior probability distribution of the parameters of interest given different priors and scale cuts. Finally, we emphasise the importance of addressing computational challenges, proposing further exploration of innovative data science techniques to efficiently navigate the Euclid high-dimensional parameter space in upcoming cosmological data releases.

We produce a clean and well-characterised catalogue of objects within 100\,pc of the Sun from the \G\ Early Data Release 3. We characterise the catalogue through comparisons to the full data release, external catalogues, and simulations. We carry out a first analysis of the science that is possible with this sample to demonstrate its potential and best practices for its use. The selection of objects within 100\,pc from the full catalogue used selected training sets, machine-learning procedures, astrometric quantities, and solution quality indicators to determine a probability that the astrometric solution is reliable. The training set construction exploited the astrometric data, quality flags, and external photometry. For all candidates we calculated distance posterior probability densities using Bayesian procedures and mock catalogues to define priors. Any object with reliable astrometry and a non-zero probability of being within 100\,pc is included in the catalogue. We have produced a catalogue of \NFINAL\ objects that we estimate contains at least 92\% of stars of stellar type M9 within 100\,pc of the Sun. We estimate that 9\% of the stars in this catalogue probably lie outside 100\,pc, but when the distance probability function is used, a correct treatment of this contamination is possible. We produced luminosity functions with a high signal-to-noise ratio for the main-sequence stars, giants, and white dwarfs. We examined in detail the Hyades cluster, the white dwarf population, and wide-binary systems and produced candidate lists for all three samples. We detected local manifestations of several streams, superclusters, and halo objects, in which we identified 12 members of \G\ Enceladus. We present the first direct parallaxes of five objects in multiple systems within 10\,pc of the Sun.

We present a comparison of our results from ground-based observations of asteroid (21) Lutetia with imaging data acquired during the flyby of the asteroid by the ESA Rosetta mission. This flyby provided a unique opportunity to evaluate and calibrate our method of determination of size, 3-D shape, and spin of an asteroid from ground-based observations. We present our 3-D shape-modeling technique KOALA which is based on multi-dataset inversion. We compare the results we obtained with KOALA, prior to the flyby, on asteroid (21) Lutetia with the high-spatial resolution images of the asteroid taken with the OSIRIS camera on-board the ESA Rosetta spacecraft, during its encounter with Lutetia. The spin axis determined with KOALA was found to be accurate to within two degrees, while the KOALA diameter determinations were within 2% of the Rosetta-derived values. The 3-D shape of the KOALA model is also confirmed by the spectacular visual agreement between both 3-D shape models (KOALA pre- and OSIRIS post-flyby). We found a typical deviation of only 2 km at local scales between the profiles from KOALA predictions and OSIRIS images, resulting in a volume uncertainty provided by KOALA better than 10%. Radiometric techniques for the interpretation of thermal infrared data also benefit greatly from the KOALA shape model: the absolute size and geometric albedo can be derived with high accuracy, and thermal properties, for example the thermal inertia, can be determined unambiguously. We consider this to be a validation of the KOALA method. Because space exploration will remain limited to only a few objects, KOALA stands as a powerful technique to study a much larger set of small bodies using Earth-based observations.

Synthetic Aperture Radar (SAR) data enables large-scale surveillance of maritime vessels. However, near-real-time monitoring is currently constrained by the need to downlink all raw data, perform image focusing, and subsequently analyze it on the ground. On-board processing to generate higher-level products could reduce the data volume that needs to be downlinked, alleviating bandwidth constraints and minimizing latency. However, traditional image focusing and processing algorithms face challenges due to the satellite's limited memory, processing power, and computational resources. This work proposes and evaluates neural networks designed for real-time inference on unfocused SAR data acquired in Stripmap and Interferometric Wide (IW) modes captured with Sentinel-1. Our results demonstrate the feasibility of using one of our models for on-board processing and deployment on an FPGA. Additionally, by investigating a binary classification task between ships and windmills, we demonstrate that target classification is possible.

We discuss the methods used to compile a high signal-to-noise dataset representative of both the instrumental and cosmic background signal measured at high galactic latitude by the XMM-Newton EPIC cameras. The characteristics of the EPIC background are described and the potential applications of the derived dataset in general science analysis are outlined. In the case of the cosmic X-ray background, the transition between a hard power-law spectrum (due to the integrated emission of unresolved, largely extragalactic, point sources) and a softer thermal spectrum (produced by hot plasma associated with the Galactic plane and halo) is unambiguously detected around ~1keV. We derive a value for the intensity of the power-law component of 2.15 (+/- 0.26) e-11 erg/sq cm/s/sq deg in the 2-10 keV band (Normalisation at 1keV of 11.1 photons /sq cm/s/sr/keV). The implication is that recent, very deep Chandra observations have resolved ~70 - 90% of the 2-10 keV background into discrete sources. Our measurement is towards the higher end of the range of quoted background normalisations.

We report here on observations of a tidal disruption event, XMMSL2 J1404-2511, discovered in an XMM-Newton slew, in a quiescent galaxy at z=0.043. X-ray monitoring covered the epoch when the accretion disc transitioned from a thermal state, with kT~80 eV, to a harder state dominated by a warm, optically-thick corona. The bulk of the coronal formation took place within 7 days and was coincident with a temporary drop in the emitted radiation by a factor 4. After a plateau phase of ~100 days, the X-ray flux of XMMSL2 J1404-2511 decayed by a factor 500 within 230 days. We estimate the black hole mass in the galaxy to be $M_{BH}=4\pm{2}\times10^{6}$ solar masses and the peak X-ray luminosity $L_{X}\sim6\times10^{43}$ ergs/s. The optical/UV light curve is flat over the timescale of the observations with $L_{opt}\sim 2\times10^{41}$ ergs/s. We find that TDEs with coronae are more often found in an X-ray sample than in an optically-selected sample. Late-time monitoring of the optical sample is needed to test whether this is an intrinsic property of TDEs or is due to a selection effect. From the fast decay of the X-ray emission we consider that the event was likely due to the partial stripping of an evolved star rather than a full stellar disruption, an idea supported by the detection of two further re-brightening episodes, two and four years after the first event, in the SRG/eROSITA all-sky survey.

We investigate the composition of the solid-state materials in the winds around S-type AGB stars. The S stars produce dust in their wind that bears a resemblance to the dust produced in some O-rich AGB stars. However, the reported resemblance is mostly based on IRAS/LRS spectra with limited spectral resolution, sensitivity, and wavelength coverage. We investigate the dust composition around S stars using ISO/SWS data that surpass the previous studies in terms of spectral resolution and wavelength coverage. We compare the dust spectra from the 9 sources with the O-rich AGB spectra and a subset of M super-giants. We constructed average dust emission spectra of the different categories. We report the discovery of several previously unreported dust emission features in the S star spectra. The long wavelength spectra of W Aql and pi1 Gru exhibit the "30" micrometer feature attributed to MgS. Two sources exhibit a series of emission bands between 20 and 40 micrometer that we tentatively ascribe to Diopside. We show that the 10-20 micrometer spectra of the S stars are significantly different from the O-rich AGB stars. The O-rich stars exhibit a structured emission feature that is believed to arise from amorphous silicate and aluminium-oxide. The S stars lack the substructure found in the O-rich stars. Instead they show a smooth peak with a varying peak-position from source to source. We suggest that this feature is caused by a family of related material, whose exact composition determines the peak position. The observed trend mimics the laboratory trend of non-stoichiometric silicates. In this scenario the degree of non-stoichiometry is related to the Mg to SiO4 ratio, in other words, to the amount of free O available during the dust grain growth.

In meteor science, the identification of meteor showers is a crucial and complex problem. The most common method is to perform a systematic search of a database of observed orbits using an orbit dissimilarity criterion (D-criterion) and an algorithm. D-criteria compare the result of an orbit dissimilarity function (D-function) and a threshold. These D-functions associate one value to two meteoroids orbits. If this value is lower than the threshold, the meteoroids' orbits are considered similar. Group of meteors are thus formed. However, not all D-criteria have been evaluated, and their high number makes it hard to know which should be prioritised. This paper presents a review of each D-function, the tests they passed, the threshold choice, and the algorithms they are used with. We show what methods are currently used in the search for meteor showers, presenting statistics based on papers justifying the existence of established meteor showers. We review D-functions from eight different papers. We describe how thresholds and clustering algorithms are usually chosen. We also analyse tests that were performed on D-criteria. We discover that most of those criteria were not properly tested, and that some have been criticised for their theoretical background. Thus, we recommend performing a post-search analysis of the groups found, both in a statistical sense (to make sure the groups formed could not have been formed randomly) and an orbital dynamics sense (to check whether the group could indeed come from a singular parent body), to present the findings as potential meteor showers.

Observational astronomy of tidal disruption events (TDEs) began with the detection of X-ray flares from quiescent galaxies during the ROSAT all-sky survey of 1990-1991. The flares complied with theoretical expectations, having high peak luminosities ($L_{\rm x}$ up to $\ge4\times 10^{44}$ erg/s), a thermal spectrum with $kT\sim$few$\times10^5$ K, and a decline on timescales of months to years, consistent with a diminishing return of stellar debris to a black hole of mass $10^{6-8}$ solar masses. These measurements gave solid proof that the nuclei of quiescent galaxies are habitually populated by a super-massive black hole. Beginning in 2000, XMM-Newton, Chandra and Swift have discovered further TDEs which have been monitored closely at multiple wavelengths. A general picture has emerged of, initially near-Eddington accretion, powering outflows of highly-ionised material, giving way to a calmer sub-Eddington phase, where the flux decays monotonically, and finally a low accretion rate phase with a harder X-ray spectrum indicative of the formation of a disk corona. There are exceptions to this rule though which at the moment are not well understood. A few bright X-ray TDEs have been discovered in optical surveys but in general X-ray TDEs show little excess emission in the optical band, at least at times coincident with the X-ray flare. X-ray TDEs are powerful new probes of accretion physics down to the last stable orbit, revealing the conditions necessary for launching jets and winds. Finally we see that evidence is mounting for nuclear and non-nuclear intermediate mass black holes based on TDE flares which are relatively hot and/or fast.

To date, galaxy image simulations for weak lensing surveys usually approximate the light profiles of all galaxies as a single or double Sérsic profile, neglecting the influence of galaxy substructures and morphologies deviating from such a simplified parametric characterization. While this approximation may be sufficient for previous data sets, the stringent cosmic shear calibration requirements and the high quality of the data in the upcoming Euclid survey demand a consideration of the effects that realistic galaxy substructures have on shear measurement biases. Here we present a novel deep learning-based method to create such simulated galaxies directly from HST data. We first build and validate a convolutional neural network based on the wavelet scattering transform to learn noise-free representations independent of the point-spread function of HST galaxy images that can be injected into simulations of images from Euclid's optical instrument VIS without introducing noise correlations during PSF convolution or shearing. Then, we demonstrate the generation of new galaxy images by sampling from the model randomly and conditionally. Next, we quantify the cosmic shear bias from complex galaxy shapes in Euclid-like simulations by comparing the shear measurement biases between a sample of model objects and their best-fit double-Sérsic counterparts. Using the KSB shape measurement algorithm, we find a multiplicative bias difference between these branches with realistic morphologies and parametric profiles on the order of $6.9\times 10^{-3}$ for a realistic magnitude-Sérsic index distribution. Moreover, we find clear detection bias differences between full image scenes simulated with parametric and realistic galaxies, leading to a bias difference of $4.0\times 10^{-3}$ independent of the shape measurement method. This makes it relevant for stage IV weak lensing surveys such as Euclid.

GSN 069 is the first galactic nucleus where quasi-periodic eruptions (QPEs) have been identified. These are high-amplitude, soft X-ray bursts recurring every ~9 hr, lasting ~1 hr, and during which the X-ray count rate increases by up to two orders of magnitude with respect to an otherwise stable quiescent level. The X-ray spectral properties and the long-term evolution of GSN 069 in the first few years are consistent with a long-lived tidal disruption event (TDE). Here we derive the properties of QPEs and of the long-term X-ray evolution in GSN 069 over the past 12 yr by studying timing and spectral X-ray data from 11 XMM-Newton, one Chandra, and 34 Swift observations on timescales ranging from minutes to years. QPEs in GSN 069 are a transient phenomenon with a lifetime > 1.05 yr. The QPE intensity and recurrence time oscillate and allow for alternating strong-weak QPEs and long-short recurrence times to be defined. In observations with QPEs, the quiescent level exhibits a quasi-periodic oscillation with a period equal to the average separation between consecutive QPEs. The QPE spectral evolution is consistent with thermal emission from a very compact region that heats up quickly and subsequently cools down via X-ray emission while expanding by a factor of ~3 in radius. The long-term evolution of the quiescent level is characterised by two repeating TDEs ~9 yr apart. We detect a precursor X-ray flare prior to the second TDE that may be associated with the circularisation phase during disc formation. A similar precursor flare is tentatively detected just before the first TDE. Future X-ray observations of GSN 069 promise that the QPE origin and the relation between QPEs and repeating TDEs in this galactic nucleus will be constrained, with consequences for the other sources where QPEs have been identified. [abridged]

We analyze the evolution of massive (log$_{10}$ [$M_\star/M_\odot$] $>10$) galaxies at $z \sim$ 4--8 selected from the JWST Cosmic Evolution Early Release Science (CEERS) survey. We infer the physical properties of all galaxies in the CEERS NIRCam imaging through spectral energy distribution (SED) fitting with dense basis to select a sample of high redshift massive galaxies. Where available we include constraints from additional CEERS observing modes, including 18 sources with MIRI photometric coverage, and 28 sources with spectroscopic confirmations from NIRSpec or NIRCam wide-field slitless spectroscopy. We sample the recovered posteriors in stellar mass from SED fitting to infer the volume densities of massive galaxies across cosmic time, taking into consideration the potential for sample contamination by active galactic nuclei (AGN). We find that the evolving abundance of massive galaxies tracks expectations based on a constant baryon conversion efficiency in dark matter halos for $z \sim$ 1--4. At higher redshifts, we observe an excess abundance of massive galaxies relative to this simple model. These higher abundances can be explained by modest changes to star formation physics and/or the efficiencies with which star formation occurs in massive dark matter halos, and are not in tension with modern cosmology.

Local Universe dwarf galaxies are both cosmological and mass assembly probes. Deep surveys have enabled the study of these objects down to the low surface brightness (LSB) regime. In this paper, we estimate Euclid's dwarf detection capabilities as well as limits of its MERge processing function (MER pipeline), responsible for producing the stacked mosaics and final catalogues. To do this, we inject mock dwarf galaxies in a real Euclid Wide Survey (EWS) field in the VIS band and compare the input catalogue to the final MER catalogue. The mock dwarf galaxies are generated with simple Sérsic models and structural parameters extracted from observed dwarf galaxy property catalogues. To characterize the detected dwarfs, we use the mean surface brightness inside the effective radius SBe (in mag arcsec-2). The final MER catalogues achieve completenesses of 91 % for SBe in [21, 24], and 54 % for SBe in [24, 28]. These numbers do not take into account possible contaminants, including confusion with background galaxies at the location of the dwarfs. After taking into account those effects, they become respectively 86 % and 38 %. The MER pipeline performs a final local background subtraction with small mesh size, leading to a flux loss for galaxies with Re > 10". By using the final MER mosaics and reinjecting this local background, we obtain an image in which we recover reliable photometric properties for objects under the arcminute scale. This background-reinjected product is thus suitable for the study of Local Universe dwarf galaxies. Euclid's data reduction pipeline serves as a test bed for other deep surveys, particularly regarding background subtraction methods, a key issue in LSB science.

Cosmological probes based on galaxy clusters rely on cluster number counts and large-scale structure information. X-ray cluster surveys are well suited for this purpose, since they are far less affected than optical surveys by projection effects, and cluster properties can be predicted with good accuracy. The XMM Cluster Archive Super Survey, X-CLASS, is a serendipitous search of X-ray-detected galaxy clusters in 4176 XMM-Newton archival observations until August 2015. All observations are clipped to exposure times of 10 and 20 ks to obtain uniformity and they span ~269 deg$^2$ across the high-Galactic latitude sky ($|b|> 20^o$). The main goal of the survey is the compilation of a well-selected cluster sample suitable for cosmological analyses. We describe the detection algorithm, the visual inspection, the verification process and the redshift validation of the cluster sample, as well as the cluster selection function computed by simulations. We also present the various metadata that are released with the catalogue, along with the redshifts of 124 clusters obtained with a dedicated multi-object spectroscopic follow-up programme. With this publication we release the new X-CLASS catalogue of 1646 well-selected X-ray-detected clusters over a wide sky area, along with their selection function. The sample spans a wide redshift range, from the local Universe up to z~1.5, with 982 spectroscopically confirmed clusters, and over 70 clusters above z=0.8. Because of its homogeneous selection and thorough verification, the cluster sample can be used for cosmological analyses, but also as a test-bed for the upcoming eROSITA observations and other current and future large-area cluster surveys. It is the first time that such a catalogue is made available to the community via an interactive database which gives access to a wealth of supplementary information, images, and data.

We present results of ultra-deep ISOCAM observations through a cluster-lens at 7 and 15 micron with the Infrared Space Observatory (ISO) satellite. These observations reveal a large number of luminous Mid-Infrared (MIR) sources. Cross-identification in the optical and Near-Infrared (NIR) wavebands shows that about half of the 7 micron sources are cluster galaxies. The other 7 micron and almost all 15 micron sources are identified as lensed distant galaxies. Thanks to the gravitational amplification they constitute the faintest MIR detected sources, allowing us to extend the number counts in both the 7 and 15 micron bands. In particular, we find that the 15 micron counts have a steep slope alpha_15 = -1.5 +/- 0.3 and are large, with N_15 (>30 microJy}) = 13 +/- 5 per square arcmin. These numbers rule out non-evolutionary models and favour very strong evolution. Down to our counts limit, we found that the resolved 7 and 15 microns background radiation intensity is respectively (2 +/-0.5) 10^(-9) and (5 +/-1) 10^(-9) W m^(-2) sr^(-1).

We present a new infrared survey covering the three Euclid deep fields and four other Euclid calibration fields using Spitzer's Infrared Array Camera (IRAC). We have combined these new observations with all relevant IRAC archival data of these fields in order to produce the deepest possible mosaics of these regions. In total, these observations represent nearly 11% of the total Spitzer mission time. The resulting mosaics cover a total of approximately 71.5deg$^2$ in the 3.6 and 4.5um bands, and approximately 21.8deg$^2$ in the 5.8 and 8um bands. They reach at least 24 AB magnitude (measured to sigma, in a 2.5 arcsec aperture) in the 3.6um band and up to ~ 5 mag deeper in the deepest regions. The astrometry is tied to the Gaia astrometric reference system, and the typical astrometric uncertainty for sources with 16<[3.6]<19 is <0.15 arcsec. The photometric calibration is in excellent agreement with previous WISE measurements. We have extracted source number counts from the 3.6um band mosaics and they are in excellent agreement with previous measurements. Given that the Spitzer Space Telescope has now been decommissioned these mosaics are likely to be the definitive reduction of these IRAC data. This survey therefore represents an essential first step in assembling multi-wavelength data on the Euclid deep fields which are set to become some of the premier fields for extragalactic astronomy in the 2020s.