Context: With the advancement of solar physics research, next-generation solar space missions and ground-based telescopes face significant challenges in efficiently transmitting and/or storing large-scale observational data. Aims: We develop an efficient compression and evaluation framework for solar EUV data, specifically optimized for Solar Orbiter Extreme Ultraviolet Imager (EUI) data, significantly reducing data volume while preserving scientific usability. Methods: We systematically evaluated four error-bounded lossy compressors across two EUI datasets. However, the existing methods cannot perfectly handle the EUI datasets (with continuously changing distance and significant resolution differences). Motivated by this, we develop an adaptive hybrid compression strategy with optimized interpolation predictors. Moreover, we designed a two-stage evaluation framework integrating distortion analysis with downstream scientific workflows, ensuring that observational analysis is not affected at high compression ratios. Results: Our framework SolarZip achieved up to 800x reduction for Full Sun Imager (FSI) data and 500x for High Resolution Imager (HRI$_{\text{EUV}}$) data. It significantly outperformed both traditional and advanced algorithms, achieving 3-50x higher compression ratios than traditional algorithms, surpassing the second-best algorithm by up to 30%. Simulation experiments verified that SolarZip can reduce data transmission time by up to 270x while ensuring the preservation of scientific usability. Conclusions: The SolarZip framework significantly enhances solar observational data compression efficiency while preserving scientific usability by dynamically selecting optimal compression methods based on observational scenarios and user requirements. This provides a promising data management solution for deep space missions like Solar Orbiter.

A tight correlation between the baryonic and observed acceleration of galaxies has been reported over a wide range of mass (10^8 < M_{\rm bar}/{\rm M}_\odot < 10^{11}) - the Radial Acceleration Relation (RAR). This has been interpreted as evidence that dark matter is actually a manifestation of some modified weak-field gravity theory. In this paper, we study the radially resolved RAR of 12 nearby dwarf galaxies, with baryonic masses in the range 10^4 < M_{\rm bar}/{\rm M}_\odot < 10^{7.5}, using a combination of literature data and data from the MUSE-Faint survey. We use stellar line-of-sight velocities and the Jeans modelling code GravSphere to infer the mass distributions of these galaxies, allowing us to compute the RAR. We compare the results with the EDGE simulations of isolated dwarf galaxies with similar stellar masses in a $\Lambda$CDM cosmology. We find that most of the observed dwarf galaxies lie systematically above the low-mass extrapolation of the RAR. Each galaxy traces a locus in the RAR space that can have a multi-valued observed acceleration for a given baryonic acceleration, while there is significant scatter from galaxy to galaxy. Our results indicate that the RAR does not apply to low-mass dwarf galaxies and that the inferred baryonic acceleration of these dwarfs does not contain enough information, on its own, to derive the observed acceleration. The simulated EDGE dwarfs behave similarly to the real data, lying systematically above the extrapolated RAR. We show that, in the context of modified weak-field gravity theories, these results cannot be explained by differential tidal forces from the Milky Way, nor by the galaxies being far from dynamical equilibrium, since none of the galaxies in our sample seems to experience strong tides. As such, our results provide further evidence for the need for invisible dark matter in the smallest dwarf galaxies.

Although numerous dynamical techniques have been developed to estimate the total dark matter halo mass of the Milky Way, it remains poorly constrained, with typical systematic uncertainties of 0.3 dex. In this study, we apply a neural network-based approach that achieves high mass precision without several limitations that have affected past approaches; for example, we do not assume dynamical equilibrium, nor do we assume that neighboring galaxies are bound satellites. Additionally, this method works for a broad mass range, including for halos that differ significantly from the Milky Way. Our model relies solely on observable dynamical quantities, such as satellite orbits, distances to larger nearby halos, and the maximum circular velocity of the most massive satellite. In this paper, we measure the halo mass of the Milky Way to be log_10 M_vir / M_Sun = 12.20^{+0.163}_{-0.138}. Future studies in this series will extend this methodology to estimate the dark matter halo mass of M31, and develop new neural networks to infer additional halo properties including concentration, assembly history, and spin axis.

We introduce SpectraPyle, a versatile spectral stacking pipeline developed for the Euclid mission's NISP spectroscopic surveys, aimed at extracting faint emission lines and spectral features from large galaxy samples in the Wide and Deep Surveys. Designed for computational efficiency and flexible configuration, SpectraPyle supports the processing of extensive datasets critical to Euclid's non-cosmological science goals. We validate the pipeline using simulated spectra processed to match Euclid's expected final data quality. Stacking enables robust recovery of key emission lines, including Halpha, Hbeta, [O III], and [N II], below individual detection limits. However, the measurement of galaxy properties such as star formation rate, dust attenuation, and gas-phase metallicity are biased at stellar mass below log10(M*/Msol) ~ 9 due to the flux-limited nature of Euclid spectroscopic samples, which cannot be overcome by stacking. The SFR-stellar mass relation of the parent sample is recovered reliably only in the Deep survey for log10(M*/Msol) > 10, whereas the metallicity-mass relation is recovered more accurately over a wider mass range. These limitations are caused by the increased fraction of redshift measurement errors at lower masses and fluxes. We examine the impact of residual redshift contaminants that arises from misidentified emission lines and noise spikes, on stacked spectra. Even after stringent quality selections, low-level contamination (< 6%) has minimal impact on line fluxes due to the systematically weaker emission of contaminants. Percentile-based analysis of stacked spectra provides a sensitive diagnostic for detecting contamination via coherent spurious features at characteristic wavelengths. While our simulations include most instrumental effects, real Euclid data will require further refinement of contamination mitigation strategies.

The Large Magellanic Cloud (LMC) will induce a dynamical friction (DF) wake on infall to the Milky Way (MW). The MW's stellar halo will respond to the gravity of the LMC and the dark matter (DM) wake, forming a stellar counterpart to the DM wake. This provides a novel opportunity to constrain the properties of the DM particle. We present a suite of high-resolution, windtunnel-style simulations of the LMC's DF wake that compare the structure, kinematics, and stellar tracer response of the DM wake in cold DM (CDM), with and without self-gravity, vs. fuzzy DM (FDM) with $m_a = 10^{-23}$ eV. We conclude that the self-gravity of the DM wake cannot be ignored. Its inclusion raises the wake's density by $\sim 10\%$, and holds the wake together over larger distances ($\sim$ 50 kpc) than if self-gravity is ignored. The DM wake's mass is comparable to the LMC's infall mass, meaning the DM wake is a significant perturber to the dynamics of MW halo tracers. An FDM wake is more granular in structure and is $\sim 20\%$ dynamically colder than a CDM wake, but with comparable density. The granularity of an FDM wake increases the stars' kinematic response at the percent level compared to CDM, providing a possible avenue of distinguishing a CDM vs. FDM wake. This underscores the need for kinematic measurements of stars in the stellar halo at distances of 70-100 kpc.

Structure in the Universe is believed to have evolved out of quantum fluctuations seeded by inflation in the early Universe. These fluctuations lead to density perturbations that grow via gravitational instability into large cosmological structures. In the linear regime, the growth of structure is directly coupled to the velocity field since perturbations are amplified by attracting (and accelerating) matter. Surveys of galaxy redshifts and distances allow one to infer the underlying density and velocity fields. Here, assuming the LCDM standard model of cosmology and applying a Hamiltonian Monte-Carlo algorithm to the grouped Cosmicflows-4 (CF4) compilation of 38,000 groups of galaxies, the large scale structure of the Universe is reconstructed out to a redshift corresponding to about 30, 000 km/s. Our method provides a probabilistic assessment of the domains of gravitational potential minima: basins of attraction (BoA). Earlier Cosmicflows catalogs suggested the Milky Way Galaxy was associated with a BoA called Laniakea. Now with the newer CF4 data, there is a slight probabilistic preference for Laniakea to be part of the much larger Shapley BoA. The largest BoA recovered from the CF4 data is associated with the Sloan Great Wall with a volume within the sample of 15.5 10^6(Mpc/h)^3, which is more than twice the size of the second largest Shapley BoA.

In the current panorama of large surveys, the vast amount of data obtained with different methods, data types, formats, and stellar samples, is making an efficient use of the available information difficult. The Survey of Surveys is a project to critically compile survey results in a single catalogue, facilitating the scientific use of the available information. In this second release, we present two new catalogs of stellar parameters (Teff, logg, and [Fe/H]). To build the first catalog, SoS-Spectro, we calibrated internally and externally stellar parameters from five spectroscopic surveys (APOGEE, GALAH, Gaia-ESO, RAVE, and LAMOST) and externally on the PASTEL database. The second catalog, SoS-ML catalog, is obtained by using SoS-Spectro as a reference to train a multi-layer perceptron, which predicts stellar parameters based on two photometric surveys, SDSS and SkyMapper. As a novel approach, we build on previous parameters sets, from Gaia DR3 and Andrae et al. (2023), aiming to improve their precision and accuracy. We obtain a catalog of stellar parameters for around 23 millions of stars, which we make publicly available. We validate our results with several comparisons with other machine learning catalogs, stellar clusters, and astroseismic samples. We find substantial improvements in the parameters estimates compared to other Machine Learning methods in terms of precision and accuracy, especially in the metal-poor range, as shown in particular when validating our results with globular clusters. We believe that there are two reasons behind our improved results at the low-metallicity end: first, our use of a reference catalog, the SoS-Spectro, which is calibrated using high-resolution spectroscopic data; and second, our choice to build on pre-existing parameter estimates from em Gaia and Andrae et al., rather than attempting to obtain our predictions from survey data alone.

The goal of this paper is to describe the science verification of Milky Way Mapper (MWM) APOGEE Stellar Parameter and Chemical Abundances Pipeline (ASPCAP) data products published in Data Release 19 (DR19) of the fifth phase of the Sloan Digital Sky Survey (SDSS-V). We compare MWM ASPCAP atmospheric parameters T$_{\rm eff}$, log g, 24 abundances of 21 elements (carbon, nitrogen, and oxygen have multiple sources for deriving their abundance values) and their uncertainties determined from Apache Point Observatory Galactic Evolution Experiment (APOGEE) spectrograph spectra with those of the literature and evaluate their accuracy and precision. We also test the zero-point calibration of the v$_{\rm rad}$ derived by the APOGEE Data Reduction Pipeline. This data release contains ASPCAP parameters for 964,989 stars, including all APOGEE-2 targets expanded with new observations of 336,511 stars from the Apache Point Observatory observed until 4 July 2023. Overall, the new T$_{\rm eff}$ values show excellent agreement with the IRFM scale, while the surface gravities exhibit slight systematic offsets compared to asteroseisimic gravities. The estimated precision of T$_{\rm eff}$ is between 50 and 70 K for giants and 70$-$100 K for dwarfs, while surface gravities are measured with a precision of 0.07$-$0.09 dex for giants. We achieve an estimated precision of 0.02$-$0.04 dex for multiple elements, including metallicity, $\alpha$, Mg, and Si, while the precision of at least 10 elements is better than 0.1 dex.

The intrinsic properties of galaxies are influenced by their environments, underscoring the environment's critical role in galaxy formation and evolution. Traditionally, these environments are categorized into four fixed classifications: knots, filaments, walls, and voids, which collectively describe the complex organization of galaxies within large-scale structures. We propose an alternative description that complements the traditional quadripartite categorization by introducing a continuous framework, allowing for a more nuanced examination of the relationship between the intrinsic properties of galaxies and their environments. This complementary description is applied using one of the most prevalent methodologies: categorization using the eigenvalues of the Hessian matrix extracted from the matter density field. We integrated our findings into a semi-analytical model of galaxy formation, combined with cosmological numerical simulations, to analyze how the intrinsic properties of galaxies are influenced by environmental changes. In our study, we find a continuous distribution of eigenvalue ratios, revealing a clear dependence of galaxy properties on their surrounding environments. This method allowed us to identify critical values at which transitions in the behavior of key astrophysical galaxy properties become evident.

The AGN Space Telescope and Optical Reverberation Mapping 2 (STORM 2) campaign targeted Mrk 817 with intensive multi-wavelength monitoring and found its soft X-ray emission to be strongly absorbed. We present results from 157 near-IR spectra with an average cadence of a few days. Whereas the hot dust reverberation signal as tracked by the continuum flux does not have a clear response, we recover a dust reverberation radius of $\sim 90$ light-days from the blackbody dust temperature light-curve. This radius is consistent with previous photometric reverberation mapping results when Mrk 817 was in an unobscured state. The heating/cooling process we observe indicates that the inner limit of the dusty torus is set by a process other than sublimation, rendering it a luminosity-invariant `dusty wall' of a carbonaceous composition. Assuming thermal equilibrium for dust optically thick to the incident radiation, we derive a luminosity of $\sim 6 \times 10^{44}$ erg s$^{-1}$ for the source heating it. This luminosity is similar to that of the obscured spectral energy distribution, assuming a disk with an Eddington accretion rate of $\dot{m} \sim 0.2$. Alternatively, the dust is illuminated by an unobscured lower luminosity disk with $\dot{m} \sim 0.1$, which permits the UV/optical continuum lags in the high-obscuration state to be dominated by diffuse emission from the broad-line region. Finally, we find hot dust extended on scales $> 140-350$ pc, associated with the rotating disk of ionised gas we observe in spatially-resolved [SIII] $\lambda 9531$ images. Its likely origin is in the compact bulge of the barred spiral host galaxy, where it is heated by a nuclear starburst.

Globular clusters (GCs) and their associated stellar streams are key tracers of the hierarchical assembly history of the Milky Way. $\omega$ Centauri, the most massive and chemically complex GC in the Galaxy, is widely believed to be the remnant nucleus of an accreted dwarf galaxy. Identifying its associated debris and that of chemically similar clusters can provide important constraints on the nature of this progenitor system. We aim to identify field stars that are chemically and kinematically linked to $\omega$ Cen and to a group of globular clusters associated with the Nephele accretion event. We analyse APOGEE DR17 data using a Gaussian Mixture Model (GMM) in a 8-dimensional chemical space to identify field stars whose abundances match those of $\omega$ Cen. We then compute the orbital energy and angular momentum of these stars and apply a second GMM, calibrated on simulations from the e-TidalGCs project, to determine kinematic compatibility with the predicted streams of $\omega$ Cen and the associated Nephele GCs. We identify 470 stars chemically compatible with $\omega$ Cen, of which 58 are also Al-rich, consistent with second-generation stars found in GCs. Of these, 6 stars show kinematics consistent with the predicted $\omega$ Cen stream, and additional stars are linked to the tidal streams of NGC 6205, NGC 6254, NGC 6273, NGC 6656, and NGC 6809. We also find overlap in chemical and kinematic properties between Nephele stars and the Gaia Sausage-Enceladus population. Our findings indicate stellar debris linked to $\omega$ Cen and its candidate globular cluster family, consistent with a shared, now-disrupted galactic progenitor. Despite residual uncertainties from disc contamination and limited sky coverage, the results demonstrate the effectiveness of combined chemical and dynamical analyses in uncovering relics of past accretion events in the inner Galaxy.

Gravitational waves from black-hole merging events have revealed a population of extra-galactic BHs residing in short-period binaries with masses that are higher than expected based on most stellar evolution models - and also higher than known stellar-origin black holes in our Galaxy. It has been proposed that those high-mass BHs are the remnants of massive metal-poor stars. Gaia astrometry is expected to uncover many Galactic wide-binary systems containing dormant BHs, which may not have been detected before. The study of this population will provide new information on the BH-mass distribution in binaries and shed light on their formation mechanisms and progenitors. As part of the validation efforts in preparation for the fourth Gaia data release (DR4), we analysed the preliminary astrometric binary solutions, obtained by the Gaia Non-Single Star pipeline, to verify their significance and to minimise false-detection rates in high-mass-function orbital solutions. The astrometric binary solution of one source, Gaia BH3, implies the presence of a 32.70 \pm 0.82 M\odot BH in a binary system with a period of 11.6 yr. Gaia radial velocities independently validate the astrometric orbit. Broad-band photometric and spectroscopic data show that the visible component is an old, very metal-poor giant of the Galactic halo, at a distance of 590 pc. The BH in the Gaia BH3 system is more massive than any other Galactic stellar-origin BH known thus far. The low metallicity of the star companion supports the scenario that metal-poor massive stars are progenitors of the high-mass BHs detected by gravitational-wave telescopes. The Galactic orbit of the system and its metallicity indicate that it might belong to the Sequoia halo substructure. Alternatively, and more plausibly, it could belong to the ED-2 stream, which likely originated from a globular cluster that had been disrupted by the Milky Way.

We present a first large-scale kinematic map of $\sim$50,000 young OB stars ($T_{\rm eff} \geq 10,000$ K), based on BOSS spectroscopy from the Milky Way Mapper OB program in the ongoing Sloan Digital Sky Survey V (SDSS-V). Using photogeometric distances, line-of-sight velocities and Gaia DR3 proper motions, we map 3D Galactocentric velocities across the Galactic plane to $\sim$5 kpc from the Sun, with a focus on radial motions ($v_R$). Our results reveal mean radial motion with amplitudes of $\pm 30$ km/s that are coherent on kiloparsec scales, alternating between inward and outward motions. These $\bar{v}_R$ amplitudes are considerably higher than those observed for older, red giant populations. These kinematic patterns show only a weak correlation with spiral arm over-densities. Age estimates, derived from MIST isochrones, indicate that 85% of the sample is younger than $\sim300$ Myr and that the youngest stars ($\le 30$ Myr) align well with density enhancements. The age-dependent $\bar{v}_R$ in Auriga makes it plausible that younger stars exhibits different velocity variations than older giants. The origin of the radial velocity features remains uncertain, and may result from a combination of factors, including spiral arm dynamics, the Galactic bar, resonant interactions, or phase mixing following a perturbation. The present analysis is based on approximately one-third of the full target sample. The completed survey will enable a more comprehensive investigation of these features and a detailed dynamical interpretation.

We present long-term (4-10 years) trends of light pollution observed at 26 locations, covering rural, intermediate and urban sites, including the three major European metropolitan areas of Stockholm, Berlin and Vienna. Our analysis is based on i) night sky brightness (NSB) measurements obtained with Sky Quality Meters (SQMs) and ii) a rich set of atmospheric data products provided by the European Centre for Medium-Range Weather Forecasts. We describe the SQM data reduction routine in which we filter for moon- and clear-sky data and correct for the SQM "aging" effect using an updated version of the twilight method of Puschnig et al. (2021). Our clear-sky, aging-corrected data reveals short- and long-term (seasonal) variations due to atmospheric changes. To assess long-term anthropogenic NSB trends, we establish an empirical atmospheric model via multi-variate penalized linear regression. Our modeling approach allows to quantitatively investigate the importance of different atmospheric parameters, revealing that surface albedo and vegetation have by far the largest impact on zenithal NSB. Additionally, the NSB is sensitive to black carbon and organic matter aerosols at urban and rural sites respectively. Snow depth was found to be important for some sites, while the total column of ozone leaves impact on some rural places. The average increase in light pollution at our 11 rural sites is 1.7 percent per year. At our nine urban sites we measure an increase of 1.8 percent per year and for the remaining six intermediate sites we find an average increase of 3.7 percent per year. These numbers correspond to doubling times of 41, 39 and 19 years. We estimate that our method is capable of detecting trend slopes shallower/steeper than 1.5 percent per year.

WEAVE, the new wide-field, massively multiplexed spectroscopic survey facility for the William Herschel Telescope, will see first light in late 2022. WEAVE comprises a new 2-degree field-of-view prime-focus corrector system, a nearly 1000-multiplex fibre positioner, 20 individually deployable 'mini' integral field units (IFUs), and a single large IFU. These fibre systems feed a dual-beam spectrograph covering the wavelength range 366$-$959\,nm at $R\sim5000$, or two shorter ranges at $R\sim20\,000$. After summarising the design and implementation of WEAVE and its data systems, we present the organisation, science drivers and design of a five- to seven-year programme of eight individual surveys to: (i) study our Galaxy's origins by completing Gaia's phase-space information, providing metallicities to its limiting magnitude for $\sim$3 million stars and detailed abundances for $\sim1.5$ million brighter field and open-cluster stars; (ii) survey $\sim0.4$ million Galactic-plane OBA stars, young stellar objects and nearby gas to understand the evolution of young stars and their environments; (iii) perform an extensive spectral survey of white dwarfs; (iv) survey $\sim400$ neutral-hydrogen-selected galaxies with the IFUs; (v) study properties and kinematics of stellar populations and ionised gas in z&lt;0.5 cluster galaxies; (vi) survey stellar populations and kinematics in $\sim25\,000$ field galaxies at $0.3\lesssim z \lesssim 0.7$; (vii) study the cosmic evolution of accretion and star formation using &gt;1 million spectra of LOFAR-selected radio sources; (viii) trace structures using intergalactic/circumgalactic gas at z&gt;2. Finally, we describe the WEAVE Operational Rehearsals using the WEAVE Simulator.

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.