The Gaia Galactic survey mission is designed and optimized to obtain astrometry, photometry, and spectroscopy of nearly two billion stars in our Galaxy. Yet as an all-sky multi-epoch survey, Gaia also observes several million extragalactic objects down to a magnitude of G~21 mag. Due to the nature of the Gaia onboard selection algorithms, these are mostly point-source-like objects. Using data provided by the satellite, we have identified quasar and galaxy candidates via supervised machine learning methods, and estimate their redshifts using the low resolution BP/RP spectra. We further characterise the surface brightness profiles of host galaxies of quasars and of galaxies from pre-defined input lists. Here we give an overview of the processing of extragalactic objects, describe the data products in Gaia DR3, and analyse their properties. Two integrated tables contain the main results for a high completeness, but low purity (50-70%), set of 6.6 million candidate quasars and 4.8 million candidate galaxies. We provide queries that select purer sub-samples of these containing 1.9 million probable quasars and 2.9 million probable galaxies (both 95% purity). We also use high quality BP/RP spectra of 43 thousand high probability quasars over the redshift range 0.05-4.36 to construct a composite quasar spectrum spanning restframe wavelengths from 72-100 nm.

Third-generation gravitational wave detectors such as Einstein Telescope and Cosmic Explorer will have significantly better sensitivities than current detectors, as well as a wider frequency bandwidth. This will increase the number and duration of the observed signals, leading to many signals overlapping in time. If not adequately accounted for, this can lead to biases in parameter estimation. In this work, we combine the joint parameter estimation method with relative binning to handle full parameter inference on overlapping signals from binary black holes, including precession effects and higher-order mode content. As this method is computationally more expensive than traditional single-signal parameter estimation, we test a prior-informed Fisher matrix and a time-frequency overlap method for estimating expected bias to help us decide when joint parameter estimation is necessary over the simpler methods. We improve upon previous Fisher matrix implementations by including the prior information and performing an optimization routine to better locate the maximum likelihood point point, but we still find the method unreliable. The time-frequency method is accurate in 86% of close binary black hole mergers. We end by developing our own method of estimating bias due overlaps, where we reweight the single signal parameter estimation posterior to quantify how much the overlapping signals affect it. We show it has 99% accuracy for zero noise injections (98% in Gaussian noise), at the cost of one additional standard sampling run when joint parameter estimation proves to be necessary.

In this work, we present LensingFlow. This is an implementation of an automated workflow to search for evidence of gravitational lensing in a large series of gravitational wave events. This workflow conducts searches for evidence in all generally considered lensing regimes. The implementation of this workflow is built atop the Asimov automation framework and CBCFlow metadata management software and the resulting product therefore encompasses both the automated running and status checking of jobs in the workflow as well as the automated production and storage of relevant metadata from these jobs to allow for later reproduction. This workflow encompasses a number of existing lensing pipelines and has been designed to accommodate any additional future pipelines to provide both a current and future basis on which to conduct large scale lensing analyses of gravitational wave signal catalogues. The workflow also implements a prioritisation management system for jobs submitted to the schedulers in common usage in computing clusters ensuring both the completion of the workflow across the entire catalogue of events as well as the priority completion of the most significant candidates. As a first proof-of-concept demonstration, we deploy LensingFlow on a mock data challenge comprising 10 signals in which signatures of each lensing regime are represented. LensingFlow successfully ran and identified the candidates from this data through its automated checks of results from consituent analyses.

Separating active regions that are quiet from potentially eruptive ones is a key issue in Space Weather applications. Traditional classification schemes such as Mount Wilson and McIntosh have been effective in relating an active region large scale magnetic configuration to its ability to produce eruptive events. However, their qualitative nature prevents systematic studies of an active region's evolution for example. We introduce a new clustering of active regions that is based on the local geometry observed in Line of Sight magnetogram and continuum images. We use a reduced-dimension representation of an active region that is obtained by factoring the corresponding data matrix comprised of local image patches. Two factorizations can be compared via the definition of appropriate metrics on the resulting factors. The distances obtained from these metrics are then used to cluster the active regions. We find that these metrics result in natural clusterings of active regions. The clusterings are related to large scale descriptors of an active region such as its size, its local magnetic field distribution, and its complexity as measured by the Mount Wilson classification scheme. We also find that including data focused on the neutral line of an active region can result in an increased correspondence between our clustering results and other active region descriptors such as the Mount Wilson classifications and the $R$ value. We provide some recommendations for which metrics, matrix factorization techniques, and regions of interest to use to study active regions.

Context. Solar observatories are providing the world-wide community with a wealth of data, covering large time ranges, multiple viewpoints, and returning large amounts of data. In particular, the large volume of SDO data presents challenges: it is available only from a few repositories, and full-disk, full-cadence data for reasonable durations of scientific interest are difficult to download practically due to their size and download data rates available to most users. From a scientist's perspective this poses three problems: accessing, browsing and finding interesting data as efficiently as possible. Aims. To address these challenges, we have developed JHelioviewer, a visualisation tool for solar data based on the JPEG2000 compression standard and part of the open source ESA/NASA Helioviewer Project. Since the first release of JHelioviewer, the scientific functionality of the software has been extended significantly, and the objective of this paper is to highlight these improvements. Methods. The JPEG2000 standard offers useful new features that facilitate the dissemination and analysis of high-resolution image data and offers a solution to the challenge of efficiently browsing petabyte-scale image archives. The JHelioviewer software is open source, platform independent and extendable via a plug-in architecture. Results. With JHelioviewer, users can visualise the Sun for any time period between September 1991 and today. They can perform basic image processing in real time, track features on the Sun and interactively overlay magnetic field extrapolations. The software integrates solar event data and a time line display. As a first step towards supporting science planning of the upcoming Solar Orbiter mission, JHelioviewer offers a virtual camera model that enables users to set the vantage point to the location of a spacecraft or celestial body at any given time.

We present the results of time-resolved photometry, abundance analysis and Doppler imaging of an Ap star, HD 100357. The {\it TESS} photometry revealed rotational modulation with a period of 1.6279247 days. Upon inspecting the residuals after removing the rotational period and its harmonics, we found additional frequencies around 15.8054 d$^{-1}$ which we later confirmed with ground-based observations as originating from a nearby star. Using high-resolution spectroscopy, we identified HD 100357 as an Ap Si/He-wk star exhibiting rotational modulation caused by surface abundance spots. The stellar parameters of HD 100357 were determined as $T_{\rm eff}$ = 11,850 K, $\log g$ = 4.57, $\upsilon\sin i$ = 60 km\,s$^{-1}$, and an inclination angle $i$ = 72$^{\circ}$. The detailed abundance analysis revealed strongly overabundant stratified silicon, an overabundance of iron-peak elements and rare earth elements combined with remarkably deficient helium. Mapping of Fe and Cr abundances revealed the existence of ring-shaped regions with a lower concentration of the elements. Their geometry might reflect the orientation of the hypothetical magnetic field of the star, oriented $\sim$90$^{\circ}$ to the rotational axis. HD 100357, with its strong chemical peculiarities and indications of possible magnetic fields, represents an interesting candidate for follow-up spectropolarimetric observations aimed at investigating its magnetic field topology and stellar activity.

Like light, gravitational waves are gravitationally lensed by intervening massive astrophysical objects, such as galaxies, clusters, black holes, and stars, resulting in a variety of potentially observable gravitational-wave lensing signatures. Searches for gravitational-wave lensing by the LIGO-Virgo-KAGRA (LVK) collaboration have begun. One common method focuses on strong gravitational-wave lensing, which produces multiple "images": repeated copies of the same gravitational wave that differ only in amplitude, arrival time, and overall "Morse phase." The literature identifies two separate approaches to identifying such repeated gravitational-wave events based on frequentist and Bayesian approaches. Several works have discussed selection effects and identified challenges similar to the well-known "birthday problem", namely, the rapidly increasing likelihood of false alarms in an ever-growing catalogue of event pairs. Here, we discuss these problems, unify the different approaches in Bayesian language, and derive the posterior odds for strong lensing. In particular, the Bayes factor and prior odds are sensitive to the number of gravitational-wave events in the data, but the posterior odds are insensitive to it once strong lensing time delays are accounted for. We confirm Lo et al.'s (2020) finding that selection effects enter the Bayes factor as an overall normalisation constant. However, this factor cancels out in the posterior odds and does not affect frequentist approaches to strong lensing detection.

Stellar-mass black holes are the final remnants of stars born with more than 15 solar masses. Billions are expected to reside in the Local Group, yet only few are known, mostly detected through X-rays emitted as they accrete material from a companion star. Here, we report on VFTS 243: a massive X-ray faint binary in the Large Magellanic Cloud. With an orbital period of 10.4-d, it comprises an O-type star of 25 solar masses and an unseen companion of at least nine solar masses. Our spectral analysis excludes a non-degenerate companion at a 5-sigma confidence level. The minimum companion mass implies that it is a black hole. No other X-ray quiet black hole is unambiguously known outside our Galaxy. The (near-)circular orbit and kinematics of VFTS 243 imply that the collapse of the progenitor into a black hole was associated with little or no ejected material or black-hole kick. Identifying such unique binaries substantially impacts the predicted rates of gravitational-wave detections and properties of core-collapse supernovae across the Cosmos.

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 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 the 2025 release of the spectral synthesis code Cloudy, highlighting significant enhancements to the scope and accuracy of the physics which have been made since the previous release. A major part of this development involves resolving the Lyman $\alpha$ line into $j$-resolved fine-structure doublets, making Cloudy of use to the X-ray community. On this front, we have also updated inner-shell ionization line energies and incorporated the 1 keV feature commonly observed in X-ray binaries. Additionally, we update our in-house database, Stout, for the carbon isoelectronic sequence, improving Cloudy microphysical calculations for all wavelengths. We have also extended the molecular network by adding new silicon-bearing species, titanium-related reactions, and phosphorus-containing molecules, enhancing Cloudy's ability to model the complex chemistry relevant to rapidly growing field of exoplanet atmospheres. Finally, we outline future developments aimed at maximizing the scientific return from the current and upcoming generation of observatories, including XRISM, JWST, Roman, the Habitable Worlds Observatory (HWO) and NewAthena.

We have supplemented existing spectra of Barnard's Loop with high accuracy spectrophotometry of one new position. Cloudy photoionization models were calculated for a variety of ionization parameters and stellar temperatures and compared with the observations. After testing the procedure with recent observations of M43, we establish that Barnard's Loop is photoionized by four candidate ionizing stars, but agreement between the models and observations is only possible if Barnard's Loop is enhanced in heavy elements by about a factor of 1.4. Barnard's Loop is very similar in properties to the brightest components of the Orion-Eridanus Bubble and the Warm Ionized Medium (WIM). We are able to establish models that bound the range populated in low-ionization color-color diagrams (I([SII])/I(H{\alpha}) versus I([NII])/I(H{\alpha})) using only a limited range of ionization parameters and stellar temperatures. Previously established variations in the relative abundance of heavy elements render uncertain the most common method of determining electron temperatures for components of the Orion-Eridanus Bubble and the WIM based on only the I([NII])/I(H{\alpha}) ratio, although we confirm that the lowest surface brightness components of the WIM are on average of higher electron temperature. The electron temperatures for a few high surface brightness WIM components determined by direct methods are comparable to those of classical bright H II regions. In contrast, the low surface brightness HII regions studied by the Wisconsin H{\alpha} Mapper are of lower temperatures than the classical bright HII regions.

Using the astrometry and integrated photometry from the Gaia Early Data Release 3 (EDR3), we map the density variations in the distribution of young Upper Main Sequence (UMS) stars, open clusters and classical Cepheids in the Galactic disk within several kiloparsecs of the Sun. Maps of relative over/under-dense regions for UMS stars in the Galactic disk are derived, using both bivariate kernel density estimators and wavelet transformations. The resulting overdensity maps exhibit large-scale arches, that extend in a clumpy but coherent way over the entire sampled volume, indicating the location of the spiral arms segments in the vicinity of the Sun. Peaks in the UMS overdensity are well-matched by the distribution of young and intrinsically bright open clusters. By applying a wavelet transformation to a sample of classical Cepheids, we find that their overdensities possibly extend the spiral arm segments on a larger scale (~10 kpc from the Sun). While the resulting map based on the UMS sample is generally consistent with previous models of the Sagittarius-Carina spiral arm, the geometry of the arms in the III quadrant (galactic longitudes 180^\circ < l < 270^\circ) differs significantly from many previous models. In particular we find that our maps favour a larger pitch angle for the Perseus arm, and that the Local Arm extends into the III quadrant at least 4 kpc past the Sun's position, giving it a total length of at least 8 kpc.

This is a summary of the 2013 release of the plasma simulation code Cloudy. Cloudy models the ionization, chemical, and thermal state of material that may be exposed to an external radiation field or other source of heating, and predicts observables such as emission and absorption spectra. It works in terms of elementary processes, so is not limited to any particular temperature or density regime. This paper summarizes advances made since the last major review in 1998. Much of the recent development has emphasized dusty molecular environments, improvements to the ionization / chemistry solvers, and how atomic and molecular data are used. We present two types of simulations to demonstrate the capability of the code. We consider a molecular cloud irradiated by an X-ray source such as an Active Nucleus and show how treating EUV recombination lines and the full SED affects the observed spectrum. A second example illustrates the very wide range of particle and radiation density that can be considered.

Physical properties of stars such as luminosity, surface temperature, distance, or mass are measured from observations. These physical properties are of paramount importance to understand how stars are born, live, and die in the universe near and far. This chapter discusses the basic concepts used by astronomers to derive key information about stars from the light they emit. We present through a pedagogical approach the methods required for determining stellar brightness (apparent and absolute magnitudes), surface temperature (via black-body radiation and spectral classification), and distance (using parallax and standard candles). We finally review techniques for estimating stellar mass and radius, including the use of binary star systems and stellar evolution models.

Setting up a relativistic lunar reference frame is of a prime importance in the context of future exploration missions to the Moon. If the procedure for building a consistent reference frame within the framework of the general theory of relativity is well established (cf. resolutions B.3 of IAU 2000), there is still some freedom in the choice of the coordinate timescale to be adopted as reference in the cislunar region. In this paper, we review the orders of magnitude of the relativistic effects resulting from (i) the gravitational redshift of a clock on the lunar surface and (ii) the time transformations between a clock on the surface of the Moon and a clock on the surface of the Earth. We then discuss possible options for a lunar reference timescale with their advantages and drawbacks. Finally, we propose possible realizations of the lunar reference timescale as well as its traceability to UTC.

Many natural processes exhibit power-law behavior. The power-law exponent is linked to the underlying physical process and therefore its precise value is of interest. With respect to the energy content of nanoflares, for example, a power-law exponent steeper than 2 is believed to be a necessary condition to solve the enigmatic coronal heating problem. Studying power-law distributions over several orders of magnitudes requires sufficient data and appropriate methodology. In this paper we demonstrate the shortcomings of some popular methods in solar physics that are applied to data of typical sample sizes. We use synthetic data to study the effect of the sample size on the performance of different estimation methods and show that vast amounts of data are needed to obtain a reliable result with graphical methods (where the power-law exponent is estimated by a linear fit on a log-transformed histogram of the data). We revisit published results on power laws for the angular width of solar coronal mass ejections and the radiative losses of nanoflares. We demonstrate the benefits of the maximum likelihood estimator and advocate its use.

Solar flares are the most powerful, magnetically-driven, explosions in the heliosphere. The nature of magnetic energy release in the solar corona that heats the plasma and accelerates particles in a flare, however, remains poorly understood. Here, we report high-resolution coronal observations of a flare (SOL2024-09-30T23:47) by the Solar Orbiter mission that reveal initially weaker but rapid reconnection events, on timescales of at most a few seconds, leading to a more prominent activity of similar nature that explosively cause a flare. Signatures of this process are further imprinted on the widespread raining plasma blobs with short lifetimes, giving rise to the characteristic ribbon-like emission pattern associated with the flare. Our novel observations unveil the central engine of a flare and emphasize the crucial role of an avalanche-like magnetic energy release mechanism at work.