Papers for Tuesday, Apr 28 2026

Dust substructures observed in protoplanetary disks are commonly attributed to embedded planets; however, intrinsic gas-dust interactions can also generate complex morphologies. We performed two-dimensional, axisymmetric simulations of gas and dust that include dust back-reaction and parameterized turbulence to investigate how the streaming instability (SI) and vertical shear instability (VSI) shape dust distributions. With moderate viscosity and sufficiently high metallicity, we identify a characteristic shuttlecock-shaped dust substructure composed of a dense, vertically settled "head" and a vertically extended "tail." This morphology arises from nonlinear SI driven by marginally coupled grains and the associated modification of gas flows. The dust scale height in the tail exceeds predictions based on the simple diffusion-settling balance, indicating strong self-generated turbulence. With lower viscosity, VSI becomes more vigorous, disrupts midplane structures, and increases vertical stirring; nevertheless, for dust grains with Stokes numbers around 0.01, SI can still attain dust-to-gas ratios of up to 20-50, potentially approaching the Hill density for gravitational binding. Our results demonstrate that intrinsic gas-dust interactions can generate prominent dust substructures even in disks with finite viscosity and, under favorable conditions, concentrate dust to levels relevant for planetesimal formation.

The Lighthouse pulsar (PSR J1101$-$6101) sports a bright X-ray trail and filament. The synchrotron emission from both structures is expected to be polarized, with electric vector position angle (EVPA) perpendicular to the magnetic field direction and polarization degree (PD) indicating the local degree of magnetic turbulence. We present a 1 megasecond Imaging X-ray Polarimetry Explorer (IXPE) observation of the Lighthouse complex. At the 99% confidence level, we detect the filament polarization with PD $55 \pm 18\%$ and EVPA indicating a magnetic field parallel to the filament axis. The large PD implies a turbulent magnetic field weaker than the background field, in conflict with some existing models. We also detect polarization from the pulsar and trail. The trail's X-ray polarization is nearly orthogonal to the radio polarization, suggesting spatial separation between the X-ray- and radio-emitting leptons. The pulsar polarization is well-fit by the rotating vector model.

Future weak lensing analyses with the Nancy Grace Roman Space Telescope will require highly realistic image simulations to control shear systematics at unprecedented precision. A key limitation of existing approaches is their reliance on analytic light-profile models, which cannot fully capture the complex, non-parametric morphologies revealed by high-resolution observations. We present a diffusion-based framework for generating realistic galaxy image simulations tailored to the weak lensing requirements of the Roman High Latitude Survey. We construct Roman-like galaxy images from multi-band JWST/NIRCam observations in the GOODS-S and GOODS-N fields, transforming them into the Roman observing regime through point-spread-function matching, pixel-scale conversion, and interloper masking that preserves correlated noise properties. These data are used to train a denoising diffusion probabilistic model to generate multi-band galaxy postage stamps in the Roman Y, J, and H filters. We validate the generated sample against an independent dataset using a consistent photometric pipeline, comparing key galaxy observables including magnitude, size, ellipticity, peak surface brightness, and three-band colors. The generated galaxies reproduce both the marginal distributions and the covariance structure of these properties, with only modest deviations in low-occupancy regions of parameter space. These results demonstrate that diffusion models provide a scalable and physically motivated alternative to analytic simulations, enabling high-fidelity galaxy populations for Roman weak lensing calibration and, more generally, for survey preparation in upcoming cosmological experiments.

Cosmological simulations of galaxy clusters are unable to resolve dwarf galaxies due to limited numerical resolution which drives the artificial disruption of dark matter substructures. We address these limitations by combining the results of the cosmological hydrodynamical simulation TNG50 in $\Lambda$CDM with an empirical model of tidal evolution of cluster galaxies calibrated using high-resolution idealized N-body simulations. Applied to the three most massive clusters in TNG50, our model allows us to study the stellar mass and radial distribution of dwarfs well below the formal resolution limit of the parent simulation. We find that, at $z=0$, clusters with virial mass $M_{200} \sim 10^{14}~\mathrm{M_\odot}$ host a vast population of dwarf galaxies within the virial radius, amounting to $2000$-$7000$ systems with $M_* > 100~\mathrm{M_\odot}$. Taken together, these satellites follow a radial distribution that matches the underlying dark matter profile of the host. However, applying a minimum mass or luminosity threshold for detection, as expected in observational studies, tends to exclude the most heavily-stripped objects, which tend to populate the inner regions. Future surveys targeting ultra-faint galaxies in group and cluster environments, such as those made possible by the Euclid, Rubin, or Roman telescopes, will be fundamental to refute or confirm this prediction.

Green valley (GV) galaxies are thought to represent a transitional population between star-forming and quiescent systems. However, their spatial distribution relative to galaxy systems remains unclear, particularly in relation to the large-scale environmental influence on galaxy quenching. We aim to determine whether GV galaxies preferentially inhabit specific environments within galaxy systems. We analyse the spatial distribution of GV galaxies using the cluster-galaxy cross-correlation function (CCF), based on the hydrodynamical simulation Illustris TNG300-1 (TNG) and observational data from the Sloan Digital Sky Survey (SDSS). Galaxy systems with $\log(M_{200}/M_{\odot}) \geq 13.5$ are used as cluster centres, while galaxies classified as blue, green, or red serve as tracers for the correlation analysis. In TNG, GV galaxies show an increasing relative fraction with cluster-centric distance, peaking in the outskirts, particularly for low-mass galaxies and haloes, and in some cases the GV fraction exceeds that of red galaxies. SDSS data reveal qualitatively similar trends, with the GV fraction remaining below that of red galaxies at all scales. Mock catalogues built from TNG and matched to SDSS selection functions reproduce the observational signal, indicating that projection effects drive the differences between datasets. GV galaxies preferentially reside in the outskirts of galaxy systems as satellites bound to the central halo, supporting a scenario in which they are transitioning objects influenced by environmental quenching.

Ultra-fast outflows (UFOs) are mildly relativistic (outflow velocity $v_{out}>0.1c$) nuclear winds detected as blueshifted absorption lines from highly ionized, dense gas in the X-ray spectra of active galactic nuclei. The AGN feedback mechanism is believed to be powered by these outflows, which can inject a large amount of energy and momentum into the surrounding interstellar medium, shaping the coevolution of the AGNs and their host galaxies. We performed a systematic search and rigorous statistical assessment of the presence of UFOs in the 7-12 keV band, in a sample of bright local AGNs. This study also aims to understand whether the presence and characteristics of UFOs depend on the state of the sources, by studying the relations between the incidence of UFOs and the accretion properties of AGNs. We collected X-ray spectroscopic flux-limited XMM data of 33 observations of local (z<0.2) type 1 AGNs. We modeled their spectra in the 2-12 keV band using a combination of direct-continuum and reflection components and searched for absorption features. This represents the first systematic search for UFOs up to 12 keV. We performed Monte Carlo simulations to assess the statistical significance of the detected lines. We report strong detections of UFOs in six sources of the sample at the >95% confidence level via MC simulations, corresponding to a fraction of 18% in our sample. From the observed energies of each absorption line, we evaluated the respective wind velocities, which in some cases exceed 40\% of the speed of light. The velocity distribution found in this work is therefore shifted to higher energies than those found in previous searches for UFOs in local sources, which were limited to 10 keV. Moreover, our analysis shows no correlation between the accretion properties of the SMBHs and the presence of winds. Furthermore, our study highlights the temporal variability of UFOs.

Numerical simulations have established that star clusters with densities comparable to the high redshift ($z>6$-$10$) James Webb Space Telescope (JWST) proto globular clusters may build up extremely massive (EMSs; $m_\mathrm{\star}>1000 M_\odot$) or even supermassive stars (SMSs; $m_\mathrm{\star}>10000 M_\odot$) and potentially intermediate mass black holes (IMBHs) through runaway stellar collisions. Using direct simulations of assembling star clusters including post-Newtonian black hole dynamics and stellar evolution, we demonstrate that in such dense environments ($\Sigma_\mathrm{h} \gtrsim 10^6 M_\odot$pc$^\mathrm{-2}$) stellar BHs ($m_\bullet \lesssim 60 M_\odot$), driven by rapid mass segregation and relaxation effects within the sphere of influence of the EMSs/SMSs, may strongly interact with the extremely massive stars and become embedded within their gaseous layers. We suggest that this quasi-star (QS) like embedded BH phase is a natural outcome of the runaway formation of EMSs/SMSs in the densest star clusters. The QS phase is orders of magnitude longer in duration than the lifetime of the SMS, enabling an extended growth period by stellar collisions, and allows the formation of embedded gravitational wave sources if the QS captures more than a single stellar BH. The star cluster assembly region sizes ($\sim100$ pc), QS masses ($\gtrsim 10^4 M_\odot$) and their proximity to young, massive blue star forming clumps are consistent with the faint population of multiple little red dots (LRDs) recently discovered by the JWST.

Observations of type Ia supernovae (SNe Ia) have led to suggestions of multiple progenitor and explosion scenarios. Distinguishing between scenarios and tying specific SNe Ia to individual scenarios however has so far been challenging. Constraints on the explosion physics are often achieved through empirical modelling of SNe Ia spectra and qualitative assessments of the level of agreement. While this approach has provided useful insights, it cannot be scaled up to large numbers of SNe Ia in a robust and systematic way. As a machine learning based framework for automated and quantitative fitting of SNe Ia, riddler is designed to overcome these limitations. Neural networks are used as radiative transfer emulators and, in conjunction with nested sampling, emulated spectra are fit to observations of SNe Ia to determine the best-fitting input parameters and explosion scenario. In this work, we present recent improvements to riddler, including a significantly expanded training dataset covering pure deflagrations, delayed detonations, double detonations, gravitationally confined detonations, and violent mergers. We show that despite the increased complexity and variety of our training data, riddler is able to accurately recover the input parameters and explosion scenario of spectra unseen during training. Using riddler, we fit observations of three SNe Ia covering different sub-classes: SN 2011fe, SN 2005hk, and SN 2018byg. We detail a number of limitations and assumptions that should be considered when applying similar approaches. Nevertheless, the benefits of this approach and riddler will result in automated fitting playing an increasingly important role in the coming years.

The physics driving type Ia supernovae (SNe~Ia) standardisation in cosmology remains poorly-understood. Recent advances however mean that it is now possible to systematically analyse the explosion properties of large numbers of cosmological SNe~Ia. To that end we use riddler, a machine learning based framework for rapidly modelling SNe~Ia based on realistic explosion simulations, to perform quantitative spectral modelling of the Zwicky Transient Facility SN~Ia DR2 sample and determine their best-fitting explosion mechanism(s). We find that approximately two thirds of our sample is best reproduced by sub-Chandrasekhar mass explosions. Analysing their light curve and host galaxy properties, we find that Chandrasekhar mass explosions are not favoured for the fastest-evolving SNe~Ia, while sub-Chandrasekhar mass explosions are favoured for the reddest SNe~Ia. Due to the differences in their environments, selecting SNe~Ia in massive, passive galaxies could produce a homogeneous sample of violent merger SNe~Ia. We show that standardising each explosion mechanism independently reduces scatter in distance estimates and previously claimed environmental and non-linear light curve shape corrections may be due to changes in the relative populations of different explosion mechanisms. Although a step forward towards understanding SNe~Ia physics in cosmology, we highlight a number of limitations affecting our conclusions, including sample biases and small numbers. We therefore cannot assess the statistical significance of our results and they should be treated with caution. Larger and more uniformly observed samples will be key to determining the significance of any trends hinted at here.

We present results from a multi-epoch Very Long Baseline Array (VLBA) survey conducted as part of the DYNAMO-VLBA project, aimed at measuring the dynamical masses of young stellar systems in the Orion complex. Our observations include 19 radio sources associated with 15 binary or multiple young systems. For four visual binaries in which both components were detected, the derived Keplerian orbits yield model-independent stellar masses; in particular, Brun~656 and HD~294300 show excellent agreement between VLBA-based and spectral-energy-distribution-based estimates, providing valuable benchmarks for pre-main-sequence evolutionary models. The component NU Ori C is confirmed as an intermediate-mass ($\sim$7\,M$_\odot$) star with nonthermal radio emission, offering rare evidence of magnetic activity near the boundary with the high-mass regime. Several additional sources exhibit astrometric accelerations or periodic residuals, revealing unseen companions and extending dynamical constraints to systems with only one radio-emitting component. These results highlight the capability of very long baseline interferometry astrometry to obtain precise and model-independent masses of young binaries, providing critical empirical anchors for stellar evolution models and new insights into the origin of magnetism in intermediate-mass stars.

We present JWST NIRSpec and NIRCam observations of 457P/Lemmon-PANSTARRS, a main-belt comet that displayed activity around its 2020 perihelion and that was observed to regain activity during its 2024 perihelion by a ground-based observing campaign. The previous successful measurements of water production from two main-belt comets by the JWST NIRSpec instrument confirmed the hypothesis that H2O reservoirs are responsible for activity in dynamically stable main-belt comets. However, the main-belt comets observed with JWST thus far, 238P/Read and 358P/PANSTARRS, occupy orbits in the outer main-belt, with main-belt comets with smaller semi-major axes not yet sensitively tested for H2O. We find that despite clearly displaying dust activity in both ground-based and JWST imaging over a broad period, there were no corresponding H2O, CO, CO2, or CH3OH emissions within sensitive upper limits; notable given 457P is the first main-belt comet with a semi-major axis within the 5:2 mean-motion resonance with Jupiter. We show that we were sensitive to production rates of gas predicted by the dust/gas ratios of 238P and 358P, and hypothesize that 457P may be more depleted than its companions; Q(H2O) must be less than 2x10^24 molecules/s, or 0.035 kg/s. Further surveying of main-belt comets across the parameter space of semi-major axis and eccentricity will shed light on whether 457P represents an edge member of a spectrum or a distinct subclass of main-belt comets.

We report results from an analysis of the volatile composition and evolution of main-belt comet (MBC) 133P/Elst-Pizarro using JWST NIRSpec and NIRCam observations and ground-based observations during its 2024 active apparition, and also assess the body of JWST MBC observations acquired to date. Using NIRSpec, we measure water vapor outgassing rates at two points in 133P's orbit, finding Q(H2O)=(1.9+/-0.6)x10^25 molecules/s on UT 2024 June 12 (at a true anomaly of nu=8 deg and heliocentric distance of rh=2.674 au), and Q(H2O)=(1.4+/-0.4)x10^25 molecules/s on UT 2024 October 14 (at nu=37.4 deg and rh=2.747 au). These measurements nominally represent a decline of ~25% in Q(H2O) between the visits, although they are also consistent with no change within uncertainties. We do not detect CO, CO2, or CH3OH, placing 133P's hypervolatile depletion (Q(CO2)/Q(H_2O)<0.009) at a similar level found for previously observed MBCs. We find log(Afrho/Q(H2O)) values for the three MBCs for which water vapor outgassing has been successfully detected that are consistent within uncertainties with an average value of log(Afrho/Q(H2O))=-24.6+/-0.2. Lastly, we find no clear correlations of water production rates with nucleus size, semimajor axis, or heliocentric distance among MBCs observed by JWST so far, but would particularly encourage future JWST observations of additional MBCs interior to the 5A:2J MMR with Jupiter and at high inclinations, as well as multiple observations of MBCs during single active apparitions to further investigate areas of interest identified from the current sample of JWST-observed MBCs.

Planetary systems can act as sensitive gravitational detectors for dark matter. We investigate the gravitational scattering of Oort cloud objects by primordial black holes (PBHs) as a potential component of the Galactic dark matter halo. Calculating the rates at which PBH encounters eject objects from the Oort cloud or inject them into Earth crossing orbits, we find a linear scaling $\Gamma \propto m_{\mathrm{PBH}}$ for $m_{\mathrm{PBH}} \gtrsim 10^{-10} M_\odot$. For $m_{\mathrm{PBH}} \sim 10^3 M_\odot$, PBHs constituting all local dark matter would eject $\sim1.3\times10^{12}$ objects over the Solar System's lifetime, comparable to the total Oort cloud population and inject $\sim2.6\times10^{10}$ objects into Earth-crossing orbits. Comparing these rates with observational constraints from long period comet fluxes and terrestrial impact records, we derive upper limits on the PBH dark matter fraction $f_{\mathrm{PBH}}$. Our most stringent constraints exclude $f_{\mathrm{PBH}}=1$ for $10^2 M_\odot \lesssim m_{\mathrm{PBH}} \lesssim 10^5 M_\odot$, with $f_{\mathrm{PBH}} \lesssim 0.002$ at $m_{\mathrm{PBH}} = 10^3 M_\odot$. For the asteroid mass window ($10^{17}$-$10^{23}$ g), scattering rates are far too low to produce observable effects. These Solar System-based constraints complement existing astrophysical probes and demonstrate that planetary systems can serve as sensitive gravitational detectors for compact dark matter.

This paper examines interacting dark energy models within the Chevallier-Polarski-Linder (CPL) parametrization, emphasizing both theoretical structure and observational viability. Two commonly adopted interaction terms are considered: $Q = \beta H \rho_{de}$ and $Q = \beta H \rho_c$. We derive exact analytic solutions that describe how the dark sector evolves. These solutions involve incomplete gamma functions and reveal a non-trivial mathematical structure that is often missed in numerical analyses. We perform a Bayesian analysis using current cosmological observations, including the Hubble parameter (OHD), Type Ia supernovae (SNIa), baryon acoustic oscillations (BAO), and cosmic microwave background (CMB) data. Relative to the non-interacting CPL scenario, the interacting model with $Q = \beta H \rho_{de}$ yields a modestly improved fit, as indicated by the Akaike Information Criterion (AIC). However, the Bayesian Information Criterion (BIC) penalizes increased model complexity, leading to a continued preference for $\Lambda$CDM. In contrast, the interaction model that depends on dark matter density does not provide observational support. The preferred interacting scenario indicates that the dark energy equation of state evolves dynamically, transitioning from an effective phantom regime at high redshift to quintessence-like behavior at late times. Further analysis indicates the potential for a transient phase of cosmic acceleration in the future. These findings suggest that interacting dark energy models within the CPL framework enrich the standard cosmological model by introducing more diverse phenomenology while maintaining consistency with current observations.

We present an analysis of the temperature structure of the Perseus cluster atmosphere using XRISM Resolve observations. The average temperature rises from 3.3 keV near the nucleus of NGC 1275 to 8 keV at 10 arcmin (210 kpc), which is consistent with Chandra and XMM measurements. The velocity and velocity dispersion profiles are broadly consistent with those in arXiv:2509.04421. While the gas at altitudes beyond $\sim60$ kpc can be modeled as a single temperature plasma, we find evidence for more than one gas phase in the inner $\sim60$ kpc. The hotter gas component, traced primarily by the Fe He$\alpha$ line, has a velocity dispersion of $\lesssim140$ km s$^{-1}$. We detect a cooler, $\sim1.87-2.43$ keV, gas component with a velocity dispersion of $\sim300-400$ km s$^{-1}$ and a bulk velocity of $\sim 21-213$ km s$^{-1}$ with respect to the central galaxy. These ranges reflect large systematic uncertainties associated with modeling spatial-spectral mixing and the bright central point source. Potential low energy gain variations may add additional uncertainties. The cooler component is identified by broad wings in prominent emission lines, most notably S Ly$\alpha$ and Fe He$\alpha$. This cooler component's Mach number $\sim0.73-0.96$ and non-thermal pressure fraction of $\sim22.9-33.7\%$ are much higher than found for the hotter gas. The cooler gas may be associated with merging halos along the line of sight which formed the cool, sloshing spiral and/or cooling gas being disturbed by the radio jets and lobes.

The Solar Neighborhood is dominated by stars smaller, colder, and fainter than the Sun: the M dwarfs. If we are to understand the context in which the Sun formed and evolved, then we must investigate the system architectures of our low-mass neighbors. We have therefore carried out the Pervasive Overview of Kompanions of Every M Dwarf in Our Neighborhood (POKEMON) speckle survey of nearby M-dwarf primaries. We created the survey with the goal of observing a volume-limited (north of -30 degrees) sample of M-dwarf primaries through M9 out to 15 pc at diffraction-limited resolution. Pre-Gaia parallax measurements yielded a catalog of 454 nearby M-dwarf primaries. However, the precise astrometry from Gaia indicated that there are additional low-mass sources within 15 pc. Here we present the POKEMON-Distance Limited Catalog (POKEMON-DLC), a supplemental catalog that consists of speckle observations for the 66 additional M-dwarf primaries identified by Gaia, increasing the number of ultracool dwarf (later than M6.5) primaries in the POKEMON catalog by a factor of 1.6. In our observations we detect four likely bound companions. After carrying out a literature search for additional companions, we update the projected separation distribution and find a peak at 7.91 au ({\sigma}log(a) = 1.1, SElog(a) = 0.10). We also update the M-dwarf stellar multiplicity and companion rates, and find values of 22.7 p/m 1.8% and 27.5 p/m 2.0%, respectively. These results emphasize the utility of Gaia for identifying low-mass, nearby sources, and we find that ensuing characterization of these sources by SPHEREx will continue to clarify the nature of the Solar Neighborhood.

We use machine learning to develop a framework for classifying meteoroids based on 13 directly observed parameters from the Global Meteor Network. This method adds depth to the $K_{b}$ parameter, which uses only three parameters. We employ a semi-qualitative approach using 28,177 meteor events observed in 2023 by the Lowell Observatory Cameras for All-Sky Meteor Surveillance (LO-CAMS) network to evaluate multiple normalization, dimensionality-reduction, and clustering algorithms. We find that a combination of Factor Analysis (FA) and a Gaussian Mixture Model (GMM) results in clusters most consistent with traditional models. Three FA-derived factors corresponding to meteoroid kinematics, activation thresholds, and size/geometry effects describe the underlying structure of meteoroid behavior. The activation factor emerged as the most discriminating factor distinguishing whether a meteor is of asteroidal or cometary origin. Resulting 3, 6, and 11 cluster models reveal progressively finer compositional structure, from broad physical regimes to detailed subdivisions within cometary and asteroidal populations. From these results, we introduce a physically motivated hardness classification scheme: $H_{\mathrm{class}}$. $H_{\mathrm{class}}$ is a data-driven extension of $K_{b}$ which physically interprets clusters in terms of the densest iron meteoroids down to the softest cometary material. Application to nine well-studied meteor showers and analysis of clusters in orbital space aids in the physical interpretation of $H_{\mathrm{class}}$ groups. The $H_{\mathrm{class}}$ model is supported by an analytical FA-GMM formulation that enables application to future datasets. Our results demonstrate that machine learning methods can extract compositional information from modern optical meteor datasets at scale and offers a new framework for interpreting meteoroid populations.

Real-time ranking of optical transient candidates during gravitational-wave (GW) and multimessenger follow-up is challenging when only sparse early-time, multi-band photometry is this http URL present \texttt{KilonovaSCORER}, an open-source framework for scoring and ranking in this regime. It quantifies the consistency of each candidate with a physically motivated kilonova model grid in absolute magnitude space using two complementary per-observation metrics, $P_{\mathrm{tail},\mathrm{KNe}}$ and $P_{\mathrm{near},\mathrm{KNe}}$. These are aggregated into a cumulative ranking score via inverse-variance weighting in logit space, naturally accounting for heterogeneous observational uncertainties across bands and epochs. A sequential Approximate Bayesian Computation (ABC) diagnostic tracks photometric consistency across epochs, penalizing candidates whose temporal evolution is incompatible with kilonova expectations. We validate the framework on AT\,2017gfo and SN\,2025ulz, and test it against supernova simulations under a realistic Rubin/LSST Target-of-Opportunity strategy. The framework recovers kilonova candidates with high confidence while ruling out supernova contaminants within five days of the gravitational-wave trigger. In our LSST ToO simulations, median cumulative scores for thermonuclear and core-collapse supernova contaminants fall to zero by $3$--$4$\,d post-trigger, whereas kilonova medians remain $\gtrsim 0.4$. \texttt{KilonovaSCORER} supports real-time workflows for ToO teams and LSST alert brokers, integrates with follow-up coordination platforms such as the Tool for Rapid Object Vetting and Examination, and is publicly available at this https URL.

While there has been significant progress in our understanding of the origin and evolu-tion of planetary nebulae in the last 50 years, there remain several unsolved problems. These include the true 3D morphological structure of the nebulae, origin of multipolar nebulae, the dust and molecular distribution relative to the optical nebulosity, large-scale structures outside of the main nebulae, the relevance of binarity to planetary nebulae evolution, and a precise definition of the planetary nebula phenomenon. The long-standing problem of elemental abundance discrepancy still remains unsolved. In this paper, we summarize current observations related to these problems and present possible future directions to tackle them.

Solar eruptions are sudden ejections of coronal mass and magnetic fields accompanied by intense energy release. The eruptive structure does not always erupt successfully, but sometimes fails to escape the Sun after initiation. The failure of an eruption, however, provides an invaluable opportunity for understanding the intricate mechanism of eruptions. We present a comprehensive observation of a failed prominence eruption on the Sun, taking advantage of multi-viewpoint and multi-messenger imaging. Simultaneous off-limb and on-disk observation gives evidence of magnetic reconnection processes occurring at different sites during the flare. Particularly, in addition to the standard flare reconnection behind the eruption, strong external reconnection occurs on the erupting flux rope, evidenced by a wealth of signatures via multi-wavelength imaging and spectroscopy. The two reconnection processes may play contrasting roles in the flux rope's acceleration and compete in altering the magnetic flux in the rope. As the high rate of external reconnection proceeds, the flux rope and embedded prominence decelerate noticeably and fail to erupt into the heliosphere, under strong magnetic confinement of overlying fields. Our results illustrate a well-defined physical picture for solar eruptive activities and provide insight into the lack of coronal mass ejections found in other solar-type stars.

A rare multiple open cluster system has been analyzed using Gaia DR3 astrometry and photometry data. Using Agglomerative Hierarchical clustering and Bayesian-HDBSCAN, we identify a compact core consisting of seven known open clusters and two additional components, including a new candidate, forming a nine-member association. Membership probabilities are refined through statistical modeling, combining GUMM, Bayesian-KDE, and Bayesian-XDGMM for tidal tails identification. Backward orbital integrations confirm coherent motions over 20-30 million years, suggesting a common origin from the same massive molecular cloud. This system offers a unique laboratory for investigating cluster multiplicity, dynamical evolution, and Galactic structure.

The origin of ultra-high-energy cosmic rays (UHECRs) remains a fundamental question in astroparticle physics. While localized 3 $\sigma$ correlations with active galactic nuclei and starburst galaxies have been reported using time-integrated analyses, we propose and implement a spatiotemporal multiplet search method utilizing a pre-defined fixed window of 3 degrees and 15 days, a kinematic filter designed to isolate high-rigidity particles and keep chance coincidences low. Applying this method to 16 years of Pierre Auger Observatory data, we identify 28 UHECR multiplets (doublets) above 32 EeV. We backtrack these trajectories using three Galactic magnetic field models across eight distinct nuclear species. Testing the backtracked directions against the ten nearest bright radio galaxies yields an overall post-trial significance of 5.8 $\sigma$, conditioned on the individual best-fit associations. Specifically, we find a 4.5 $\sigma$ conditional post-trial significance for the joint association of 8 of these multiplets with the Fornax A region alone. These results point to radio galaxies, with a strong contribution from Fornax A, as long-term accelerators of heavy (Z > 3) UHECRs, possibly within the mildly relativistic backflows of their extended radio lobes, detected at Earth primarily as independent secondary fragments above 32 EeV.

Using \textit{Hubble Space Telescope} images from the PHAT and PHAST surveys, we construct an updated catalogue of 747 OB cluster (OBC) candidates. We introduce a dimensionless structural metric, the trace coefficient of variation ($CV_{\rm tr}$), derived from the Hessian matrix in four \textit{HST} bands, to quantify the internal photometric substructure of partially resolved OBC candidates. Cross-matching with the subset of M31 clusters that have independent colour--magnitude diagram (CMD) age estimates yields 247 objects in common. We find statistically significant anti-correlations between $CV_{\rm tr}$ and age in the UV and blue bands, suggesting a progressive smoothing of the light distribution as clusters evolve. Bootstrap resampling confirms the robustness of these trends. Forward modelling of synthetic clusters analysed with the same pipeline recovers a monotonic $CV_{\rm tr}$--age relation under simplified but physically motivated assumptions. These results show that second-order photometric structure contains measurable evolutionary information within the CMD-calibrated regime ($\sim10$--300~Myr).

We construct mean spectral energy distributions (SEDs) for a substantial sample of 56,969 Sloan Digital Sky Survey DR16 quasars with $z < 0.75$, utilizing multiwavelength data from the mid-infrared (MIR) to ultraviolet (UV). These SEDs are built on eigenvector 1 parameters -- the relative optical $\rm Fe~ II$ strength ($R_{\rm Fe~II}$) and the H$\beta$ line width ($\rm H\beta$) -- that capture the principal spectral variance of quasar spectra. From three $R_{\rm Fe~II}$-dependent mean SEDs we find that quasars with a larger $R_{\rm Fe~II}$ exhibit redder UV and optical and redder MIR and near-infrared (NIR) continua, indicating more dust emission. We also split our sample directly into Eddington ratio $L_{\rm Bol} /L_{\rm Edd}$ (or dimensionless accretion rate $\dot{\mathscr{M}}$) bins to construct different mean SEDs and find that the continua become increasingly red with increasing $L_{\rm Bol} /L_{\rm Edd}$ (or $\dot{\mathscr{M}}$) in the MIR, NIR, and UV bands. This demonstrates that the shapes of Type 1 AGN SEDs depend on the accretion rate. However, the optical continuum shows the opposite trend (becoming harder and bluer), indicating the complexity of the optical emission region. From $\rm FWHM_{H\beta}$-dependent mean SEDs we find that quasars with a larger $\rm FWHM_{H\beta}$ show redder optical and NIR continua and bluer UV and MIR continua. The bluer MIR continuum suggests that a larger angle between of the line of sight and the torus plane results in weaker torus emission in the MIR.

The next few years will be critical for technology development for Habitable Worlds Observatory (HWO) in its mission to search for and characterize extrasolar planets. To achieve its stated goals with contrasts of one part in ten billion, HWO will require outstanding stability and precision, particularly in measuring and controlling the wavefront of the light propagate through the telescope and coronagraph system. We present simulations for the Photonic-Enabled ExoPlanet Spectroscopic Sensor (PEEPSS), which uses a set of photonic lanterns to efficiently couple light from the "dark hole" in the coronograph focal plane (where the exoplanets are expected to lie) into single-mode fibers and the main spectrograph. PEEPSS uses rejected host star light from the region interior to the dark hole to aid in the wavefront sensing; this has the advantage of doing the sensing in the coronograph focal plane, eliminating non-common-path errors between the wavefront sensing and science channels. The photonics lanterns allow us to combine our science channel and wavefront sensor into a single system. PEEPSS will be particularly advantageous provide in the near-infrared (NIR) bandpass, which is of particular interest for HWO. Because the limiting inner working angle (IWA) of a coronagraph scales as wavelength over diameter, exoplanet imaging in the NIR becomes a major challenge as the IWA can exceed the exoplanet orbital radius. PEEPSS will enable NIR coronagraphic observations at smaller IWA than other approaches, increasing the observational parameter space HWO can probe in the search for exoplanets.

Understanding how galaxy populations emerge and evolve from the growth of dark matter structure is a central challenge in galaxy formation theory. Semi-analytic models (SAMs) provide an efficient framework to address this problem, but exploring large ensembles of merger trees across broad parameter spaces remains computationally demanding. We develop a conditional graph neural network surrogate model that combines merger tree information with SAM parameters to predict galaxy properties across cosmic time. Using merger trees of dark matter halos from the Uchuu simulation and the Galacticus SAM, the model predicts stellar mass, luminosity, angular momentum, gas metal mass, and specific star formation rate across the wide redshift range of 0 <= z <= 5. For instance, the model can predict stellar mass at 0 <= z <= 3 with a scatter of 0.19-0.28 dex and coefficient of determination R^2 of 0.946-0.973 (R^2 close to 1 indicates prediction closely matching the truth). The results show that a single graph based model can reproduce these galaxy properties with good accuracy over multiple SAM realizations, merger trees and redshifts. This catalog-level model provides a practical route for accelerating SAM based studies of galaxy formation to enable a more detailed investigation of the model parameter space. The inference code, trained models, and example data products are publicly available at this https URL.

Cygnus X-3, hosting a Wolf-Rayet (WR) star whose dense wind produces various spectral lines due to photoionization by X-rays from a compact object, provides an ideal laboratory for studying wind dynamics and density structure. We measured the orbital modulations of the Fe, Ca, Ar, and S Ly$\alpha$ lines observed with the X-ray microcalorimeter (Resolve) onboard the $XRISM$, taking account of both emission and absorption lines of the Ly$\alpha$ complexes. The modulations of Doppler shifts of the Fe, Ca, Ar, and S Ly$\alpha$ lines showed amplitudes of 500 km s$^{-1}$ and phase offsets of 0.04, 0.09, 0.11, and 0.17, respectively, in units of an orbital period (4.8 hours) relative to the orbital motion of the compact object. This result indicated that H-like Fe most closely follows the compact object's motion. The line widths ranged from 400 to 1000 km s$^{-1}$. The intensities of both emission and absorption lines reached their minima around orbital phase 0.0 and their maxima around phase 0.5. The absorption peaks, however, did not align exactly with phase 0.5, suggesting the inhomogeneous structures such as an accretion wake and/or a bow shock. We compared the observed modulations with calculations based on a stellar wind model, accelerated by ultraviolet radiation from the WR star. One of the calculations qualitatively reproduced the observed trend that H-like Fe ions were concentrated near the compact object, whereas H-like S was distributed across the binary system, with H-like Ca and Ar showing intermediate spatial distributions. From this comparison, we estimated that a mass-loss rate of the stellar wind was approximately $5 \times 10^{-6}$-$1 \times 10^{-5}\ M_{\odot}\ {\rm yr}^{-1}$.

DRACuLA (Detector irRAdiation Cryogenic faciLity for Astrophysics) is a mobile dilution refrigerator platform developed at the Institut d'Astrophysique Spatiale (IAS) to expose sub-Kelvin detectors to particle beams at their nominal operating temperature, in the range 50-300 mK. We report on its design, beam-line integration at the Particle Therapy Research Center (PARTREC) in Groningen, and the operational performance achieved during the September 2025 irradiation campaign on Kinetic Inductance Detector (KID) arrays developed by SRON for the PRIMA mission. The detector samples were maintained at 120 mK throughout a 12-hour proton irradiation run at 184 MeV. The scientific results of this campaign are reported in the companion paper by Besnard et al.

Preheating after inflation proceeds through parametric resonance, leading to efficient particle production in scalar field models. In this work, we investigate the structure of parametric resonance in the $\phi^4$ chaotic inflationary model during the preheating phase by performing a fully numerical analysis of the coupled dynamical equations governing the inflaton field and the mode function of the produced particles, thereby avoiding the approximations commonly employed in earlier studies. Our results reveal resonance patterns that differ significantly from those obtained with approximate analytical treatments. In the weak coupling regime, short-wavelength modes rapidly settle into oscillations with nearly constant amplitude, while the corresponding occupation numbers approach saturation. However, the long-wavelength modes exhibit gradual amplitude growth, with occupation numbers transitioning into a non-linear oscillatory regime. As the coupling strength increases, the dynamics becomes increasingly nonlinear, leading to the emergence of stochastic behavior. In the strong coupling regime, short-wavelength modes display a step-like (staircase) evolution in the occupation number, indicative of intermittent bursts of particle production. However, the long-wavelength modes exhibit a more gradual, monotonic growth with small superimposed fluctuations. These findings highlight the rich, coupling-dependent, structure of parametric resonance in the quartic inflationary model and underscore the importance of exact numerical treatment in accurately capturing preheating dynamics.

The galaxy luminosity and stellar mass function (LF, SMF), and halo mass function (HMF), are fundamental quantities in astrophysics and crucial inputs to a range of astrophysical and cosmological analyses. They are typically parametrised by fitting functions that have been chosen "by eye" to match observed or simulated data. We apply symbolic regression -- specifically the Exhaustive Symbolic Regression (ESR) algorithm -- to automate the search for optimal LF, SMF and HMF functional forms. ESR scores all functions up to a maximum complexity composed of a user-defined basis set of operators using the description length, an approximation to the Bayesian evidence that balances accuracy with complexity. We find many functions outperforming the Schechter and double Schechter functions for the LF and SMF, and that outperform the Press--Schechter and Warren/Tinker functions for the HMF. By additionally imposing "physicality checks" on functions' extrapolation and integration properties, we identify the optimal, low-complexity functional forms in terms of accuracy, simplicity and behaviour beyond the data range. As well as providing drop-in replacements for literature LF, SMF and HMF fitting functions, and identifying robust behaviour across well-fitting functions, we present a framework with which symbolic regression may be used to automate the discovery of optimal functions for any astrophysical dataset.

Submillimeter (submm) integral field units (IFUs) utilising kinetic inductance detectors (KIDs) are a promising instrument architecture for the study of galaxies, galaxy clusters, and the large-scale structure of the Universe. In order to design successful experiments targeting these science cases, several aspects such as instrument design, observation and calibration strategies, and data reduction pipelines must be collectively developed, tested, and optimised. This can be achieved through end-to-end simulations of the experiment, allowing for quantitative assessment of the aforementioned aspects. To this end, we have developed gateau, a modular, flexible, and efficient simulator for submm IFU observations of astronomical sources. The simulator consists of a Python interface, powered by a C/C++ backend that uses CUDA for GPU-acceleration, and is publicly available and fully open-source. gateau simulates observations by taking user input such as an astronomical source, a set of atmospheric screens, a scan pattern, and telescope and instrument parameters. It then propagates the source signal to the detectors. A physically motivated photon-noise model is used to add a white noise component to the received power. Detector noise is added as temporally correlated pink noise. The output is stored in the form of time-ordered datasets. We validated gateau against observations with DESHIMA 2.0, a superconducting, ultra-wideband spectrometer utilising KIDs and on-chip filterbank technology. We show that we can reproduce real observations of the atmosphere and Uranus with gateau simulations. Lastly, we present a use case to show how gateau can simulate long observations in timespans orders of magnitude smaller than the observation time itself, highlighting its applicability and efficiency.

On 2024 May 6, Active Region 13663 produced an X4.5-class flare associated with a filament eruption that exhibited remarkable rotation and deflection dynamics. This study aims to investigate two key aspects of this event: the formation mechanisms of the complex flare ribbon structures and the physical drivers behind the observed filament deflection. We conduct a data-constrained magnetohydrodynamic simulation using the zero-beta approximation to reconstruct the filament's evolution. Through detailed analysis of quasi-separatrix layers (QSLs) and their comparison with observed flare ribbons, we establish crucial connections between magnetic topology and flare morphology. First, our simulation successfully reproduces key observational features of the eruption. Then, we connect the flare ribbon morphology with calculated QSLs. Finally, we find filament deflection resulting from localized reconnection at the X-point, as evidenced by Lorentz force decomposition. We demonstrate that reconnection above two current channels of opposite helicity governs the eruption dynamics, with magnetic pressure gradients driving flux rope deflection while magnetic tension force simultaneously restraining arcade ascent. The event features a "sandwich" magnetic configuration including double parallel polarity inversion lines with strong shear component. We suggest that this particular configuration could serve as a plausible formation mechanism for the observed parallel three-ribbon structure. In addition, the evolution of QSLs and flare ribbons provides clear evidence of reconnection between two flux ropes.

We explore the viability of scalar field dark matter halo models through the rotation curve analysis of the Andromeda galaxy (M31), taking into account a realistic description of its baryonic structure. The mass model includes a stellar disk described by the Freeman profile and two alternative bulge configurations: a classical single de Vaucouleurs bulge and a two-component structure consisting of inner and main bulges modeled by exponential sphere profiles. The dark matter halo is modeled using three scalar field motivated models: fuzzy dark matter (FDM), Bose-Einstein condensate and multistate scalar-field dark matter. The model parameters are determined through the Levenberg-Marquardt nonlinear least-squares fitting, and the relative performance of the models is evaluated using the Bayesian Information Criterion which allows a direct comparison with previous phenomenological halo studies performed for the same galaxy. We find that the two-bulge baryonic configuration ensures a better statistical description of the M31 rotation curve, independently of the adopted halo model. The results also suggest that, within scalar field dark matter scenarios, smooth cored halos, such as FDM, provide the most consistent description of the M31 kinematics.

Scattered light is one of the most common sources of non-stationary noise at low frequencies in Advanced LIGO detectors. It appears as arch-like features in time-frequency spectrograms, produced when stray light reflects from moving surfaces and recombines with the main interferometer beam. In this study, we present ArchGEM, an automated framework for identifying and characterizing these arches and recovering the physical properties of the scattering surfaces. ArchGEM combines a prominence-based peak-finding method with a Gaussian Mixture Model clustering approach to capture a range of scattered-light morphologies across different detector conditions. We apply ArchGEM to scattered light glitches across Advanced LIGO observing runs O3 (2019--2020) and O4 (2023--2024). We find that the average frequency distributions of this noise span 15--25 Hz in O3a and O4, but increase to 20--40 Hz during O3b. Typical inferred surface velocities are 0.2--0.5 $\mu$m/s, and inferred surface displacements are 0.1--0.3 $\mu$m. The Gaussian Mixture Model performs most consistently for complex or overlapping features, with mean frequency offsets within 5 Hz of the Gravity Spy baseline. Our results show that ArchGEM provides a practical tool for detector characterization by linking observed spectrogram features to the motion of scattering surfaces and helping guide future mitigation of scattered light noise in current and next-generation interferometers. By quantifying the temporal and spectral behavior of scattered light, ArchGEM provides a robust framework for diagnosing noise sources and guiding targeted mitigation strategies in future detector upgrades.

We investigate whether Scalar-Tensor-Vector Gravity in its weak-field modified gravity form can account for the cluster-scale inverse-square force law inferred from recent kinematic Sunyaev-Zeldovich measurements of cluster pairwise motions. The starting point is the X-COP cluster fit of STVG-MOG, for which a representative baryonic cluster mass $M\sim 10^{15}M_\odot$ together with parameters $\alpha\sim 9.11$ and $\mu\sim 0.196~{\rm Mpc}^{-1}$ provides a successful description of cluster dynamics without particle dark matter. We extrapolate this fit to the separation range $30$ to $230~{\rm Mpc}$, relevant for the pairwise kSZ analysis. Since the Yukawa transition length $\mu^{-1}\simeq 5.1~{\rm Mpc}$ is much smaller than these separations, the STVG-MOG acceleration law reduces to an effective inverse-square form. This explains why the theory can satisfy the observed Newtonian behavior while remaining distinct from MOND-like long-distance modifications. We derive the corresponding pairwise velocity curve and show that, after fitting a single overall kSZ amplitude, the extrapolated STVG-MOG prediction reproduces the measured trend of the pairwise kSZ data. The analysis shows that the X-COP cluster fit and the cosmological-scale kSZ force-law result are mutually consistent within STVG-MOG.

Epsilon Indi A b is a directly imaged $\sim6 M_{\rm Jup}$ exoplanet orbiting a nearby (3.6 pc) K-dwarf at $\sim 30$ AU. We analyze archival JWST/MIRI 15 $\mu$m coronagraphic imaging of this planet to search for directly imaged satellites orbiting Eps Ind A b. Within the planet's Hill sphere (radius $R_H \approx 2.3$ AU or $1.3 \lambda/D$), we compare single- and double-PSF models using Bayesian evidence. We find that a double-PSF (binary planet) fit is preferred. This apparent preference can most plausibly be explained by systematics, although follow-up observations would be required to fully rule out a binary planet interpretation. We construct a contrast curve of the exoplanet after removing this feature, demonstrating sensitivity to companions as faint as $0.03\times$ the F1550C flux of Eps Ind A b (equivalent to $T = 130$ K, $1.3 M_{\rm Jup}$) at large separations (>2 AU). We also demonstrate sensitivity to brighter companions $0.2\times$ the F1550C flux of Eps Ind A b (equivalent to $T = 180$ K, $2.5 M_{\rm Jup}$) down to separations of 0.52 AU (1.3 pixels; $0.29 \lambda/D$; 144 mas). This study demonstrates that JWST/MIRI can directly detect exomoons or binary planets inside the Hill sphere of directly imaged exoplanets orbiting neighboring stars.

Recent late-Universe observations suggest an open Universe. If confirmed, such a departure from spatial flatness would carry profound implications for our understanding of cosmic inflation and the ultimate fate of the Universe. Motivated by this intriguing result and the release of new data, we revisit the question using baryon acoustic oscillation measurements from DESI DR2, multiple Type Ia supernova samples, refined strong gravitational lensing time-delay analyses, and the most up-to-date cosmic chronometer data. We find that within the $\Lambda$ cold dark matter ($\Lambda$CDM) paradigm, the combined data still prefer an open Universe with $\Omega_K=0.049\pm0.037$. However, this preference vanishes in extensions to $\Lambda$CDM, where the data instead favor a flat Universe. The model comparison shows that for $\Lambda$CDM, introducing new physics is preferred over merely allowing spatial curvature, and flat $\Lambda$CDM extensions perform better than their curved counterparts. We therefore argue that the mild open-Universe signal is an artifact of limited model flexibility, rather than a genuine feature of late-Universe observations.

The evolution of neutron stars (NSs) embedded within massive stellar envelopes is a critical phase in binary stellar evolution, potentially leading to the formation of Thorne-Żytkow Objects (TŻOs) or catastrophic collapse. We present the first fully coupled general relativistic hydrodynamics (GRHD) simulations of hypercritical accretion onto NSs that simultaneously incorporate grey two-moment (M1) neutrino transport and an $\alpha$-chain nuclear reaction network. By investigating four distinct progenitor evolutionary stages, we resolve the complex interplay between intense neutrino cooling, multidimensional fluid dynamics, and nuclear feedback. Our results show that while vigorous convection is triggered in the post-shock region, the global energy budget is primarily governed by neutrino cooling, which effectively balances the accretion power. Crucially, even though our M1 transport scheme captures neutrino absorption and localized heating, the efficient cooling sink and high ram pressure of the infalling envelope prevent the formation of any core-collapse supernova-like explosion. We find that all nucleosynthetically processed material ($T > 5$~GK) remains strictly gravitationally bound, challenging the assumption that these systems contribute significantly to galactic nucleosynthetic yields via convective dredge-up. The lack of sustained outflows and the persistent hypercritical accretion rates suggest that embedded NSs will rapidly exceed the Tolman-Oppenheimer-Volkoff mass limit on timescales of minutes to hours. We conclude that these systems are not stable TŻOs, but are rather transient precursors to catastrophic black hole formation and potential central engines for high-energy transients.

Taiji is a gravitational wave detection mission in space initiated by the Chinese Academy of Sciences, which will open the millihertz window through a heliocentric triangular constellation of three drag-free spacecraft. Its ultimate sensitivity is determined partly by the residual acceleration noise of the gravitational reference sensors (GRS), within which the coupling between the test-mass and the fluctuating environmental magnetic field constitutes one of the key stray-force contributions. Following the path established by the LISA and TianQin teams, high-precision ground characterization of remanent magnetic moment $\vec{m}_r$ and volume susceptibility $\chi$ of the test masses is a central step in the Taiji pre-launch test program. A persistent challenge for this characterization is the non-stationary, colored background noise inherent to torsion-pendulum facilities, which systematically biases classical Ordinary Least Squares (OLS) and Kalman filter (KF) estimators. We propose an AI-enhanced Differentiable Weighted Least Squares (AI-WLS) framework that fuses a dilated one-dimensional residual network, acting as a dynamic noise evaluator, with a fully differentiable analytical physical solver. This architecture preserves the exact linear mapping from the magnetic parameters to the torque response while autonomously identifying and suppressing contaminated data segments. Validated on real measured noise from the Changchun Institute of Optics, Fine Mechanics and Physics torsion-pendulum facility developed for Taiji, which achieves a torque sensitivity of order $10^{-13}\,\mathrm{N\cdot m\,Hz^{-1/2}}$, the AI-WLS framework bounds the maximum absolute estimation errors at $4.46\times 10^{-10}\,\mathrm{A\cdot m^2}$ for $\vec{m}_r$ and $7.8\times 10^{-8}$ for $\chi$, satisfying Taiji's ground-test requirements on all these parameters simultaneously.

In many astrophysical transients, outflows drive shocks into the ambient medium, accelerating electrons to non-thermal energy distributions that produce broadband synchrotron emission. At late times, even initially collimated relativistic jets evolve into quasi-spherical Newtonian blastwaves. As the shock decelerates, the post-shock internal energy per particle decreases; below a critical velocity $\beta_{\rm DN} \approx 0.2$, only a fraction $\xi_e < 1$ of electrons are accelerated to relativistic energies, defining the deep Newtonian (DN) regime. We develop a unified analytic framework for synchrotron emission in this phase, applicable to both single-velocity and stratified ejecta. For gamma-ray burst afterglows in a uniform medium, the DN transition occurs at $t_{\rm DN} \approx 3.7\,E_{51}^{1/3} n_0^{-1/3}$~yr, yielding a shallower decay by $\delta\alpha = 6(p-2)/5$ relative to standard Newtonian predictions. For kilonova remnants ($E_0 = 10^{50.5}$~erg, $M_{\rm ej} = 0.1\,M_\odot$), the DN phase begins prior to deceleration; neglecting it underestimates radio flux by factors of $\sim 3$--$5$ during coasting and even more thereafter. Magnetar-boosted remnants ($E \sim10^{52}$~erg) should reach $\sim$\,10\,--\,100\,$\mu$Jy at 3~GHz at $\sim$\,40\;Mpc, though limits on GW170817 already disfavor a long-lived millisecond magnetar. In core-collapse supernovae in a wind medium ($\rho\!\propto\!r^{-k}$), the peak luminosity remains constant during coasting, while $\nu_{\rm pk} \propto t^{-1}$; for SN~2023ixf, we find $k = 1.29 \pm 0.14$. The DN SED typically satisfies $\nu_m\!<\!\nu_{\rm sa}\!<\!\nu_c$, peaking at sub-GHz frequencies where LOFAR and SKA-low are most sensitive. Even non-detections place robust constraints on ambient density and outflow energetics.

We present a high-precision joint gravitational-lensing and kinematic analysis of nine massive galaxy clusters from the CLASH and CLASH-VLT surveys to test chameleon screening gravity and its $f(R)$ sub-class at Mpc scales. We investigate the dependence on the assumed parametrization of the total cluster mass profile by adopting three models, namely Navarro--Frenk--White (NFW), Burkert, and Hernquist. When cuspy models (NFW or Hernquist) are assumed in the general chameleon framework, the combined constraints from the nine clusters are fully consistent with General Relativity (GR), excluding large regions of the modified-gravity parameter space (the coupling constant $\mathcal{Q}$ and the background chameleon field $ \phi_\infty$), providing one of the tightest bounds on general chameleon models with clusters to date. In contrast, adopting a Burkert profile -- disfavored by lensing data -- leads to a mild ($\sim 2\sigma$) departure from the GR expectation in joint analysis. When considering the $f(R)$ sub-case, we obtain a bound on the background scalaron field of $|f_R| \lesssim \mathrm{2-5}\times 10^{-5}$ (95\% C.L.) for NFW and Hernquist models, in agreement with current constraints at cosmological scales, and an apparent deviation from standard gravity of $\log_{10}|f_R| = -4.7 \pm 1.2$ for the Burkert case. We investigate the impact of systematics in the kinematical analysis, showing that the tension is mitigated when clusters exhibiting clear dynamical disturbance are excluded from the sample. [...[ The upcoming generation of wide-field lensing surveys and spectroscopic follow-up programs will enable similar analyses on substantially larger samples, offering the prospect of tightening cluster-based constraints on gravity and the dark sector.

From the onset of observations of JWST we have discovered unexpectedly luminous galaxies at redshifts $z>10$ and as high as $z=14$. With their discovery, the question immediately followed as to where their progenitors are, since such progenitors should be within reach of existing surveys. However, the discovery of several bright candidates at $z>15$ may indicate further discrepancies between pre-JWST model predictions and current observations. Progenitors of the bright $z\sim 14$ galaxies should be visible at redshifts as high as $z\sim 20$--$30$, showing in the data as F356W and F277W dropouts. We identify two such candidates in the Bullet Cluster JWST data; however, subsequent NIRSpec follow-up data show spectra that can be well fit with ultra-cool Y dwarf templates with temperatures $T_{\rm eff} = 350^{+110}_{-80}\,\mbox{K}$ and $T_{\rm eff} = 410^{+110}_{-50}\,\mbox{K}$ and distances of $\sim 500\,\mbox{pc}$. The first is one of the lowest temperature brown dwarfs known spectroscopically. With additional NIRCam imaging taken $\sim 1$ year later, we also detect their proper motions of $(49 \pm 8)\,\mbox{mas/yr}$ and $(24 \pm 3)\,\mbox{mas/yr}$, further indicating that at least some F277W and F356W dropouts are sub-stellar cold Milky Way objects such as brown dwarfs. We find a sky density of 0.14 Y dwarfs per arcmin$^2$ and caution that the probability of detecting such objects may increase significantly in surveys at low galactic latitudes.

The physical properties of Milky Way Mgii-bearing gas remain poorly constrained due to the saturation of the near-UV doublet. We utilize the weaker Mgii $\lambda\lambda$1239, 1240 doublet from 482 archival HST/COS extragalactic sightlines to probe this cool gas phase. We identify 43 low-velocity absorbers ($|v_{\rm LSR}|<40\ {\rm km\ s^{-1}}$), yielding a covering fraction ($C_f$) of $32\pm5\%$ for $\log N_{\rm MgII} > 15$. We find that $C_f$ follows an exponential decay relative to equivalent width thresholds, marking a transition from a diffuse medium to localized, dense structures (e.g., cold neutral medium cores). The steep decline of the distribution at high column densities likely reflects the saturation of the turbulent log-normal spectrum and dust depletion. By integrating stellar data, we derive a Mgii scale height $h_{\rm MgII} = 0.12\pm0.02\ \rm\ kpc$ and mid-plane density $n_{0,\rm MgII} = (3.9\pm0.4)\times 10^{-6}\ \rm cm^{-3}$. A pronounced north-south asymmetry exists, with the northern hemisphere displaying a significantly higher mid-plane density ($n_{0,n} \approx 4.7 \times 10^{-6}\ \rm cm^{-3}$) than the south ($3.2 \times 10^{-6}\ \rm cm^{-3}$). This discrepancy suggests that the northern interstellar medium is more spatially concentrated and clumpy, whereas the southern gas is more ubiquitously distributed with a lower average density. These results indicate that Mgii is tightly confined to the disk, governed by a unified depletion law and restricted vertical extent.

We analyze periodicities in radial velocity (RV) measurements and magnetic activity indicators (S-index and BIS) for 767 Gaia RV standard stars to distinguish between stellar activity and planetary signals. Significant RV periods were detected in only 359 of these stars. Rotation and magnetic cycle periods are identified through iterative periodogram analysis. Among stars with confirmed planets, $28.2\%$ exhibit RV signals that coincide with activity indicators, compared to $21.3\%$ among stars without planets; however, statistical tests show this difference is not statistically significant. Several RV signals previously attributed to planets, such as those in HIP7240, HIP28460, and HIP48331, are instead likely caused by stellar activity, emphasising the importance of using multiple diagnostics to assess RV variability. We report rotation periods in 125 stars, including 30 new estimates, and detect magnetic activity cycles in 127 stars, 95 of which are new. We further investigate the relationship between rotation and magnetic cycle periods in the context of stellar dynamo theory. The full sample reveals a continuous distribution in the $P_{\rm rot}/P_{\rm cyc}$, Rossby number diagram, lacking the classical division into active and inactive branches and instead showing a negative slope, in contrast to some earlier studies. Interestingly, stars with planetary companions exhibit a steeper trend (slope of $-1.049 \pm 0.078$) compared to non-hosts ($-0.654 \pm 0.056$), suggesting that the presence of planets may subtly influence the host star's magnetic behaviour.

The advent of multi-messenger astronomy has provided abundant information for understanding the acceleration and particle-production mechanisms of cosmic rays. In this work, we present a unified study of cosmic gamma-ray and neutrino spectra within the Gluon Condensation (GC) model. Derived from Quantum Chromodynamics (QCD), the GC model predicts that, in high-energy hadronic processes, gluons may condense near a critical momentum, leading to a dramatic enhancement in secondary-pion production and imprinting a characteristic broken power-law feature on the gamma-ray spectrum. Within this framework, we first derive the neutrino spectrum corresponding to the GC scenario and then investigate three astrophysical sources with both gamma-ray observations and neutrino candidate signals: the active galactic nuclei TXS~0506+056 and NGC~1068, and the supernova remnant G54.1+0.3. Using the GC model, we fit the observed gamma-ray spectra of these sources and predict their corresponding neutrino spectra. Our results show that the gamma-ray spectra of TXS~0506+056 and NGC~1068 are well described by the GC model, and that the predicted neutrino spectra are consistent with IceCube observations within uncertainties; in particular, clear relations are found between their relative magnitudes. For SNR~G54.1+0.3, however, the GC-predicted neutrino spectrum exhibits continuous hardening after the break, deviating from the typical power-law behavior expected for cosmic-ray secondaries and thus disfavoring a common GC origin. This study represents the first systematic attempt to correlate gamma-ray and neutrino spectra within the GC framework, offering a new perspective on multi-messenger emission from high-energy astrophysical sources.

The quiet-Sun coronal electron-temperature ratio $R \equiv T_\mathrm{EUV}/T_B \approx 2.4$, stable across an eight-year solar cycle, is read here as a measurement of relative entropy between two diagnostic projections of the coronal electron distribution onto the one-parameter Maxwellian family. The EUV ionization temperature is a moment-matching projection against a Bethe-type ionization kernel; the radio brightness temperature is the Rayleigh-Jeans source function of thermal bremsstrahlung. For a kappa distribution in the mean-energy convention, Fleishman & Kuznetsov (2014) give the radio-side projection in closed form as $T_B = T_\mathrm{core}$; the EUV side returns $T_\mathrm{eff}$ up to a shape-dependent correction within the Dud\'ık et al. (2014) intensity-ratio envelope. At $\kappa = 2.5$ the Kullback-Leibler divergences between the true distribution and its two Maxwellian projections evaluate to $0.32$ and $1.20$ nats, and their difference satisfies $\Delta D_\mathrm{KL} = (3/2)[R_0 - \ln R_0 - 1] = (3/2) d_\mathrm{IS}(T_\mathrm{eff}, T_\mathrm{core})$, where $R_0 \equiv \kappa/(\kappa - 3/2)$ is the ideal closed-form ratio and $d_\mathrm{IS}$ is the Itakura-Saito distance. The identity is offered as an analytical reference for observational systems in which two diagnostics project different moments of a common non-equilibrium distribution; the eight-year stability of $R$ expresses a stability of that projection structure.

The Legacy Survey of Space and Time (LSST) on the Vera C. Rubin Observatory will generate a massive collection of time series (light curves) of the measured flux of transient and variable astronomical objects. With each new flux observation, light curve classifiers need to generate updated probability distributions over candidate classes, which will then be shared with the global community for the purpose of identifying interesting targets for follow-up observations as well as less time-sensitive analysis applications. Using the synthetic light curves and classification results of participating classifiers from the Extended LSST Astronomical Time-series Classification Challenge (ELAsTiCC), we investigate a novel framework to enhance existing light curve classifications by incorporating their classification histories and the temporal evolution of these histories. To demonstrate the potential of this approach, we introduce a model that combines a recurrent neural network and an additive attention module, which shows improved classification accuracy and more balanced precision-recall performance compared to existing classifiers from the challenge. Furthermore, at this stage, most, if not all, of the existing classifiers are evaluated by their final classification results on complete light curves; we propose new metrics that evaluate the stability, accuracy, and early classification performance of a classifier's predictions when using limited data by considering the Wasserstein distance between the temporally evolving classification probability distributions. Our metrics offer a more comprehensive perspective for model assessment by supplementing classical methods such as the confusion matrix and precision-recall.

We present the first data release (DR1) of the Spectroscopic Classification of Astronomical Transients (SCAT) survey, covering the first $\approx 5$ years of observations (March 2018 - January 2023). DR1 includes 1810 spectra of 1330 transients, which we sort into broad spectroscopic classes including supernovae (SNe), transients originating in galactic nuclei, and stellar variability. We collect multi-filter light curves from imaging surveys and fit them with phenomenological models to estimate peak brightnesses and the time of explosion/first-light. Extragalactic transients are matched to candidate host galaxies, and we compare host-galaxy luminosities and projected offsets by SN type. SNe appear to be a reliable way to augment the redshift coverage of nearby ($z\lesssim 0.1$) galaxies in tandem with dedicated redshift surveys. We present new redshifts for roughly half of the SN host galaxies, most of which are low-luminosity dwarfs similar to the Magellanic Clouds ($M_r \gtrsim -18$ mag). This set of transient spectra, light curves, luminosities, redshifts, and host galaxies offers an excellent testbed for real-time photometric/light curve classification pipelines in the modern era of deep and large-area surveys. We conclude with a brief discussion of the provided data products and status of the SCAT survey.

We present a comprehensive study of the galaxy UV luminosity function (UVLF) at $z=6-9$ leveraging deep JWST observations from the GLIMPSE survey. Thanks to gravitational lensing, we probe the UVLF to an unprecedented depth of $M_{\text{UV}} = -12$ mag, approximately three magnitudes deeper than previous robust constraints. Our UVLF determination incorporates a rigorous end-to-end uncertainty framework, including statistical and systematic lensing uncertainties. We find that the $z \sim 7$ UVLF continues to rise steeply with a faint-end slope of $\alpha = -1.98_{-0.05}^{+0.06}$. Crucially, our data show no clear evidence of a turnover down to \muv $= -12.3$. The persistence of this faint population provides stringent constraints on galaxy formation models and cosmological simulations that predict an early flattening of the luminosity function due to radiative feedback or star-formation thresholds. Furthermore, post-JWST models specifically calibrated to match the UV-bright excess at $z > 10$ generally fail to reproduce the observed evolution toward lower redshifts and fainter magnitudes, highlighting a significant tension in our current understanding of early galaxy assembly. We derive a comoving ionizing emissivity at $z=7$ of log($n_{\mathrm ion}$ / s$^{-1}$ Mpc$^{-3}$) $\approx 50.85$, which suggests that faint galaxies dominate the ionizing budget, providing enough photons to maintain reionization even in a highly clumped IGM ($C_{\text{HII}} = 5$). As our detection of faint galaxies effectively rules out a luminosity function truncation at $M_{\text{UV}} \geq -15$, these results emphasize the need to either accurately characterize the ionizing properties of the global, low-mass galaxy population at $z > 6$, or to refine physical models of intergalactic medium clumping and its redshift evolution to maintain consistency with the observed reionization timeline.

Near-infrared (near-IR) spectroscopy provides critical constraints on the surface composition of trans-Neptunian objects (TNOs), but spectroscopic observations remain limited compared to broadband photometry. We develop a probabilistic latent-space framework to quantify how much spectral information is retained in sparse photometric measurements. Using a principal component representation trained on a sample of near-IR spectra, we model the spectral manifold of TNOs and perform Bayesian inference in this reduced space to reconstruct full spectra from photometry while propagating uncertainties. Leave-one-out cross-validation demonstrates that the dominant modes of spectral variability are low-dimensional: 4 to 5 principal components capture the structure relevant for taxonomic classification, while 8-10 components improve spectral reconstruction fidelity and uncertainty calibration. For most objects, the reconstructed spectra achieve empirical credible-interval coverage of 95 percent across wavelength. This suggests the diversity of near-IR spectral shapes is governed by structured, correlated surface processes rather than stochastic variation. Practically, we apply this framework to survey optimization, quantifying the information content of JWST/NIRCam filters to identify optimal configurations (e.g., F090W, F115W, F410M, F460M) for TNO taxonomy. Additionally, we demonstrate the pipeline's capability to detect and reconstruct rare spectral types, such as the peculiar Neptune Trojans 2006 RJ103 and 2011 SO277, by allowing constraining photometry to select low-probability intermediate models from the continuous topological manifold. Ultimately, this framework bridges the gap between sparse photometry and spectroscopy, providing a statistically rigorous tool to map the compositional structure of minor planets in upcoming large-scale surveys.

Detecting possible electromagnetic precursors to the gravitational signal from merging compact objects is challenging, but it can reveal intricate physical properties of the merging stars through their gravitational and electromagnetic interactions. We demonstrate, using 3D Particle-In-Cell simulations, that a neutron star moving through the magnetosphere of a merging companion generates a complicated system of dissipative currents, a relativistic analogue of planetary Alfven wings. Generated electric currents carry a large fraction of the electromagnetic power intersected by the neutron star. These currents may lead to the generation of beamed, pulsar-like coherent radio and high-energy emission. Orbital modulation will produce a nearly periodic signal, an Alfven-winged pulsar.

The environmental mechanisms driving unwinding spiral arms in cluster galaxies remain debated. While earlier studies attributed it mainly to gravitational interactions, recent works suggest that RPS alone can induce unwinding. We present a VLT/MUSE spatially resolved analysis to investigate the mechanisms responsible for spiral-arm unwinding in two galaxies, UG101 and UG103, drawn from a larger sample. They are selected as tidal and RPS-driven candidates, respectively, based on the proximity of close neighbors. We estimate the galactocentric radius at which tidal forces, from a companion or the cluster potential, become relevant ($R_{\mathrm{tid}}$). We examine gas and stellar kinematics, exploiting their different responses to gravitational and hydrodynamical perturbations. SINOPSIS is used to map stellar populations in age bins and constrain unwinding timescales. For UG101, we find $R_{\mathrm{tid}} \sim 1.5 R_e$, while the unwound features extend beyond this radius. UG101 shows irregular stellar and gas kinematics; its rotation curve indicates similar motions, although the gas is truncated on one side and extended on the other. For UG103, neither the closest companion nor the cluster appear capable of triggering unwinding. UG103 displays regular stellar but disturbed gas kinematics, with truncation on the disk side likely facing the ICM wind and gas extended in the opposite direction. Stellar population maps show the emergence and unwinding of the spiral arms in UG103 on timescales consistent with its cluster infall time ($\sim 1.6$ Gyr). We conclude that unwinding in UG101 and UG103 is primarily driven by tidal interactions and RPS, respectively, although a combined effect cannot be excluded for UG101. Our methodology provides a framework to identify the mechanisms driving unwinding in cluster galaxies from spatially resolved properties.

Circularization of the stream material into a debris cloud during tidal disruption events (TDEs) was recently demonstrated in one of the most accurate long duration TDE simulations to-date. The cooling envelope model (CEM) provides a description of the circularized debris cloud and its emission over time well beyond circularization across different disruption parameters. In the CEM, sub-Eddington accretion rates occur early in TDEs and the debris has a shallow density profile of roughly $\rho \propto r^{-1}$, with Eddington accretion only being achieved after several months. To explore the late stages of the CEM, we perform general relativistic radiation magnetohydrodynamics (GRRMHD) simulations of magnetized tori adapted from the near Eddington phase of the CEM for a $1M_\odot$ star disrupted around a $10^7 M_\odot$ black hole (BH). We find that the disk becomes thermally unstable within 17.1-46.5 days depending on the spin of the BH. Thermal spectra show a soft X-ray excess prior to collapse, with a nearly two order of magnitude decline in X-ray luminosity upon disk collapse. Furthermore, the evolution of the blackbody radius and temperature of our models are correlated with the spin of the black hole. The spectral properties and soft X-ray luminosity in our models are similar to the TDE AT2021ehb, which is a non-jetted TDE with late X-rays and a state transition after $\approx 271$ days.

In transiting planetary systems, where planetary sizes are accurately determined from transit observations, the presence of transit timing variations (TTVs), especially when combined with radial velocity (RV) data, provides powerful constraints on masses and orbital eccentricities. Together, these measurements offer crucial insights into system architecture, formation mechanisms, and dynamical evolution. We present long-term RV and transit/TTV monitoring of the active and young star (age $\sim$1 Gyr) TOI-201, revealing an exceptional multi-planet system composed of a hot super-Earth (SE) transiting every 5.8 days, a warm Jupiter (WJ) on a 53-day orbit, and an eccentric (e = 0.622) low-mass brown dwarf (BD) on an approximately 8-year orbit, with an estimated mass of M$_{\rm BD}$ $\sim$ 16 Jupiter masses. The BD is the longest-period transiting object ever characterized via RVs, and the only one known to be coplanar with inner planets. The architecture of this system suggests that the SE was formed isolated and in the innermost region of the gaseous disc. On the other hand, the orbital configuration of the outer companions suggests a nearly in-situ formation of both objects, with the WJ forming in a dense inner disc. Alternatively, the BD might have formed farther out and migrated inward, while inflating its eccentricity due to interactions with the disc.

Accurate astrometric measurements for star-forming regions located on the far side of the Milky Way remain scarce. In this work, we present the astrometric results for a 22\,GHz water maser associated with star-forming region G040.96+02.48 located on the far side of the Milky Way, using the East Asian VLBI Network. The target water maser's proper motion was determined to be ($\mu_{\alpha}\cos\delta, \mu_{\delta}$) = ($-2.06_{-0.51}^{+0.53}$, $-2.95_{-0.44}^{+0.45}$)~mas~yr$^{-1}$. The derived three-dimensional kinematic distance to the star-forming region is 20.2$\pm$3.2\,kpc, placing it slightly outside the Outer Scutum$-$Centaurus Arm. The corresponding vertical height of 872$\pm$139\,pc indicates a significant warp of the outer Galactic disk, which is in good agreement with the latest precessing warp model. Moreover, the resulting peculiar motions reveal a complex kinematic pattern, characterized by a large outward radial velocity of $-32\pm$18\,km~s$^{-1}$. Our observations substantially expand the valuable sample of star-forming regions with accurate astrometric measurements in the Extreme Outer Galaxy.

We present a generalized phenomenological parameterization of the deceleration parameter $q(z)$ that incorporates an effective radiative component (ERC) in addition to a localized late-time contribution. The proposed framework extends previous two-parameter $q(z)$ reconstructions by explicitly regulating the high-redshift behavior while preserving the late-time transition dynamics. We constrain the free parameters $(h, q_0, z_c, z_e)$ using late-time observational data from cosmic chronometers (CC), Pantheon+ Type Ia supernovae (SNIa), H\,\textsc{ii} galaxies (HIIG), and intermediate-luminosity quasars (QSO). For the full data combination (CC+SNIa+HIIG+QSO), we obtain $q_0 = -0.25^{+0.04}_{-0.04}$ and a transition redshift $z_T \simeq 0.80$, indicating a currently accelerating Universe with a transition occurring earlier than in the $\Lambda$CDM model. Within the redshift range probed by the data, the reconstructed $q(z)$ deviates from the $\Lambda$CDM trend, suggesting a possible reduction of the late-time acceleration. Furthermore, the reconstruction favors a relatively high value of the Hubble parameter, $h = 0.729 \pm 0.006$. The ERC remains weakly constrained by late-time data but ensures a smooth and monotonic evolution of $q(z)$, $j(z)$, and $w_{\rm eff}(z)$ across a wide redshift range. Within the observed interval, the model effectively reproduces the late-time behavior of the previous parametrization, while providing a controlled extension toward early epochs. Our results show that current low- and intermediate-redshift data are compatible with a reduced late-time acceleration.

Visualization of high-dimensional data is crucial to retrieve all the knowledge that is contained within a dataset. Effective and informative presentation of three-dimensional data via a two-dimensional medium is challenging, especially if the dataset more closely resembles a 2.5-dimensional (2.5D) entity due to sparse sampling. We present LStein (Linking Series to envision information neatly), a novel visualisation approach implemented in Python, in an attempt to solve this challenge. Inspired by the astrophysical application of displaying photometric timeseries in multiple passbands with minimal loss of information, we compare our method to traditional approaches. While astronomy -- specifically multi-passband visualisation for lightcurves obtained with the Rubin Observatory -- serves as the principal driver for the design, we demonstrate that LStein can be used in any context with 2.5D datasets from radio astronomy to machine learning hyperparameter search visualization. LStein can be installed from GitHub (this https URL).

We present a model-independent, sound-horizon-free measurement of the Hubble constant $H_0$ using baryon acoustic oscillation tracers from the Dark Energy Spectroscopic Instrument Data Release 2. The function reconstructions are performed using the artificial neural network method, which is a completely data-driven approach that avoids the mild $\Lambda$CDM prior dependence. Our approach is based on the distance duality relation and combines three complementary observational probes, such as Type Ia supernovae, cosmic chronometer, and DESI DR2 BAO -- without requiring any knowledge of the sound horizon scale $r_d$ or any assumption about the absolute luminosity of SNe Ia. We obtain a joint constraint of $H_0 = 71.5\pm2.2$ km s$^{-1}$ Mpc$^{-1}$ at 68\% confidence for 1000 bootstrap realisations and 4096 neurons, which is consistent with the TRGB result and the SH0ES measurement within $0.6\sigma$, consistent with the Planck 2020 result within $2\sigma$. Our results favor a higher value of $H_0$ compared to the Planck CMB inference, adding independent support for the reality of the Hubble tension.

The `Triangal' galaxy evolution schema is used to assess whether the Tuning Fork (bar strength) or the van~den~Bergh Trident and ATLAS$^{3D}$ Comb (spiral strength) offer greater evolutionary insight. A new catalogue of quantitative bar strengths (measured by the bar-to-total luminosity ratio, $P$), refined galaxy morphologies, and dust bin classifications is presented. It contains 137 galaxies with spheroid stellar masses, obtained from multi-component decompositions, and directly measured black hole masses, $M_{\rm bh}$. By placing these galaxies within the $M_{\rm bh}$-($M_{\rm\star,sph}$, $M_{\rm\star,gal}$) parameter space, an evolutionary reference frame reflecting integrated growth is established. Galaxies with varying bar strengths, and double bars, are observed to not occupy preferred locations, highlighting that bars are products of secular evolution-and can be transient or recurrent phenomena-and that they track neither hierarchical mass assembly nor galaxy speciation. In contrast, three physically distinct formation channels for S0/a galaxies are identified: (primeval S0)-to-S transitions; faded spiral galaxies; and, most commonly, wet-major-merger-built dust-rich S0 galaxies (on the `green mountain'). Galaxies with particularly strong spirals appear on the right-hand side of the spiral galaxy distribution. Furthermore, a `Dust Attrition/Retention' sequence places S0 (and compact massive ES,b) galaxies with dusty nuclear discs between the dust-poor and dust-rich S0 galaxies, and a `Disc Down-sizing' sequence is revealed, in which E galaxies with dusty nuclear discs-potentially formed through `damp' mergers-bridge the ES,e (ellicular) galaxies with intermediate-scale stellar discs and the dust-poor pure E galaxies. Extensive historical context is provided, and, finally, suspected biases in precision cosmology stemming from neglected precision galaxy morphology are discussed.

We present a multiwavelength follow-up study of 621 winged radio galaxies (WRGs) recently identified from LoTSS DR2, constituting the largest statistically significant samples of X-shaped (XRGs) and Z-shaped (ZRGs) radio galaxies to date. Our results show that WRGs are predominantly strongly radio-dominated, with XRGs on average more radio-luminous than ZRGs. Their optical hosts are massive elliptical galaxies residing in moderate-density environments. For 270 of XRGs, we measure angular offsets between the radio wings and the optical major axis. While most XRGs show large misalignments consistent with hydrodynamic backflow along the host minor axis, a substantial fraction ($\sim$25\%) exhibits small offsets (<30°), indicating that additional processes, such as jet reorientation, may also play a role. ZRGs, in contrast, are characterized by strongly antisymmetric deformations of their radio lobes pointing toward a coherent mechanism affecting both jets, modulated by local environmental interactions at the lobe termini. Mid-infrared diagnostics indicate merger-related cold gas in many WRGs, particularly XRGs, which also more frequently host powerful AGN, while ZRGs are more often classified as low-excitation radio galaxies (LERGs). This is consistent with our previous results showing that, although most WRGs exhibit FR II morphologies, FR I sources are almost exclusively ZRGs, suggesting that Z-shaped structures are statistically associated with lower jet power and are therefore more susceptible to perturbations. Nevertheless, the physical processes responsible for shaping XRGs and ZRGs need not be fundamentally different. Instead, the final morphology likely reflects the interplay between jet power, jet stability, and the surrounding environment.

We present a comprehensive analysis of 146 contact binaries using medium-resolution LAMOST spectra and photometric data from the All-Sky Automated Survey for SuperNovae (ASAS-SN) and the Transiting Exoplanet Survey Satellite (TESS). Radial velocity curves obtained through the cross-correlation function method were modeled simultaneously with the light curves using the Wilson-Devinney code to derive the physical parameters of these systems. The reliability of our results was verified through comparison with previous studies of ten systems, showing good agreement. Our analysis shows that the more massive components are generally less-evolved main-sequence stars, whereas the less massive components tend to be over-sized and over-luminous, consistent with earlier findings. The distribution of orbital angular momentum supports the scenario in which contact binaries form from detached binaries via angular momentum loss. We identified 38 low mass ratio ($q < 0.25$) systems, 11 of which have extremely low mass ratios ($q < 0.15$). A remarkable example is ASASSN-V J111451.48+005038.6, which exhibits a mass ratio of 0.113 and the highest fill-out factor (98.3%) reported to date, making it a strong candidate for future mergers. Conversely, we also identified 11 high mass ratio (H-type) systems, including ASASSN-V J093921.74+390452.6 - the system with the highest spectroscopically confirmed mass ratio ($q = 0.993$) and a low fill-out factor (1.8%), suggesting it recently entered the contact phase. Additionally, several empirical relations between physical parameters are established.

We analyze zenith-pointing $(\delta=-26.7^{\circ})$ Murchison Widefield Array (MWA) $\nu_c=154.2 \,{\rm MHz}$ drift scan observations covering $349.0^{\circ} \le \alpha \le 70.0^{\circ}$ with 163 pointing centers (PCs) spaced by $0.5^{\circ}$. We measure $D_{\ell}$, the mean-squared angular brightness temperature fluctuations, as a function of $\alpha$. A broad peak at $\alpha \approx 50.0^{\circ}$ corresponds to the bright extended source Fornax~A in the main lobe of the primary beam. A smaller peak at $\alpha \approx 5.0^{\circ}$ possibly corresponds to Fornax~A in the first sidelobe. For $\alpha \leq 22.0^{\circ}$ and $\ell \ge 200$, we find $D_{\ell} \propto \ell^2$, which we interpret as Poisson fluctuations from point sources. We present $\Delta^2(k)$, the mean-squared 21-cm brightness temperature fluctuations from the Epoch of Reionization, as a function of $\alpha$. Fornax~A causes strong contamination near $\alpha \approx 50.5^{\circ}$, elsewhere several PCs are consistent with noise. The range $358.5^{\circ} \leq \alpha \leq 11.5^{\circ}$ is relatively foreground-free and best suited for EoR science. The PC at $\alpha = 11.0^{\circ}$ yields the best $2\sigma$ upper limit $\Delta^{2}_{\rm UL}(k) = (173.13)^{2}\,{\rm mK^{2}}$ at $k = 0.161\,{\rm Mpc^{-1}}$. We incoherently combine $23$ PCs to obtain $\Delta_{\rm UL}^2(k)=(98.67)^{2}\,{\rm mK}^{2}$ at $k=0.156\,{\rm Mpc}^{-1}$. This is the tightest upper limit from the MWA, being $\approx3$ times lower than earlier MWA limits, but $\approx2$ and $\approx21$ times higher than the LOFAR and HERA limits, respectively, and $\approx3$ orders of magnitude above theoretical predictions.

Galaxy clusters are located at the nodes of the filamentary network known as the cosmic web. A more comprehensive understanding of galaxy clusters can be achieved by considering their environment, in particular, the filamentary structures to which they are connected. In this work, we aim to assess the reliability of the cosmic web reconstruction from mock observational data. In particular, we aim to quantify the effects of the 2D projection relative to the underlying 3D network and the impact of using the Sunyaev-Zel'dovich (SZ) effect as a tracer of the cosmic web. We reconstruct the filamentary networks in the outskirts of The Three Hundred simulated clusters with the filament finder DisPerSE. First, we extract the networks from the 2D gas distribution and evaluate their purity and completeness with respect to the 3D networks projected along the line of sight. We also compute the distances between the corresponding skeletons. Moreover, we identify filaments from simulated Compton-$y$ maps of the clusters at redshift $z=0$, and we compare them with the 2D gas network. The skeletons extracted from 2D maps provide good representations of the underlying 3D ones, both in terms of critical points and filaments. We find a median distance between the spines of the 2D and projected 3D networks of approximately $0.22 \, h^{-1}$ Mpc, although the connectivity derived from the 2D networks is slightly underestimated. We observe a good spatial agreement between the gas and SZ networks, with a median distance of $\approx 0.24 \, h^{-1}$ Mpc. Finally, we show that gas outside galaxy clusters is preferentially located in filamentary structures, which contribute $\sim 80\%$ of the integrated Compton-$Y$ parameter of clusters' outskirts.

SOXS (Son Of X-Shooter) is a new spectrograph for the European Southern Observatory (ESO), recently installed at the New Technology Telescope (NTT) at the La Silla Observatory, Chile. The main instrument goal consists in the characterization of transient sources, based on alerts. It covers from (partially) ultra-violet to visible and near-infrared bands, with a spectral resolution of R $\sim 4500$, using two separate, wavelength-optimized spectrographs. A scientific grade visible camera, primarily intended for target acquisition, also provides a "light imaging" mode. In this paper, we present the design of the SOXS Instrument Control Software, which is in charge of controlling all motors, calibration lamps and detectors, monitoring sensors and components' status, coordinating the execution of exposures, and implementing all observation, calibration and maintenance procedures. Given the extensive experience of the SOXS consortium in the development of instruments for the ESO Very Large Telescope (VLT), we decided to base the design of the Control System on the same standards, both for hardware and software control. We illustrate the control network, the instrument functions and detectors to be controlled, the overall design of SOXS Instrument Software (INS) and its main components. Then, we provide details about the control software for the most SOXS-specific components, and peculiar features: the piezoelectric tip-tilt corrector used for active compensation of mechanical flexures of the instrument; the cryogenic piezoelectric slit exchanger for the NIR spectrograph; the co-rotator monitoring system; and the control of the Commercial-Off-the-Shelf (COTS)- based imaging camera.

The Microchannel X-ray Telescope (MXT) is a compact and lightweight focusing X-ray telescope, which is part of the space payload of the SVOM mission. The main goal of the MXT instrument is to precisely localize and physically characterize the early phases of the X-ray afterglows detected by the SVOM ECLAIRs coded mask telescope after a satellite slew. The MXT is composed by a "Lobster-Eye" type optics, with a 58$\times$58 arcmin$^{2}$ field of view, based on micro-pores of 40 $\mu$m side. This innovative type of optics is coupled to an X-ray camera, which implements at its focal plane a low-noise pnCCD. The MXT system is completed by an onboard calculator, able to command the whole telescope and to analyze in real time the MXT data stream and hence to localize the sources within the MXT field of view. In this paper, we present the MXT design and in-flight performance, as measured during the SVOM Commissioning and early science operation phase. In particular, we will focus on the optical and spectral performances, the in flight localization capabilities, and how these compare with the pre-flight ground measurements.

The Space-based multi-band astronomical Variable Objects Monitor (SVOM) mission was launched in June 2024. It is a joint Sino-French collaboration designed to detect, localize, and study gammaray bursts (GRBs) and other high-energy transients. Among its onboard instruments, the Microchannel Xray Telescope (MXT) plays a central role by providing follow-up X-ray observations of GRB afterglows and other transient phenomena. To ensure timely and accurate scientific exploitation of MXT observations, a dedicated ground processing pipeline has been developed. This pipeline automatically ingests raw event lists, performs calibration, background and time filtering, corrects instrumental effects, and produces science-ready data products such as images and light curves and spectra of detected sources. In this paper, we describe the architecture and key components of the MXT data analysis pipeline, highlighting its modular design and integration within the broader SVOM ground segment. We also show results from real datasets, demonstrating the pipeline's ability to meet the performance requirements of the mission.

The core instrument of the SVOM Gamma-ray burst mission launched in June 2024 is the 4-150 keV 2-D coded mask camera ECLAIRs responsible for the autonomous trigger and localization of transient events within its field of view. The flight model of ECLAIRs has been built by several French labs (IRAP, CEA, APC) under the supervision of the French Space Agency (CNES), while APC, LUPM and IAP built a suite of data reduction and analysis software. This paper outlines the main science goals of ECLAIRs and describes the different instrument sub-systems and their main characteristics. The paper then discusses the instrument configuration and operation as well as the main in-flight measured performances. Finally, the paper summarizes the science performance of ECLAIRs up to March 31, 2025.

At the heart of the SVOM French ground segment, the French Science Center is a cloud-based platform which provides services and tools for the management, storage, scientific processing and visualization of SVOM data for the French community. This digital center is a critical node of the SVOM system since it is the single point of access to SVOM scientific data for the French community and the only component of the ground system connected to the SVOM VHF network allowing near-time communication from the satellite. Scientific processing pipelines are fully integrated into its infrastructure, allowing the automated production of high-level scientific data and the generation and broadcast of alerts to the scientific community at large. The software components of the French Science Center are running 24/7 and thus require a high level of automation, which led to the development of dedicated software relying on modern technical solutions such as micro-services, application containerization, infrastructure-as-code and continuous integration and deployment. In this paper, we describe the FSC infrastructure design, technological choices, and the process of SVOM data ingestion, archiving, and automated processing by the FSC scientific pipelines. We present analysis on the FSC performances in terms of availability, amount of data processed as well as processing speed.

The Chinese-French SVOM (Space-based Multi-band Astronomical Variable Objects Monitor) mission is dedicated to the study of gamma-ray bursts (GRBs) from the distant universe. A key component of the SVOM Chinese Ground Segment, the Science User Support Services (SUSS) provides comprehensive support for the mission's scientific operations. SUSS consists of two integral pillars: a suite of specialized software tools that automate key workflows, and a dedicated User Support Team that delivers expert-led, human services. These human-delivered services include operational coordination across telescope networks, direct technical assistance to astronomers, user training, and proactive problem-solving throughout the observation lifecycle. This paper focuses on the organization of SVOM scientific operations and the role of SUSS in facilitating these tasks. We provide a detailed description of the SUSS software architecture and its functionalities, encompassing the General Platform, the Burst Advocate (BA) support tools for GRB counterpart identification, the Target of Opportunity (ToO) support tools, and the General Program (GP) support tools. The structure and services provided by the user support team at the Chinese Science Center (CSC) are also elaborated. Furthermore, we evaluate the performance of SUSS during its first operational year, assessing its effectiveness in fulfilling user requirements. The evaluation offers valuable insights to guide future user support strategies and software enhancements, ultimately enabling better service for the SVOM scientific community.

The SVOM mission, a Sino-French collaboration dedicated to Gamma-Ray Bursts (GRBs) and transient sources, began scientific operations in 2025. This paper describes the ground computing infrastructure and user support tools for SVOM's three observing programs: the Core Program (CP), the General Program (GP), and Targets of Opportunity Program (ToO), the latter two being open to the broader scientific community, provided they collaborate with a mission Co-I. The mission adopts operational roles inspired by Swift, including on-duty scientists such as Burst Advocates (BAs), who validate GRB triggers and coordinate follow-up observations, and Instrument Scientists (IS), who calibrate and validate data for all programs. Users can access observation schedules, public data products, and support tools via the French and Chinese mission centers. The SVOM portal serves as the primary interface for accessing these resources, including a GRB public table, API, and user documentation. This paper serves as a guide for both newcomers and external researchers interested in SVOM scientific operations, focusing on aspects related to the CP.

The detection plane of the high-energy transient camera ECLAIRs onboard SVOM is made of 200 XRDPIX detection modules, each consisting of a matrix of $8\times 4$ Schottky-type CdTe detectors hybridized with the low-noise and low-consumption ASIC IDeF-X. The 6400 detectors are operated at -20°C and reverse biased at -300 V, reaching a low energy threshold of 4 keV. The 20 us time resolution readout electronics works in photon counting mode classifying detected events as single or multiple events and measuring the deposited energy in real time. In this paper, we present the detection plane sub-systems and their main features. We also discuss its overall performances as measured both on ground and in-flight, showing compliance with the ECLAIRs science requirements.

This paper reports on the scientific pipeline for the analysis of the ECLAIRs data of the SVOM mission. We describe the overall procedure, the different steps and the main algorithms of the data analysis for this hard X-ray coded mask instrument. The pipeline runs in automatic mode at the science center generating standard products but can also be used off-line with specific choices of parameters. Generated data products and preliminary performances are illustrated along with perspectives for future improvements.

The French-Chinese SVOM satellite mission (Space-based multi-band astronomical Variable Objects Monitor) was launched in mid-2024, with science objectives focused on the detection and study of astrophysical transient events, primarily Gamma-Ray Bursts (GRBs). The onboard trigger of the hard X-ray wide-field coded-mask instrument ECLAIRs autonomously detects and localizes GRBs on SVOM and requests automatic spacecraft slews toward these sources, enabling follow-up observations by the onboard narrow field-of-view instruments MXT and VT. The trigger also transmits real-time alerts via the SVOM VHF network to the ground, allowing rapid follow-up campaigns by the broader community, including multiple space- and ground-based facilities. We present an overview of the ECLAIRs trigger, with emphasis on the two trigger algorithms running simultaneously onboard: the Count-Rate Trigger (CRT) and the Image Trigger (IMT), both of which issue alerts for GRBs localized on the sky. The trigger has already detected several notable events, including both classical GRBs and peculiar X-ray-rich GRBs, enabling numerous redshift measurements, including high-redshift bursts.

We present the in-orbit calibration of the Visible Telescope (VT), one of the key instruments aboard the Space Variable Objects Monitor (SVOM) mission for gamma-ray burst (GRB) studies. Using Gaia Data Release 3 (DR3) as a reference, the VT achieves an astrometric precision better than 0.03'' for bright stars, degrading to ~0.25'' for faint targets. Shortly after launch, contamination was detected, reducing system transmission by ~40%. An initial bake-out successfully restored performance, but gradual recontamination caused transmission to decline by ~20% over the following 100 days before stabilizing. Despite this effect, routine standard star observations maintain precise zero-point calibration, ensuring a photometric stability of 0.02 mag. Using synthetic stellar spectra, we derived photometric transformations to the Gaia, SDSS, and Johnson-Cousins systems with typical residuals of 0.03 mag. These results demonstrate the VT system's capability and reliability in calibrating GRBs and other transients.

The Ground Support System (GSS) is a critical component of the Space-based multi-band astronomical Variable Objects Monitor (SVOM) mission's ground segment. Its main tasks include organizing and implementing the operations and management of the SVOM payloads, receiving scientific data, as well as preprocessing and managing the scientific data. To address the specific requirements of the SVOM mission, including specialized mission planning, data reception, status monitoring, and product processing, a dedicated SVOM Ground Support System has been designed based on the integrated architecture of the Chinese Space Science Satellite Project Ground Support System. This system has successfully supported SVOM's launch and on-orbit operations.

COLIBRI, the French Mexican Ground Followup Telescope (FM GFT) for SVOM, is a 1.3 meter rapid response optical facility specifically developed for prompt, multiband observations of GRB afterglows and for delivering subarcsecond localisations of optical counterparts for detailed followup studies. The telescope operates through a fully automated system that manages the entire workflow, from alert reception to counterpart identification. Commissioning results confirm that the telescope meets design specifications, and this paper presents a comprehensive performance assessment of the capabilities.

As one of the key ground-based facilities of the Chinese-French SVOM mission, the main scientific objectives of the Ground-based Wide Angle Camera array (GWAC) are to detect prompt optical emission of gamma-ray bursts or other short duration astronomical transients on a second-scale temporal resolution. GWAC is located at Xinglong observatory, China, and consists of 10 mounts and 40 cameras, providing a joint field of view of about 3600 square this http URL detection ability is 16 magnitude in 10 seconds of exposure time in the visual band under the condition of the new moon phase. Here, we give an overview of GWAC and introduce the science motivation of the project, as well as the performance of the hardware and the software. The observation strategies and the data processing are briefly presented. The early sciences in the last 5 years since the first light are summarized.

ECLAIRs is a hard X-ray coded-mask telescope onboard the SVOM space mission, designed to detect and localize high-energy transients, in particular gamma-ray bursts. Operating over the 4-150 keV energy range, ECLAIRs extends coded-mask imaging to an unusually low-energy threshold. Achieving sensitivity down to 4 keV while maintaining performance up to 150 keV motivated the development of a novel self-supporting coded mask. This design addresses both scientific and mechanical challenges through dedicated pattern-generation algorithms and an innovative stiffened sandwich structure. We present the rationale, development, and final implementation of the ECLAIRs coded mask.

On-board the SVOM mission, the Microchannel X-ray Telescope observes the soft X-ray band of the gamma-ray bursts afterglows. The so-called lobster-eye optics focuses X-rays to the camera subsystem that performs imaging and spectroscopy of a region of the sky 58x58 arcmin2 wide centered on the burst detected by the ECLAIRs instrument. The recorded photon positions are used by the on-board scientific software to rapidly localize the source, whereas spectral information is used on ground to model the properties of the gamma-ray bursts. The first months in orbit were intensively used to tune the parameter settings of the detector and the calibration method to provide high availability of the camera and accurate spectroscopy to the users. The paper presents the design of the camera validated by on-ground testing, the tuning phase in flight and the performance of the camera at the beginning of the mission. Perspectives are given concerning the evolution of the spectral response during the mission.

The scientific success of the SVOM mission will rely on the rapid transmission of alert messages from the satellite to the scientific community, and in particular to the ground-based instruments supporting the mission. In this paper, we present the alert system developed for SVOM which relies on the rapid transmission of alert messages through the transfer of data packets from an onboard VHF-band radio transmitter to a network of radio receivers deployed along the satellite ground track. We will successively detail the antenna design, radio performance, network deployment, its integration within the French data center, as well as the performance achieved after one year of operation in terms of availability and latency.

The Ground Wide Angle Camera Network (GWAC-N) is a robotic telescope network. It consists of ten wide-field core telescopes (GWAC-A) and two 60cm narrow-field rapid follow-up telescopes (GWAC-F60A/B). The primary scientific goal of GWAC-N is to detect optical counterparts of gamma-ray bursts (GRBs) discovered by the SVOM satellite. This is achieved through synchronized monitoring with the GWAC-A array. Upon receiving a GRB trigger alert, the network conducts rapid, multi-band follow-up observations using the GWAC-F60A/B telescopes. The two-stage observation process involves many telescopes, making manual control impractical. Automated operations are therefore essential. They are realized through an integrated alert processing chain and an automated observation scheduling and dispatching mechanism. To enable this, we employ the SVOM Follow-up Observation Coordinating Service (FOCS) and GWAC-N's Automatic Observation Management (AOM) system. This paper presents the integrated alert processing workflow. It also describes the formulation of observation strategies, and the scheduling and execution of observations enabled by FOCS and AOM.

The SVOM mission (Space-based multi-band astronomical Variable Objects Monitor) is a Franco-Chinese mission dedicated to the study of the most distant explosions of stars, the gamma-ray bursts. Here, we introduce the real-time response and collaboration system of SVOM, with the adoption of the BeiDou-3 short message communication service. We present the SVOM on-board and on-ground system designs and data flow, together with the collaboration mechanism with other missions. In the first year of the in-flight operation, SVOM has detected 172 gamma-ray bursts, including 147 by the GRM instrument and 62 by the ECLAIRs instrument. At the same time, SVOM has performed 1040 observations, including 122 ToO-EX(Target of Opportunity-Exceptional) observations, 48 ToO-MM(Target of Opportunity-Multi-messenger) observations and 870 ToO-NOM(Target of Opportunity-Nominal) observations. All these have increased the scientific output of the mission.

VT (the Visible Telescope) is an optical telescope onboard the SVOM (Space-based Multi-band Astronomical Variable Objects Monitor) mission, specifically designed to detect optical counterparts of gamma-ray bursts (GRBs), study their afterglows, and select high-redshift candidates. It performs rapid follow-up observations simultaneously in two channels either via autonomous platform slewing or Target of Opportunity (ToO) observations. The science images acquired by VT and transmitted via the X-band downlink system are designated as VT X-band data. This paper provides an overview of GRB optical afterglow identifications with VT and describes the ground-based processing pipeline for VT X-band data, including preprocessing, astrometric calibration, and photometry. Up to 2025 December 3, VT has followed up 111 GRBs triggered by SVOM or external missions. The overall detection rate of optical counterparts is approximately 75%. Specifically, for bursts detected by SVOM/ECLAIRs, the detection rate is 77% when observed by VT within 30 minutes after the burst. A slightly higher detection rate of 81% is achieved for GRBs triggered by external missions through rapid ToO observations with a mid-time of less than 3 hours.

The VT--VHF data comprise three types of onboard-processed data results generated from four sequential observational sequences and transmitted to the ground via a Very High Frequency (VHF) downlink. On the ground, these data are processed by three successive pipelines: the pre-processing pipeline, the VT--VHF data processing pipeline (VVPP), and the VT afterglow candidate pipeline (VTAC). These pipelines perform packet decoding, astrometric and photometric calibration, and afterglow candidate identification, respectively. This paper describes the architecture and operational implementation of the VT--VHF ground processing system and assesses its end-to-end performance using the first year of SVOM operations. These data enable rapid identification of GRB optical counterparts. Early detections, while the source is still optically bright, facilitate spectroscopic redshift measurements. Dual-band colors provide preliminary redshift constraints and help identify high-redshift candidates, whereas non-detections in both bands may indicate very high redshift, significant extinction, or intrinsically dark bursts. In-orbit operations show that the VT--VHF ground processing system successfully identifies optical afterglow candidates for a significant fraction of ECLAIRs triggers with available VT--VHF data, demonstrating its robustness and readiness.

The Chinese Ground Follow-up Telescope (C-GFT) is an optical facility upgraded to support the Space Variable Objects Monitor mission (\textit{SVOM}). Located at the Jilin Observation Station, it is capable of rapidly identifying and monitoring the optical counterparts of Gamma-Ray Bursts (GRBs). The 1.2-m telescope is equipped with two switchable focal-plane instruments: the prime-focus wide-field LATIOS camera and the Cassegrain-focus three-channel CATCH camera. In this paper, we present a system overview, including the observatory, the telescope, the instrumentation, the automated operational framework managed by the Operations Center, and the data processing pipelines. We also report the performance results obtained during over one year of \textit{SVOM}'s post-launch operations. The results demonstrate that the system meets its design specifications and delivers robust observational and operational performance.

The study of the prompt high-energy emission of Gamma-Ray Bursts (GRBs) with SVOM relies on the observations performed by ECLAIRs (4-150 keV) and the Gamma-Ray Monitor (GRM, 0.015-5 MeV), the two wide field-of-view instruments on board the satellite. In this article, we introduce the eclgrm pipelines running at the French Science Center of SVOM, which combine the ECLAIRs and GRM data to generate scientific data products describing the GRB broad-band temporal and spectral properties. The architecture of the pipelines is presented, as well as their activation following each onboard trigger, and their workflow. The statistical data analysis methods employed by the pipelines are described, along with the scientific data products that are created in real time or from the full event data. We also present the eclgrm-ui user interface which allows the scientists on shift to monitor the automated data processings in the pipelines, and to optimize the analysis results interactively.

Cool, dense condensations such as coronal rain and prominences suggest that coronal plasma can undergo runaway radiative cooling. Connecting this behaviour to linear thermal modes requires us to fully understand the deeper connection between eigenvalue spectra and actual time-dependent evolution. We aim to clarify this intricate link for a simplified, coronal-only model of a stratified coronal loop by combining spectral, linear initial-value, and nonlinear simulations of the same loop setup. We study waves and instabilities, as well as temporal evolutions for a 1D hydrostatic, thermally balanced loop with optically thin radiation and prescribed heating. The non-adiabatic spectrum is computed with our open-source Legolas code. We demonstrate our newly developed boundary value-initial value solver Legolas-IVP, where linear evolutions are performed for controlled perturbations, and fully equivalent nonlinear runs are carried out with MPI-AMRVAC. The spectrum contains discrete acoustic modes and a thermally unstable branch including a thermal continuum. Linear initial-value experiments with isochoric, isobaric, and isentropic pulses highlight how the polarisation of the eigenmodes demonstrates physically consistent behaviour expected from the eigenspectrum. Even in the linear stage, thermal imbalance drives siphon-like flows toward the cooling region. Growth rates from Legolas-IVP agree with spectral predictions and are reproduced in MPI-AMRVAC, which follows the condensation through runaway cooling to chromospheric temperatures, with the cool dense blob sliding under gravity toward the loop footpoint. The spectral-linear-nonlinear investigation demonstrates a direct link between thermal eigenmodes and condensation dynamics, providing a basis for extending to fully 3D MHD models.

We describe the public release of $>2.3$ petabytes of data from the FLAMINGO cosmological simulations. The suite consists of hydrodynamical simulations that include radiative cooling, star formation, stellar mass loss and the resulting chemical enrichment, supernova feedback, and two implementations of AGN feedback. Neutrinos are simulated explicitly using particles. Data products include snapshots, halo and galaxy catalogues, HEALPix all-sky lightcone maps, particle data for lightcone maps, and power spectra. The FLAMINGO set includes 22 hydrodynamical simulations. In addition, there are 16 gravity-only simulations, including the $10080^3$ particles FLAMINGO-10k run, with initial conditions that match those of the corresponding hydrodynamical runs. The fiducial hydrodynamical simulations span three numerical resolutions that have each been calibrated to reproduce the present-day galaxy stellar mass function and gas fractions in low-redshift clusters. Other simulations systematically vary the galaxy stellar mass function, cluster gas fractions, cosmology (including neutrino masses), and/or the nature of dark matter, in volumes of 1Gpc$^3$. The release includes hitherto unpublished simulations that use extra dark matter particles. While we provide a facility for downloading complete simulation outputs, we recognise that for many users this will not be possible due to limited local storage or network bandwidth. We implement a web service that enables users to explore available outputs and selectively download datasets or parts of datasets.

The identification of open cluster (OC) members has been revolutionized by high-precision Gaia astrometry, yet traditional kinematic membership selections remain inherently conservative, often overlooking stars in tidal tails or those with perturbed velocities. This study investigates the reliability of these kinematic probabilities by searching for leaky cluster members -- stars that fail standard kinematic membership criteria ($P < 0.7$) but possess chemical signatures identical to their host clusters. Using high-resolution spectroscopic data from the Gaia-ESO Survey, we established a seven-element chemical fingerprint ([Fe/H], Li, Si, Ca, Ti, Co, and Ni) for 34 OCs. We identified a sample of 63 stars across 22 clusters that are chemically indistinguishable from their host populations despite being kinematically rejected by standard algorithms. By cross-referencing these targets with Jacobi radii (rJ) derived from modern Milky Way potential models, we find that 35% are located in extra-tidal regions (d > rJ), providing direct evidence of active cluster dissolution and tidal debris. The remaining 65% are located within the Jacobi radius, suggesting that their kinematic rejection is likely due to orbital motion in unresolved binary systems. These results demonstrate that chemical tagging is a critical tool for overcoming the spatial and kinematic biases of astrometric catalogues. By recovering these lost members, we provide a more complete census of cluster mass loss and underscore the necessity of a hybrid chemical-kinematic approach to map the transition of stars from bound systems to the Galactic field.

Approximately 25--50\% of white dwarfs (WDs) exhibit metal absorption lines in their photospheres, interpreted as evidence of ongoing/recent accretion of planetary debris from remnant systems. Previous theoretical studies have suggested that massive, close-in substellar companion may prevent delivery of larger bodies via dynamical interactions, thereby reducing white-dwarf pollution. However, no conclusive observational evidence has yet been established to confirm such a protective effect. In this work, based on a sample of 17 white dwarf-substellar companion (1--75 $M_{\rm J}$) systems with reliable spectroscopic classifications, we find that white dwarfs hosting close substellar companions (orbital period $P < 5$ d) exhibit a metal-pollution fraction of $7.7^{+11.3}_{-4.0}\%$, which is suppressed by a factor of $5.75^{+3.24}_{-1.94}$ (corresponding to a protection efficiency of $87.2^{+3.4}_{-9.2}\%$) relative to single white dwarfs with a confidence level of 99.96\%. In contrast, white dwarfs with wider companions show a metal-pollution fraction of approximately $25.0^{+24.0}_{-12.8}\%$, comparable to that of single white dwarf systems. To interpret these results, we perform ensembles of N-body integrations and demonstrate that massive close-in substellar companions are capable of clearing 80\%--90\% of small-body contaminants. The good consistency between the observational statistics and dynamical simulations provides strong evidence for suppressed metal pollution in white dwarfs with close companions, and offers insights into the long-term dynamical evolution of WD remanent systems.

TIFR-ARIES Near-Infrared Spectrometer (TANSPEC) is a spectrograph-cum-imager operating over the wavelength range $0.55 - 2.5~\mu$m. The instrument is mounted on the 3.6-m Devasthal Optical Telescope (3.6-m DOT). It offers two resolution modes: Low Resolution (LR) with $R\sim100-350$ and Cross-Dispersed (XD) via various slits of different widths (0.5", 0.75", 1.0", 1.5", 2.0" and 4.0"). The LR mode provides a resolving power ($R$) of $\sim 100-350$, while the XD mode achieves $R\sim2500$ using the 0.5" slit. The previous version of the data reduction pipeline supported only wavelength-calibrated XD mode spectra and was limited to two slits (S-0.5 and S-1.0). In this work, we present an upgraded version of pyTANSPEC. The upgraded pipeline not only improves the data extraction algorithm but also introduces several new features for users. It now enables the reduction of spectra from all available slits for both LR and XD modes. The upgraded version also implements a template-matching method for more precise wavelength calibration. Additionally, a step for flux calibration is also included. Alongside pyTANSPEC, we upgraded HxRGproc, a Python package for cleaning and generating slope images from Non-Destructive Readout (NDR) frames taken with H1RG and H2RG detectors. The package performs non-linearity correction, flags saturated pixels, removes pink noise, and eliminates cosmic ray events. HxRGproc is updated to work for the H2RG detector of TANSPEC and is set up on the TANSPEC server, ensuring users receive data that are pre-cleaned and non-linearity corrected.

FU Ori outbursts are thought to play a key role in stellar mass assembly and in the chemistry of protoplanetary disks during the early formation of stars. However, uncertainties remain regarding the universality of these events and the physical mechanism driving the high-amplitude variability. In this work, we present an analysis of optical, near- and mid-IR photometry (ZTF, UKIDSS GPS, NEOWISE) and near-IR spectra (IRTF, Gemini) of the eruptive variable Class I YSO GPSV16. The YSO, associated with the HII region G71.52$-$00.38 ($d=3.61$~kpc), showed two outbursts, one with $\Delta K_{\rm s}=2.2$~mag (2005-2012) and a second starting in 2016 with $\Delta K_{\rm s}=5.6$~mag and accretion luminosity of $\sim$130 L$_{\odot}$. The outbursts displayed distinct spectroscopic characteristics: the first showed emission lines associated with a hot inner disk surface, whereas the second showed absorption lines arising from the cooler upper layers of a viscously heated disk. These features likely arose due to the different accretion rates reached during each outburst. The second outburst showed a two-stage mid-IR rise, requiring $\approx8.4$ years to reach peak brightness. The mid-IR rise also started 8 years before the onset of the optical outburst. The wavelength-dependent light curve points to an instability that is triggered at larger distances within the accretion disk and propagates inward. Assuming a propagation time of 8 years for the accretion wave, we estimate that the second outburst started at a distance of $r\sim0.4$~AU. These results show how long-term, multi-wavelength photometric monitoring can help identify the disk instabilities that trigger eruptions in YSOs.

Over 50 circumbinary exoplanets have been discovered in recent years, with several of them being gas giants on wide orbits ($>10$AU). The aim of this work is to investigate whether these planets can form through circumbinary disc fragmentation due to gravitational instability. We perform hydrodynamic simulations of marginally unstable (i) circumstellar discs, (ii) circumbinary discs with the same temperature profile as the circumstellar discs (fiducial model), and (iii) realistic circumbinary discs heated individually by each star of the binary. We find that discs around binaries with wider separations fragment earlier and more efficiently than those around closer binaries, and earlier than circumstellar discs. Realistic circumbinary discs form a larger number of protoplanets ($9\pm0.9$ protoplanets per disc), than fiducial circumbinary ($6.5\pm0.6$), and circumstellar discs ($7.5\pm0.8$). In realistic circumbinary discs, initial protoplanet masses are lower than those formed in circumstellar discs, and a larger fraction of them lie in the planetary-mass regime, favouring the formation of gas giant planets over brown dwarfs or low-mass stars. Fragmentation occurs predominantly beyond a binary-imposed forbidden region of $\sim50$AU, leading to final orbital radii peaking at $\sim100$AU. We also find that in circumbinary discs dynamical interactions eject a higher fraction of protoplanets than in circumstellar discs, producing free-floating objects, with ejection velocities on the order of $2-6~{\rm km s^{-1}}$. We conclude that gravitational fragmentation of circumbinary discs is a viable and potentially significant formation pathway for circumbinary gas giant planets.

Uncertainties in the radial distribution of galaxies, $\boldsymbol{n}(\boldsymbol{z})$, are one of the major contributions to the error budget of early Stage-IV galaxy survey analyses of weak gravitational lensing, galaxy clustering and galaxy-galaxy lensing (3$\times$2-pt). Based on ensembles of simulated $\boldsymbol{n}(\boldsymbol{z})$ including stochastic and systematic variations, we study the impact of four different $\boldsymbol{n}(\boldsymbol{z})$ uncertainty models: shifts, shifts & stretches, Gaussian processes (GP) and principal component analysis (PCA). Due to the high dimensionality of the latter models, we make use of state-of-the-art gradient-based inference methods as well as approximate analytical marginalisation schemes. Our results show that Stage-IV 3$\times$2-pt analyses must go beyond simple shift & stretch models. In particular, we advocate for the adoption of PCA models even in early Stage-IV surveys. Our results show that considering a five-parameters PCA model only degrades the constraint on the $S_{\rm 8}$ parameter by $5$ per cent with respect to the case when only a shift and a stretch parameter are included, while incurring half the bias in its constituents parameters, $\Omega_{\rm m}$ and $\sigma_{\rm 8}$. We demonstrate that all models considered can be safely marginalised analytically, with speed-ups of up to a factor of 25 depending on the dimensionality of the model. This will allow Stage-IV analyses to safely include higher-dimensional $\boldsymbol{n}(\boldsymbol{z})$ uncertainty models in their analysis at negligible additional computational cost.

The upcoming imaging survey of the Chinese Space-station Survey Telescope (CSST) will deliver high-resolution imaging of an unprecedented number of galaxies for galaxy studies. To understand CSST's capability, and to support the preparation of early-science programs, we generate 470,526 mock CSST images for 22,406 simulated galaxies with $M_*>10^9 M_\odot$, whose parameters are calibrated to match real HST observations spanning photometric redshift $0<z\lesssim7$, across seven CSST filters and three planned survey depths: wide, deep, and extreme. We then perform source detection and Sérsic fitting. For point sources, we found that the 95% completeness magnitude in the g band reaches 26.3, 27.4, and 28.5 mag for the wide, deep, and extreme fields, respectively. For extended galaxies, their spatial extent dilutes the surface brightness, leading to brighter 95% completeness magnitudes of 24.4, 25.9, and 27.1 mag. The detection completeness remains above 95% at $z\lesssim3-4$ in the extreme field, while the corresponding redshift limits are $z\approx1$ in the deep field and $z\approx0.5$ in the wide field. Using three fitting codes, GALFIT, AstroPhot, and SourceXtractor++, we quantify measurement biases and uncertainties in galaxy magnitude ($m$), effective radius ($R_e$), effective surface brightness ($\mu_e$), Sérsic index ($n$), and axis ratio ($q$). On average, for fainter galaxies, the reduced signal-to-noise ratio leads to systematic overestimates in $m$, $R_e$, and $\mu_e$, and underestimates in $n$ and $q$. These biases, as well as the associated scatter, become progressively smaller in deeper fields. Overall, our results provide quantitative constraints on sample selection and the robustness of morphological measurements in CSST early-science and legacy surveys.

This paper develops a robust angles-only IROD method based on polynomial optimization for arbitrary nonlinear dynamics. First, the relative motion is approximated by high-order Taylor polynomials within the differential algebra framework, and the resulting cross-product-residual minimization problem is solved through a recursive polynomial optimization procedure. Second, a reduced-order weighting strategy is introduced by projecting the residual onto the two-dimensional tangent subspace of the line of sight, thereby structurally removing the intrinsic singularity of conventional three-dimensional weighting. Third, a zero-solution-avoidance constraint together with an adaptive threshold-selection mechanism is developed to improve robustness against poor initialization, strong measurement noise, and unfavorable observation geometries. Numerical simulations show that the proposed method improves IROD accuracy by about three orders of magnitude relative to the baseline methods, while also reducing the downstream orbit-refinement burden. The reduced-order weighting strategy further improves accuracy by about 43% in the nominal case and remains stable under large-noise conditions, outperforming the conventional three-dimensional weighting by about 81%.

The high-resolution near-infrared spectrograph CRIRES+ at ESO VLT covers the Y, J, H, K, L and M bands. The U-Ne and Fabry-Perot calibration light sources, however, only work up to the K-band, leaving the bands L and M without wavelength calibration, and without a way to measure the inclination of the long slit relative to the detector frame. To remedy this, we present here a uniformly reprocessed archive of all public CRIRES+ L/M science observations obtained between September 2021 and March 2025, totalling 11 131 raw frames. We use the telluric modelling tool viper that fits a model to the plethora of atmospheric absorption features that exist around these wavelengths. We calibrate the slit tilt from the wavelength solutions for the nodding A and B frames that have the target in the lower and upper half of the slit, respectively. We then update the static inputs to the data reduction system with the slit tilt information and reduce the data with the standard pipeline recipes. Subsequently, we derive new wavelength scales for each observation from telluric fits on the spectra themselves, additionally interpolating the solutions for spectra that have no tellurics from the ones that have. The resulting 5649 extracted, calibrated and telluric-fitted AB nod-pair spectra, spanning 156 unique targets from 68 ESO programmes, are served through an interactive web archive at this https URL that offers data downloads and figures for all datasets that allow an initial judgement of the data quality.

Context. Convolutional neural networks (CNNs) are widely used for automated galaxy morphological classification in large surveys. However, projection effects, image artefacts, and intrinsic degeneracies limit reliable identification of detailed features, requiring large-scale visual validation. Aims. To visually inspect SDSS galaxies at 0.02 < z < 0.1 classified by a CNN as merging, irregular, edge-on, barred, ringed, or dust-lane galaxies; assess CNN completeness and failure modes; construct visually verified morphological catalogues; and determine nuclear activity types via BPT diagrams. Methods. We visually inspected all galaxies assigned by the CNN to six morphological classes: merging (2,574), irregular (9,432), edge-on (17,000), barred (6,000), ringed (13,882), and dust-lane (588), regardless of CNN probability. Refined samples were cross-matched with Galaxy Zoo 2; remaining galaxies were classified here for the first time. Nuclear activity was determined from SDSS DR17 spectra using H{\alpha}\alpha {\alpha}, H\b{eta}\beta \b{eta}, [O III]\lambda$5007, and [N II] \lambda$6583 line ratios. Results. We present catalogues of 612 merging, 9,372 irregular, 16,822 edge-on, 575 dust-lane, 811 barred, and 2,150 ringed galaxies. CNN misclassifications stem primarily from projection effects, foreground stars, faint tidal features, and irregular star-forming structures. We characterise nuclear activity types for edge-on, barred, ringed, and dust-lane galaxies, finding systematic differences in LINER-like and composite fractions across subsamples. Five strong polar ring galaxy candidates were identified. Conclusions. Visual validation remains essential for refining CNN-based classifications. The resulting datasets support morphological studies, investigations of galaxy structure and secular evolution, and provide robust training samples for future machine learning models.

Light curves of oscillating stars provide valuable insights into the stellar interiors. When oscillations from a pair of stars are captured within a single photometric aperture, they can be considered as potential asteroseismic binaries (ABs). If the two stars oscillate at similar frequency ranges, the superpositioned oscillation patterns appear as if from a single star, leading to inaccurate asteroseismic parameters. We investigate seismically unresolved AB candidates consisting of two red-giant stars observed by Kepler. We directly compare the power density spectra (PDSs) of blended and separated oscillations from both stars, and examine the impact of oscillations from two stars on asteroseismic and stellar parameters. We selected APOKASC3 stars with at least one neighboring source within 20 arcsec and show oscillations in similar frequency ranges. We focus on the systems where the light curves from each star in AB candidates are available or can be extracted with a custom mask. We identified 6 seismically unresolved AB candidates whose PDS morphologies change noticeably across light curves extracted with different apertures. Oscillations from two stars in a PDS cause inaccurate mode identification and bias the seismic parameters. These biases propagate into stellar properties: masses and radii for the 6 AB candidates differ by up to about 3 and 2 times relative to the individual stars, respectively. For the AB candidate with the most complex PDS, core properties become unreliable, with the coupling factor often being overestimated. We checked that all 6 AB candidates are chance alignments. Our results indicate that the inconsistencies in asteroseismic and stellar parameters across different studies can be explained by potential seismically unresolved ABs. We highlight the importance of identifying and accurately accounting for such systems in asteroseismic analysis.

The origin and structure of the hot ($T\gtrsim10^6$ K) gaseous halo around Milky Way (MW)-mass galaxies provide a critical test for galaxy formation models. We perform a comprehensive comparison for a sample of MW analogues from the TNG50 cosmological simulation by generating synthetic soft X-ray emission and O VII/O VIII absorption lines. The simulated halos successfully reproduce the observed global soft X-ray luminosity and key inner-halo properties, including X-ray surface brightness, emission measure, and O VII absorption strength. However, two critical discrepancies are identified: (i) the simulated X-ray surface brightness profiles decline too steeply at large radii compared to extended eROSITA stacking emission, and (ii) the halos systematically underproduce O VIII absorption, indicating a deficit of hotter-phase gas at $T\sim(1.6-3.2)\times10^{6}$ K. These findings indicate that the simulated halos are spatially too compact and lack the hotter gas phase observed in real galaxies. This suggests that the feedback model in TNG50, while generating hot gas, may deposit its energy too centrally and too vigorously to sustain a gently extended, multi-phase corona.

Total solar eclipses (TSEs) offer a unique opportunity to observe the solar atmosphere, detect limb phenomena, and accurately measure the solar radius. Following the TSE in 1733, Wassenius first reported the existence of prominences to the scientific community. Wassenius' original manuscript is held in the Royal Academy Archives of Sweden; this study translates his report and documents the associated source materials and local eclipse visibility. The solar radius (R_Sun) during the TSE in 1733 are 696250 +/- 170 km and 959.99 +/- 0.24" in the absolute and apparent scales, respectively. This result contrasts with the modern standard (helioseismic) R_Sun of 695780 +/- 160 km and 959.34 +/- 0.22"; however, it is consistent with the solar radius recorded in 1715. The observed prominences are located at +23.5 +/- 22.5°, +66.5 +/- 22.5°, and -68.5 +/- 22.5° in the heliographic latitude. The appearance of prominences at such high latitudes contrasts with the sunspot butterfly diagram for 1725-1750, confirming 1733 as a solar minimum. These high-latitude prominences can potentially be attributed to the so-called 'polar rush' prominences that appear a few years after a solar minimum. If they are categorised as 'polar rush' prominences, the solar minimum must be re-dated to before 1733 May. Furthermore, the latitudes of at least two of the prominences reported by Wassenius enable their classification as quiescent prominences, suggesting the presence of a polarity inversion line in the polar regions in early 1733.

In recent years, several aromatic molecules (benzene-based rings) have been detected in the cold molecular cloud TMC-1, with its CN-derivative, benzonitrile (c-C$_6$H$_5$CN), also identified in other nearby cold sources. However, observed abundances differ significantly from chemical model predictions, indicating an incomplete understanding of its chemistry and motivating searches in distinct environments. We report new detections of benzonitrile in two warmer molecular clouds of the Central Molecular Zone (CMZ): G+0.693-0.027 and G+0.633-0.0604. Using Yebes 40m ultra-deep surveys in the 31--50 GHz range, we performed LTE and non-LTE analyses to derive the physical parameters of the emission. We obtain column densities of $N$=(7.4$\pm$0.5)$\times10^{12}$ and (2.60$\pm$0.13)$\times10^{12}$ cm$^{-2}$, corresponding to abundances relative to H$_2$ of (6$\pm$1)$\times10^{-11}$ and (4.3$\pm$0.9)$\times10^{-11}$, consistent with values in cold Galactic clouds. The HC$_7$N/benzonitrile ratio is lower (2.15-2.4) than in colder sources (4.5-30), suggesting environmental effects and a relative enhancement of aromatic chemistry in the CMZ. These results confirm that benzonitrile is widespread and can survive in harsher environments (e.g., high temperatures, shocks, enhanced cosmic-ray ionization) than those in Galactic cold clouds. This suggests that aromatics are stable and abundant species that can significantly contribute to the total budget of interstellar carbon in molecular clouds. A top-down formation scenario, involving fragmentation of larger carbonaceous species, is consistent with the nearly constant abundances observed with molecular size.

With the rapid development of time-domain surveys, the availability of massive light curve data offers new opportunities for studying stellar evolution and variable star classification, while simultaneously posing challenges for feature extraction and modeling. We present StarCLR, a contrastive pretraining framework for large-scale light curves. By constructing positive pairs from partially overlapping sub-sequences, StarCLR encourages the model to learn temporal representations. We pretrain StarCLR on the TESS dataset and fine-tune it for variable star classification on three surveys with distinct observational characteristics, namely TESS (18 types), ZTF (11 types), and Gaia (24 types). StarCLR achieves macro-F1 scores of 84.35%, 87.82%, and 92.73%, and micro-F1 scores of 94.46%, 92.83%, and 99.49%, respectively. Compared with LSTM and Transformer trained from scratch, StarCLR performs better on TESS and ZTF, with the largest gains on sparsely sampled ZTF light curves, demonstrating promising generalization. For Gaia, which involves a broader class space, the evaluation is not directly comparable, and performance is likely influenced by astrophysical features, resulting in a more limited contribution from the pretrained backbone. Systematic ablations on embedding design, pooling strategy, and pretraining settings further indicate that the pretrained representations provide performance gains by capturing informative temporal characteristics of light curves. Looking ahead, with standardized datasets and more diverse labeling schemes, the generalization ability of StarCLR can be further enhanced.

On April 13, 2029, the asteroid Apophis will pass near Earth at a geocentric distance of about 38,000 km. Numerical models have suggested that the post-encounter spin state will critically depend on the orientation of Apophis during the flyby. We aim to determine the spin state of Apophis from its photometric observations collected during two apparitions in 2012-2013 and 2020-2021. This will enable us to accurately predict the pre-encounter rotation state and, by accounting for Earth's gravitational torque, predict a range of possible post-encounter states. We used the light curve inversion method for tumbling asteroids to reconstruct the spin state of Apophis and its convex shape model. The result is adopted as the initial condition of a numerical model describing Apophis's future rotation state. The data from the two apparitions are insufficient to determine Apophis's rotation and precession periods uniquely. The formally best-fit solution is 27.374 +/- 0.001 h for the precession period and 262.2 +/- 0.1 h for the rotation period, but at least two other combinations of the periods provide a similarly good fit to the available data. All the currently acceptable models result in approximately the same pre-encounter orientation of Apophis in early 2029. This is because the accurate photometric data were collected during two apparitions separated by 8 years, which is the same interval as from 2021 to 2029. Although the close encounter with Earth in April 2029 hugely increases the post-encounter uncertainty of Apophis's spin state, the short-axis spin mode will be preserved with a high likelihood. Additional observations taken in 2027 and 2028 will break the ambiguity in Apophis's pre-encounter spin solution and allow us to get a more accurate post-encounter spin state prediction

Context. High-resolution X-ray spectroscopy offers a powerful tool to investigate the physical and chemical properties of dust grains, especially through the analysis of absorption edges of elements such as oxygen, magnesium, silicon, and iron, which are the main constituents of interstellar dust. In all previous X-ray studies, these absorption edges have been modeled assuming the MRN grain size distribution. This model successfully reproduces the average interstellar extinction curve. However, with the advent of new observations, it shows important limitations, indicating that more complex grain-size distributions are required to fully describe interstellar dust properties. Aims. We aim to constrain the composition and size distribution of interstellar dust along the line of sight to the bright low-mass X-ray binary GX 13+1. Methods. We analyzed high-resolution X-ray spectra obtained with the Chandra HETG instrument (MEG+1 and MEG-3) and simultaneously modeled the Si K and Mg K absorption edges. For the first time, we compared the classical Mathis et al. 1977, ApJ, 217, 425 grain size distribution with other grain size distributions, thus exploring different ISM densities. Results. Our analysis rules out scenarios of both very diffuse and very dense ISM, favoring grain size distributions associated with average Galactic conditions along this line of sight. The dust composition is found to be dominated by amorphous olivine and the crystallinity contribution is about 2%. The depletion patterns and elemental abundances derived are consistent with prior X-ray and infrared studies.

HD~20794 is a nearby, bright, metal-poor G-type dwarf hosting a compact planetary system, including a super-Earth near the habitable zone. Its low stellar activity and the availability of precise radial-velocity and photometric data make it an excellent benchmark for studying stellar structure and chemical abundances in low-metallicity planet-hosting stars. We present, to our knowledge, the first grid-based stellar evolution analysis of HD~20794 using \texttt{MESA}, focusing on its main-sequence and late main-sequence evolution. A set of 252 stellar models was computed for initial masses between $0.78$ and $0.80\,M_{\odot}$, varying convective efficiency, numerical resolution, and atmospheric boundary conditions. Models were selected through $\chi^2$ minimization using observed constraints on effective temperature, surface gravity, luminosity, radius, and age. The best-fit models favor a mass of $0.80\,M_{\odot}$ and an age of about $9$~Gyr, reproducing all observed stellar properties within uncertainties. They also successfully recover the observed surface abundance pattern over a wide range of elements, including light elements, $\alpha$-elements, and the odd-$Z$ species phosphorus and chlorine. Comparison with nucleosynthesis yields from massive stars suggests that the measured phosphorus and chlorine abundances are compatible with enrichment from core-collapse supernovae and have remained preserved during stellar evolution. Our results support standard stellar evolution theory, indicating that low-mass, metal-poor G dwarfs such as HD~20794 can retain their natal chemical signatures over Gyr timescales. This highlights their importance as probes of stellar evolution, Galactic chemical enrichment, and the chemical environments associated with long-lived planetary systems.

Aphelion Thermospheric Polar Warming (TPW), first identified in 2024 by Mars Atmosphere and Volatile EvolutioN (MAVEN) observations, is a dynamical heating phenomenon in the Martian atmosphere that exists in the winter hemisphere near the aphelion solstice. Studying the formation mechanism of aphelion TPW will help us better understand the energy budget of the Martian thermosphere. In this study, we investigate aphelion TPW using the Mars Global Ionosphere Thermosphere global circulation model (M-GITM). The simulation results show that the local dust storms have little impact on the formation of aphelion TPW. The simulated thermospheric temperature difference between the polar region and the low-latitude region is considerably lower than the value observed, which suggests that some important atmospheric processes are not captured by M-GITM. To investigate potential causes, we conduct sensitivity tests on solar insolation, gravity waves, and model horizontal resolution. The sensitivity test on solar insolation shows that the magnitude of aphelion TPW increases with increasing solar insolation. We also find that gravity waves play a critical role in modulating dynamical heating, as their suppression increases the latitudinal temperature difference. Model resolution has minimal impact on polar warming but affects thermospheric structure at low latitudes. These findings highlight the importance of refining the representation of dynamical processes, especially the parameterization of subgrid-scale internal gravity waves in the Martian general circulation model to better capture thermospheric dynamics.

The details of the spiral structure of the Milky Way are still debated due to large uncertainties in the distance estimates obtained through the most common tracers. X-ray dust scattering rings produced by short extragalactic X-ray transients provide instead a direct method to measure the 3D distribution of interstellar clouds up to the edges of our Galaxy with a few percent precision. We report on the analysis of all the available XMM-Newton and Chandra follow-up observations of three low-latitude gamma-ray bursts: GRB 031203 ($l \sim 255°$, $b \sim -5°$), GRB 160623A ($l \sim 84°$, $b \sim -3°$), and GRB 221009A ($l \sim 53°$, $b \sim 4°$). The previous detection of X-ray rings in these observations, produced by dust clouds located beyond 5 kpc, can be associated with dust in the Perseus, Outer, and Outer Scutum-Centaurus arms, thus providing direct distance measurements to these structures along three distinct lines of sight. We have identified two additional rings in the direction of GRB 160623A, produced by dusty clouds at $6.91\, \pm\,0.06$ kpc and $9.9\,\pm\,0.6$ kpc, and confirmed -- through a second XMM-Newton observation -- the presence of one cloud at $9.7\,\pm\,0.4$ kpc toward GRB 031203. We also accurately measured the distance of dusty clouds up to $19.0\,\pm\,0.2$ kpc owing to the analysis of one Chandra and four XMM-Newton observations of GRB 221009A. The small statistical and systematic uncertainties of these measurements place tight constraints on the geometry of the outer Milky Way and reveal significant deviations from current models, which critically depend on spectroscopy-based Galactic rotation curves at large distances.

Cosmological analyses using the latest set of type Ia SNe data weakly favor an evolving dark energy (EDE) model without strongly disfavoring the standard LCDM paradigm. Nonparametric reconstructions of the expansion history may reveal signal features potentially missed by a parametric LCDM model without laying out a specific functional form for the evolution of dark energy. Information field theory (IFT) is a Bayesian framework for optimal, nonparametric reconstruction algorithms. In this work, we present charm2, the successor to charm1, a previous IFT-based code to reconstruct the cosmic energy density's redshift evolution from SNe Ia. We apply our reconstruction algorithm to the Union2.1, Pantheon+, DESY5 and DESY5-Dovekie data sets to investigate the agreement between the nonparametric reconstruction and the signal suggested by a parametric, flat LCDM model. To enable an accurate Gaussian approximation, we employ geometric variational inference, which finds a coordinate transformation through which a curved posterior gets "flattened". The redshift evolution of the energy density can then be traced on a double-logarithmic scale, which, after de-trending, is well described by a stationary Gaussian process. The nonparametric charm2 reconstructions using the Union2.1 and Pantheon+ data sets are consistent with flat LCDM signal fields. The DESY5 and DESY5-Dovekie reconstructions deviate from flat LCDM comparison fields and are compatible with an evolving dark energy signal. However, using the evidence lower bound (ELBO) measure for model selection, we find no conclusive evidence supporting a preference for non-flat-LCDM features in any of the data sets. We note that at current DESY5 noise levels, the ELBO tends to favor flat LCDM over our nonparametric model although the latter better recovers the ground truth in synthetic EDE data; a trend reversing only at ~7x lower noise covariance.

A recently developed model-independent approach to measuring the Weyl potential has shown some tensions with $\Lambda$CDM (Lambda Cold Dark Matter) in DES (Dark Energy Survey) Y3 data. We apply this framework to Kilo-Degree Survey (KiDS-1000) weak lensing and BOSS/2dFLenS galaxy clustering using the KiDS Cosmology Analysis Pipeline (KCAP) in two redshift bins. Without external CMB priors, both the Weyl potential and $E_G$ measurements are consistent with late time constraints. After imposing Planck18 priors, the low redshift bin remains compatible with General Relativity, whereas the high redshift bin shows a weaker Weyl potential and lower $E_G$, corresponding to a mild $1.52\sigma$ deviation from the $\Lambda$CDM cosmology. Furthermore, phenomenological modified gravity models show a mild preference for a suppressed high redshift Weyl potential, but late time data alone remain consistent with $\Lambda$CDM. Our results also suggest that this deviation is primarily driven by the specific high redshift CMASS sample, reflecting the well-known ``Lensing is low'' problem.

Numerical analysis to determine the form of the scalar power spectrum in Warm Inflationary paradigm is inevitable. One further needs numerical techniques to analyse any Warm Inflation model with the current observational data through the MCMC codes that are available publicly, like COSMOMC or Cobaya. We present \texttt{SWIM} (Stochastic Warm Inflation Module) written in C++ and Python, that not only helps generate the Warm Inflationary scalar power spectrum, either semi-analytically or fully numerically, but also is integrated with Cobaya enabling the user to constrain the model parameters with current CMB data and thus to put any Warm Inflation model to test. \texttt{SWIM} numerically solves the standard stochastic perturbation equations of Warm Inflation without any approximations, uses machine learning techniques to speed up the MCMC analysis while analysing the fully numerical power spectrum that significantly reduces the computational cost, and is able to accommodate any Warm Inflation model with any form of inflationary potential and dissipative coefficient for numerical analysis. We show that \texttt{SWIM}, in most of the cases, outperforms other numerical codes on Warm Inflation that are designed to yield only the semi-analytical power spectrum as far as the runtimes are concerned. We further point out that there can be situations where the semi-analytical way of determining the scalar power spectrum in Warm Inflation can fall short, and one needs the full numerical power spectrum for parameter estimation given the observational data. In such cases, \texttt{SWIM} is the only code available so far that is designed to perform the task. Hence, \texttt{SWIM} offers a complete numerical platform for thorough analysis of Warm Inflation models against the current cosmological data. \texttt{SWIM} has been made publicly available at this https URL.

We present a kinematic study of six infrared-luminous galaxies observed with the Mid-InfraRed Instrument Medium-Resolution Spectrometer (MIRI/MRS) onboard JWST. These galaxies lie at $z = 0.5$--$0.6$, midway between the present day and the peak of cosmic star formation. Our sample spans a range of star formation (SF) and active galactic nucleus (AGN) contributions to the mid-infrared emission. We characterize the dynamical state of these IR-luminous galaxies and assess how AGN activity influences the kinematics of the interstellar medium. Using mid-IR atomic lines, we map galaxy kinematics beyond the local Universe for the first time. The spatial resolution of MIRI/MRS (3.0 kpc for 0.46$\arcsec$ at z $\sim$ 0.55) allows us to resolve the internal kinematics of our targets. We compute kinematic maps in three different emission lines ([Ar II]6.99$\mu$m, [Ne II]12.81$\mu$m, and H$_2$ 0-0 S(5)6.91$\mu$m). Using the [Ar II]6.99$\mu$m kinematic maps, we derive rotation curves for these sources. All galaxies exhibit ordered rotation, with \(V/\sigma \geq 2\), consistent with stable disks. Although some show minor disturbances, we find no strong evidence for recent major mergers or galaxy-wide ionized outflows. We find no correlation between \(V/\sigma\) and AGN fraction, suggesting AGN activity does not significantly disrupt global kinematics or that disk disruption is not required to trigger AGN. However, galaxies with higher AGN fractions show elevated central dispersions, indicating localized turbulence, possibly due to AGN feedback, stellar feedback, accretion or bulge structure. These IR-luminous galaxies likely represent mature, rotationally supported disks, with AGN activation occurring after disk assembly.

We present the results of broad-line region (BLR) dynamical modeling for eight high-mass active galactic nuclei (AGNs) from the Seoul National University AGN Monitoring Project, by constraining BLR geometry and kinematics as well as black hole (BH) mass ($M_{\rm BH}$). We find that the H$\beta$-emitting BLRs are best described as thick disks viewed at intermediate inclinations, with emission preferentially originating from the far side of the BLR. BLR kinematics show a combination of rotational, inflowing and outflowing components. By comparing the $M_{\rm BH}$ from dynamical modeling with the virial products based on reverberation lags and line widths, we determine the virial factor $f$ for individual AGNs. Combining our sample with those $M_{\rm BH}$ consistently determined from BLR dynamical modeling, yielding a total of 38 objects, we derive a virial factor for future $M_{\rm BH}$ estimation of log$_{10}({f})_{\rm pred}=0.69\pm0.21$ based on $\sigma_{\rm line,rms}$ and $-0.08\pm0.23$ based on FWHM$_{\rm mean}$. The derived virial factor is consistent with that inferred by aligning the reverberation-mapped AGNs with quiescent galaxies in the $M_{\rm BH}$-$\sigma_{\ast}$relation, supporting the assumption that local active and inactive galaxies follow the same $M_{\rm BH}$-$\sigma_{\ast}$ relation. Our updated $f$ values exhibit an intrinsic dispersion of $\sim0.2$ dex, which allows for a more precise $M_{\rm BH}$ estimates than those based on the $M_{\rm BH}$-$\sigma_{\ast}$ relation. Our sample extends the dynamical modeling-based reverberation sample to $M_{\rm BH}$ $\sim$ [$10^8$, $10^{8.5}$] $M_{\odot}$ range, where the virial factor from the the AGN $M_{\rm BH}$-$\sigma_{\ast}$ relation remains poorly constrained, underscoring the unique value of dynamical modeling analysis in constraining the $M_{\rm BH}$ of the most massive BHs.

The Gaia DR3, released in June 2022, included low-resolution BP/RP (XP) spectra that have been exploited for the classification of various types of emission-line objects using machine-learning techniques. The Gaia Extended Stellar Parametrizer for Emission-Line Stars (ESP-ELS) algorithm identified 273 sources as potential planetary nebulae (PNe). We aim to analyze the PN sample produced by the ESP-ELS algorithm to investigate the true nature of the objects classified as PNe. We extracted all sources from the catalog classified as PNe by the ESP-ELS algorithm and filtered out 200 objects with secure classifications available in the literature. Of these, $\sim$65% correspond to known Galactic or Magellanic compact PNe, and $\sim$20% to D- or D'-type symbiotic systems. The XP spectra of the remaining sources were visually inspected, leading to a subset of 14 promising candidates showing strong emission features attributable to H$\alpha$ and [O III] $\lambda$5007. Although typical of PNe, such features are also consistent with D- or D'-type symbiotics, known to mimic compact PNe. We obtained spectroscopic follow-up observations for these objects with the 2SPOT facilities in Chile and France, complemented by an analysis of archival photometric data to further constrain their nature. We report the identification of nine bona-fide or likely D- or D'-type symbiotic systems, one planetary nebula in the LMC, one polar cataclysmic variable, and three possible Be stars in (or in the direction of) the SMC, within our sample of 14 objects.

The crust of a neutron star (NS) provides a unique laboratory for studying matter under extreme density and magnetic field conditions that cannot be realized in terrestrial experiments. However, direct observational constraints on its composition have remained very limited. Magnetar bursts provide a promising means to probe the nuclear composition of the outer crust, as their energy release may be associated with stress-driven yielding of the crustal Coulomb lattice (including plastic deformation) and magnetic reconnection in the surrounding magnetosphere. We develop a general-purpose radiative transfer framework for a strongly magnetized electron--ion thermal plasma (MEITP) and apply it to the observed X-ray burst spectra. The spectral fits disfavor light-ion compositions and instead favor plasmas characterized by effective charge numbers around $Z \sim 37$. These results provide spectral evidence for the participation of heavy nuclei in magnetar bursts, offer new observational constraints on the baryonic content and the location of the emitting fireballs, and further imply a crustal origin of the heavy ions.

Investigating the chemical complexity of the interstellar medium (ISM) is key for understanding its physical nature and evolution. In this work, we study parsec-scale interstellar dust clouds in the neutral ISM of the Milky Way using two different probes: dust depletion and dust extinction. We examine their relationship to investigate the distribution of metals and dust in the Solar neighbourhood, and how they are related to the Local Bubble. We use measurements of dust depletion for individual gas clouds along sight lines of sight towards bright O/B stars within 1.1 kpc of the Sun, derived from UV absorption-line spectra. We combine these with parsec-scale 3D dust extinction density maps out to 1.25 kpc. We assume a correlation between dust depletion and dust extinction density, which we use to imply that the absorption components are spatially associated with the peaks in dust extinction density, and to pinpoint the likely locations of the gas clouds in physical this http URL identify peaks in the dust extinction curves, and then associate the stronger peaks with the strongest dust depletion components. Independent distance measurements along the line of sight towards one of our targets, theta1 Ori C, validates our results. In our sample, the minimum distance between clouds that have significantly different chemical properties is ~ 100pc, giving an indication on the physical scale on which chemical mixing remains incomplete in the ISM of the Milky Way. For five of the eight targets, we report dust depletion values for gas clouds associated with the Local Bubble. Additionally, we find a velocity gradient that is consistent with the expansion of the Local Bubble, further supporting our methodology. Overall, we show that it is possible to use complementary information from dust depletion and dust extinction to build more detailed maps of ISM metal and dust distributions.

Multiple mechanisms are proposed for the formation of giant molecular clouds (GMCs), from gravitational free-fall caused by self-gravity to stellar feedback-driven gas compression. Both the galactic environment and galaxy conditions could play an additional role in enhancing the formation via their gas surface density and star formation activity. In this paper, we make use of a catalog of 108,466 GMCs identified by F770W PHANGS--JWST imaging across 66 galaxies at a homogenized resolution of 30~pc. We measure the mass spectra in various galactic regions, whose power-law slopes vary from $-1.2$ to $-2.0$. We then estimate the formation time of each cloud using a model where GMCs form from multiple feedback compression, and find that clouds with masses $\leq 10^{5}\,M_{\odot}$ form, on average, in 20~Myr, with more massive clouds ($\sim 10^{6}$--$10^{7}\,M_{\odot}$) taking up to 100~Myr. We also find that cloud formation proceeds most rapidly in the central regions of galaxies, with formation timescales that are typically shorter by $\sim 5$--$10$~Myr compared to galactic disks. This effect is most pronounced in central molecular zones with enhanced star formation, highlighting the role of intense massive star formation, high molecular gas surface densities, and strong supersonic compressions in accelerating cloud formation. However, star formation is generally inefficient as the cloud lifetime is $\sim 1\,\%$ of the molecular depletion time. The formation time of clouds is $\sim 0.1$~dex longer than the free-fall time. This hints that magnetic fields, stellar feedback, or other mechanisms may prolong their formation instead of immediate free-fall collapse. This indicates a longevity of massive GMCs. The GMC ages also show only limited variation with galactocentric radius in both spiral and disk galaxies, suggesting that cloud formation proceeds similarly in these galaxy types.

Type Ia supernovae (SNIa) play a central role in constraining the late-time expansion history of the Universe and are directly implicated in current cosmological tensions. Motivated by the possibility of unaccounted redshift-dependent calibration systematics or new physics, we investigate the impact of a phenomenological correction to SNIa magnitudes that scales with cosmic look-back time. We parameterize this effect with a free amplitude and constrain it using a combination of cosmic microwave background, baryon acoustic oscillation, and SNIa data, considering both $\Lambda$CDM and dynamical dark energy models. Importantly, our parameterization is not intended to serve as a proxy for SNIa progenitor age, as current observations show no significant difference in standardized SNIa brightness between young and old progenitor populations at low redshift. We find no evidence for a redshift-dependent calibration effect when fitting uncalibrated SNIa data, and its inclusion has a negligible impact on cosmological parameters within $\Lambda$CDM, nor does it qualitatively change the inferred dynamics of evolving dark energy. When incorporating a prior on the SNIa absolute magnitude from SH0ES, a nonzero calibration parameter is weakly preferred within $\Lambda$CDM. Interestingly, with dynamical dark energy, the preference of a nonzero calibration parameter increases to $4.3\sigma$, and it can accommodate both the distance ladder and early-Universe constraints, reducing the Hubble tension to $1.5\sigma$, with the best-fit model effectively corresponding to a constant equation of state with $w < -1$. Overall, our results indicate that redshift-dependent SNIa calibration effects, as parameterized here, are not supported by current data within $\Lambda$CDM, but can play a role in reconciling cosmological datasets when combined with extensions to the late-time expansion history.

This paper presents an integrated lander-propulsion-GNC framework for autonomous lunar powered descent. The BUG VTVL test vehicle serves as the reference platform, with the YUNT V0 throttleable bipropellant engine providing variable thrust across a wide operating envelope, integrated with a real-time successive convexification guidance solver. The vehicle design accounts for structural configuration, landing stability, center-of-mass migration, and inertia evolution, while the propulsion architecture defines the throttle ratio, dead-zone behavior, and gimbal authority that constrain the guidance problem. A successive convexification algorithm addresses all nonconvexities; thrust lower bounds, mass depletion coupling, and thruster dead-zone behavior are all handled within a unified second-order cone program solvable in near-real time. Parametric analysis reveals a fundamental coupling between throttle ratio, pointing authority, and surface gravity. Monte Carlo simulations validate guidance robustness, achieving sub-50-meter landing precision under realistic perturbations.

Kinetic Inductance Detectors (KIDs) are a promising technology for future space missions, where exposure to high-energy particles may affect detector performance. In this work, we irradiated two types of KID arrays, absorber coupled and antenna coupled, with high-energy protons at 120 mK. We used a total dose equivalent to approximately 10 years of operation at the L2 Lagrange point. A comparison between pre-irradiation and post-irradiation measurements (24 hours after a 5.7 krad total dose) was done, while keeping the detectors at 120 mK. We find that there is no significant change in the quasi-particle lifetime {\tau}_qp and the dark responsivity d{\theta}/dPdark, but we do observe an increase in the noise and NEP that is tentatively attributed to limitations in the post radiation data analysis.

Spectral problems governed by differential operators underpin a wide range of physical systems, yet remain computationally challenging because their spectra depend sensitively on continuous parameters and often demand repeated evaluations across parameter space. Here we present $\texttt{DeepOPiraKAN}$, an open source physics informed neural network architecture for spectral analysis. By combining operator learning with enhanced optimization stability, it captures the underlying parameter-to-spectrum mapping in a single model, avoiding repeated spectral solutions at isolated points in parameter space. As a representative and stringent benchmark, we apply this framework to the computation of quasinormal modes of Kerr black holes. A single trained network accurately resolves modes with $(\ell,m)\in \{(2,0),(2,1)\}$ and overtones up to $n=7$ across the full spin range, achieving relative errors of $\mathcal{O}(10^{-6})$ for the fundamental mode and gradually increasing to $\mathcal{O}(10^{-4})$ for higher overtones, benchmarked against the Leaver's method. This level of accuracy is already significant for black hole spectroscopy and practical ringdown modelling for current and future observatories. More broadly, these results highlight the potential of $\texttt{DeepOPiraKAN}$ as a general and scalable framework for parameter dependent spectral problems across complex physical systems.

The space-borne gravitational-wave (GW) detectors will open a new mass and redshift regime, allowing us to observe massive black hole binaries (MBHBs) throughout the Universe. A subset of these systems is expected to produce electromagnetic (EM) counterparts, offering a unique opportunity to follow the continuous evolution of massive black holes through joint GW and EM observations. Realizing this potential, however, requires low-latency, high-throughput data-analysis pipelines that can extract reliable source parameters and sky localizations from space-borne data streams fast enough to trigger EM follow-up. In this work we develop a fast, normalising flow-based inference pipeline designed for early-warning analysis of MBHB signals in a TianQin-like configuration. Our method combines a learned embedding of the detector time series with a neural spline flow (NSF) to perform amortized Bayesian inference, producing posterior samples for the main source parameters in roughly one minute per event. For a representative MBHB whose merger occurs $\sim 15$ minutes after the end of the analyzed GW observation, the pipeline achieves pre-merger sky localizations of order $\sim 20~\mathrm{deg}^2$, recovers the same number of sky modes as a reference parallel-tempered Markov chain Monte Carlo (PTMCMC) analysis, and yields parameter uncertainties of comparable scale, while still operating within a practically useful pre-merger warning window. These results demonstrate that NSF-based inference can deliver accurate, near-real-time parameter estimation for space-borne MBHB GW signals, and that the resulting early-warning localizations are sufficiently precise to make rapid EM follow-up.

Gravitational wave (GW) observations provide a unique opportunity to test Einstein's General Relativity (GR) in the strong-field regime. While GR predicts only two tensor polarization modes, generic metric theories allow up to six independent modes. We perform a parameterized test of GR using the parameterized post-Einsteinian (PPE) framework applied to GW170817, incorporating for the first time the polarization angle constraints from the gamma-ray burst afterglow alongside other electromagnetic (EM) counterpart information. We extend the GR waveform by adding a scalar breathing mode and modifications to the tensor modes, introducing three non-GR parameters. We perform Bayesian inference for both quadrupole $\ell = |m|= 2$ and dipole $\ell = |m|= 1$ angular harmonics, with two frequency evolution models. For $\ell = |m|= 2$ , we find mild preference for a scalar mode (scalar amplitude deviates from zero at $\sim 2 \sigma$), while for the $\ell = |m|= 1$, we find no preference for a scalar mode. The EM constraint on the polarization angle places very tight bounds on non-GR parameters; for instance, in the case $\ell = |m| = 2$, the bound on the scalar (tensor) amplitude modification parameter improves by roughly $60\%$ $(30\%)$, highlighting the impact that long-term follow up of GW events can have on tests of gravity.

Vision-language models (VLMs) are increasingly proposed as general-purpose tools for scientific data interpretation, yet their reliability on real astronomical observations across diverse modalities remains untested. We present AstroVLBench, a comprehensive benchmark comprising over 4,100 expert-verified instances across five tasks spanning optical imaging, radio interferometry, multi-wavelength photometry, time-domain light curves, and optical spectroscopy. Evaluating six frontier models, we find that performance is strongly modality-dependent: while one model (Gemini 3 Pro) emerges as the most consistently capable across tasks, task-specific strengths vary, and all models substantially underperform domain-specialized methods. Mechanistic ablations reveal that performance depends not only on directing attention to salient visual features but also on grounding those features in physical knowledge. Phenomenological prompts describing what to look for improve accuracy by sharpening model focus, but physical prompts explaining why those features matter perform better overall and yield more balanced classifications with reduced class-specific bias. Consistent with this picture, presenting the underlying one-dimensional measurements directly as numerical tables instead of rendered plots yields up to 13 percentage points improvement. Reasoning quality analysis further demonstrates that, without explicit physical grounding, models may reach correct predictions from phenomenologically plausible cues while providing physically imprecise justifications, establishing that accuracy alone is insufficient for trustworthy scientific deployment. These findings provide the first systematic, multi-modal baselines for VLMs in observational astronomy and identify the specific representation, grounding, and reasoning bottlenecks where current models fail.