Daily Papers

Active Galactic Nuclei (AGN) are some of the most luminous and extreme environments in the Universe. The central engines of AGN, believed to be super-massive black-holes, are fed by accretion discs threaded by magnetic fields within a dense magneto-ionic medium. We report our findings from polarimetric Very-long-baseline Interferometry (VLBI) observations of quasar NRAO150 taken in October 2022 using a combined network of the Very Long Baseline Array (VLBA) and Effelsberg 100-m Radio Telescope. These observations are the first co-temporal multi-frequency polarimetric VLBI observations of NRAO150 at frequencies above 15GHz. We use the new VLBI polarization calibration procedure, GPCAL, with polarization observations of frequencies of 12GHz, 15GHz, 24GHz, and 43GHz of NRAO150. From these observations, we measure Faraday rotation. Using our measurement of Faraday rotation, we also derive the intrinsic electric vector position angle (EVPA0) for the source. As a complementary measurement we determine the behavior of polarization as a function of observed frequency. The polarization from NRAO150 only comes from the core region, with a peak polarization intensity occurring at 24GHz. Across the core region of NRAO150 we see clear gradients in Faraday rotation and EVPA0 values that are aligned with the direction of the jet curving around the core region. We find that for the majority of the polarized region the polarization fraction is greater at higher frequencies, with intrinsic polarization fractions in the core 3%. The Faraday rotation gradients and circular patterns in EVPA0 are strong evidence for a helical/toroidal magnetic field, and the presence of low intrinsic polarization fractions indicate that the polarized emission and hence the helical/toroidal magnetic field, occur within the innermost jet.

We describe the design and commissioning tests for the DSA-110 Not-So-Fast Radio Burst (NSFRB) search pipeline, a 1.4 GHz image-plane single-pulse search sensitive to 134 ms-160.8 s radio bursts. Extending the pulse width range of the Fast Radio Burst (FRB) search by 3 orders of magnitude, the NSFRB search is sensitive to the recently-discovered Galactic Long Period Radio Transients (LPRTs). The NSFRB search operates in real-time, utilizing a custom GPU-accelerated search code, cerberus, implemented in Python with JAX. We summarize successful commissioning sensitivity tests with continuum sources and pulsar B0329+54, estimating the 6sigma flux (fluence) threshold to be ~290 mJy (~40 Jy ms). Future tests of recovery of longer timescale transients, e.g. CHIME J1634+44, are planned to supplement injection testing and B0329+54 observations. An offline DSA-110 NSFRB Galactic Plane Survey was conducted to search for LPRTs, covering -3.5^circ<b<5.7^circ and 141^circ<l<225^circ (~770 square degrees) in Galactic coordinates. We estimate an upper limit Poissonian burst rate ~1 hr^{-1} per square degree (~7 hr^{-1} per 3^circtimes3^circ survey grid cell) maximized across the inner |b|<0.25^circ of the surveyed region. By imposing the ~290 mJy flux limit on two representative models (the magnetar plastic flow model and the White Dwarf-M Dwarf binary model), we reject with 95% confidence the presence of White Dwarf-M Dwarf binary LPRTs with periods between ~10-70s within ~95% of the surveyed region. Combined with the prevalence of LPRTs in the Galactic Plane, our results motivate further consideration of both White Dwarf-M Dwarf binary models and isolated magnetar models. We will continue to explore novel LPRT search strategies during real-time operations, such as triggered periodicity searches and additional targeted surveys.

In this work we propose an analytical model that reproduces the core-bounds phase of gravitational waves (GW) of Rapidly Rotating (RR) from Core Collapse Supernovae (CCSNe), as a function of three parameters, the arrival time tau, the ratio of the kinetic and potential energy beta and a phenomenological parameter alpha related to rotation and equation of state (EOS). To validate the model we use 126 waveforms from the Richers catalog Richers_2017 selected with the criteria of exploring a range of rotation profiles, and involving EOS. To quantify the degree of accuracy of the proposed model, with a particular focus on the rotation parameter beta, we show that the average Fitting Factor (FF) between the simulated waveforms with the templates is 94.4\%. In order to estimate the parameters we propose a frequentist matched filtering approach in real interferometric noise which does not require assigning any priors. We use the Matched Filter (MF) technique, where we inject a bank of templates considering simulated colored Gaussian noise and the real noise of O3L1. For example for A300w6.00\_BHBLP at 10Kpc we obtain a standar deviation of sigma = 3.34times 10^{-3} for simulated colored Gaussian noise and sigma= 1.46times 10^{-2} for real noise. On the other hand, from the asymptotic expansion of the variance we obtain the theoretical minimum error for beta at 10 kpc and optimal orientation. The estimation error in this case is from 10^{-2} to 10^{-3} as beta increases. We show that the results of the estimation error of beta for the 3-parameter space (3D) is consistent with the single-parameter space (1D), which allows us to conclude that beta is decoupled from the others two parameters.

The advent of next-generation radio telescopes is set to transform radio astronomy by producing massive data volumes that challenge traditional processing methods. Deep learning techniques have shown strong potential in automating radio analysis tasks, yet are often constrained by the limited availability of large annotated datasets. Recent progress in self-supervised learning has led to foundational radio vision models, but adapting them for new tasks typically requires coding expertise, limiting their accessibility to a broader astronomical community. Text-based AI interfaces offer a promising alternative by enabling task-specific queries and example-driven learning. In this context, Large Language Models (LLMs), with their remarkable zero-shot capabilities, are increasingly used in scientific domains. However, deploying large-scale models remains resource-intensive, and there is a growing demand for AI systems that can reason over both visual and textual data in astronomical analysis. This study explores small-scale Vision-Language Models (VLMs) as AI assistants for radio astronomy, combining LLM capabilities with vision transformers. We fine-tuned the LLaVA VLM on a dataset of 59k radio images from multiple surveys, enriched with 38k image-caption pairs from the literature. The fine-tuned models show clear improvements over base models in radio-specific tasks, achieving ~30% F1-score gains in extended source detection, but they underperform pure vision models and exhibit ~20% drop on general multimodal tasks. Inclusion of caption data and LoRA fine-tuning enhances instruction-following and helps recover ~10% accuracy on standard benchmarks. This work lays the foundation for future advancements in radio VLMs, highlighting their potential and limitations, such as the need for better multimodal alignment, higher-quality datasets, and mitigation of catastrophic forgetting.

The Stokes V parameter characterizes asymmetry of amplitudes between right- and left-handed waves, and non-vanishing value of the V parameter yields a circularly polarized signal. Cosmologically, V parameter may be a direct probe for parity violation in the universe. In this paper, we theoretically investigate a measurement of this parameter, particularly focusing on the gravitational-wave backgrounds observed via ground-based interferometers. In contrast to the traditional analysis that only considers the total amplitude (or equivalently Omega_{GW}), the signal analysis including a circular-polarized mode has a rich structure due to the multi-dimensionality of target parameters. We show that, by using the network of next-generation detectors, separation between polarized and unpolarized modes can be performed with small statistical loss induced by their correlation.

Forthcoming space-based gravitational-wave (GW) detectors will employ second-generation time-delay interferometry (TDI) to suppress laser frequency noise and achieve the sensitivity required for GW detection. We introduce an inverse light-path operator P_{i_{1}i_{2}i_{3}ldots i_{n-1}i_{n}}, which enables simple representation of second-generation TDI combinations and a concise description of light propagation. Analytical expressions and high-accuracy approximate formulas are derived for the sky- and polarization-averaged response functions, noise power spectral densities (PSDs), and sensitivity curves of TDI Michelson, (alpha,beta,gamma), Monitor, Beacon, Relay, and Sagnac combinations, as well as their orthogonal A, E, T channels. Our results show that: (i) second-generation TDIs have the same sensitivities as their first-generation counterparts; (ii) the A, E, T sensitivities and the optimal sensitivity are independent of the TDI generation and specific combination; (iii) the A and E channels have equal averaged responses, noise PSDs, and sensitivities, while the T channel has much weaker response and sensitivity at low frequencies (2pi fL/clesssim3); (iv) except for the (alpha,beta,gamma) and zeta combinations and the T channel, all sensitivity curves exhibit a flat section in the range f_{n}<flesssim 1.5/(2pi L/c), where the noise-balance frequency f_{n} separates the proof-mass- and optical-path-dominated regimes, while the response-transition frequency sim 1.5/(2pi L/c) separates the response function's low- and high-frequency behaviors; (v) the averaged response, noise PSD, and sensitivity of zeta scales with those of the T channel. These analytical and approximate formulations provide useful benchmarks for instrument optimization and data-analysis studies for future space-based GW detectors.

Radio interferometric imaging aims to estimate an unknown sky intensity image from degraded observations, acquired through an antenna array. In the theoretical case of a perfectly calibrated array, it has been shown that solving the corresponding imaging problem by iterative algorithms based on convex optimization and compressive sensing theory can be competitive with classical algorithms such as CLEAN. However, in practice, antenna-based gains are unknown and have to be calibrated. Future radio telescopes, such as the SKA, aim at improving imaging resolution and sensitivity by orders of magnitude. At this precision level, the direction-dependency of the gains must be accounted for, and radio interferometric imaging can be understood as a blind deconvolution problem. In this context, the underlying minimization problem is non-convex, and adapted techniques have to be designed. In this work, leveraging recent developments in non-convex optimization, we propose the first joint calibration and imaging method in radio interferometry, with proven convergence guarantees. Our approach, based on a block-coordinate forward-backward algorithm, jointly accounts for visibilities and suitable priors on both the image and the direction-dependent effects (DDEs). As demonstrated in recent works, sparsity remains the prior of choice for the image, while DDEs are modelled as smooth functions of the sky, i.e. spatially band-limited. Finally, we show through simulations the efficiency of our method, for the reconstruction of both images of point sources and complex extended sources. MATLAB code is available on GitHub.

A stochastic gravitational wave background causes the apparent positions of distant sources to fluctuate, with angular deflections of order the characteristic strain amplitude of the gravitational waves. These fluctuations may be detectable with high precision astrometry, as first suggested by Braginsky et al. in 1990. Several researchers have made order of magnitude estimates of the upper limits obtainable on the gravitational wave spectrum \Omega_gw(f), at frequencies of order f ~ 1 yr^-1, both for the future space-based optical interferometry missions GAIA and SIM, and for VLBI interferometry in radio wavelengths with the SKA. For GAIA, tracking N ~ 10^6 quasars over a time of T ~ 1 yr with an angular accuracy of \Delta \theta ~ 10 \mu as would yield a sensitivity level of \Omega_gw ~ (\Delta \theta)^2/(N T^2 H_0^2) ~ 10^-6, which would be comparable with pulsar timing. In this paper we take a first step toward firming up these estimates by computing in detail the statistical properties of the angular deflections caused by a stochastic background. We compute analytically the two point correlation function of the deflections on the sphere, and the spectrum as a function of frequency and angular scale. The fluctuations are concentrated at low frequencies (for a scale invariant stochastic background), and at large angular scales, starting with the quadrupole. The magnetic-type and electric-type pieces of the fluctuations have equal amounts of power.

The Gamma-ray detection from an astrophysical object indicates the presence of an extreme environment where high-energy radiation is produced. With the continuous monitoring of the Gamma-ray sky by the Fermi Large Area Telescope (LAT), leading to deeper sensitivity, the high-energy Gamma-ray emission has now been detected from a diverse class of jetted active galactic nuclei (AGN). Here, we present the results of a multiwavelength study of the radio source DA~362, which was reported to be a blazar candidate of uncertain type. However, it was recently identified as a bona fide compact symmetric object (CSO) based on its sub-kpc, bi-polar radio morphology, and lack of radio variability. This makes DA~362 the only fourth Gamma-ray emitting object of this enigmatic class of radio-loud AGN. Using five very long baseline interferometry observations covering 1996-2018, we found the jet separation velocity to be subluminal (v_{rm app}sim 0.2c), thus supporting its CSO nature. Its Fermi-LAT observations revealed a Gamma-ray flaring activity, a phenomenon never detected from the other three Gamma-ray detected CSOs. This object is bright in the near-infrared band but extremely faint in the optical-ultraviolet filters, hinting at possible obscuration. The Swift X-Ray Telescope observation of DA 362 reveals an extremely hard X-ray spectrum, though a strong claim cannot be made due to large uncertainties. We conclude that deeper observations are needed to probe the broadband properties of this enigmatic object and to understand the origin of high-energy Gamma-ray emission.

We extend our previous work on applying CMB techniques to the mapping of gravitational-wave backgrounds to backgrounds which have non-GR polarisations. Our analysis and results are presented in the context of pulsar-timing array observations, but the overarching methods are general, and can be easily applied to LIGO or eLISA observations using appropriately modified response functions. Analytic expressions for the pulsar-timing response to gravitational waves with non-GR polarisation are given for each mode of a spin-weighted spherical-harmonic decomposition of the background, which permit the signal to be mapped across the sky to any desired resolution. We also derive the pulsar-timing overlap reduction functions for the various non-GR polarisations, finding analytic forms for anisotropic backgrounds with scalar-transverse ("breathing") and vector-longitudinal polarisations, and a semi-analytic form for scalar-longitudinal backgrounds. Our results indicate that pulsar-timing observations will be completely insensitive to scalar-transverse mode anisotropies in the polarisation amplitude beyond dipole, and anisotropies in the power beyond quadrupole. Analogously to our previous findings that pulsar-timing observations lack sensitivity to tensor-curl modes for a transverse-traceless tensor background, we also find insensitivity to vector-curl modes for a vector-longitudinal background.

In our previous paper, we developed a technique for identifying pulsar candidates in interferometric radio images using their distinctive scintillation signatures. Building on this technique, the present study simulates a pulsar population using the PsrPopPy Python module to investigate the technique's limitations and detection capabilities. Among pulsars detectable exclusively by this technique, 50% have duty cycles exceeding the mean value of 0.09 observed in time-domain detections. Our pulsar population simulations revealed a set of observational parameters that optimize pulsar detection. An observation frequency of ~ 1420 MHz and a channel width of ~10 kHz emerge as the optimal configuration to maximize the pulsar detection efficiency. By applying a scintillation-based technique to future radio telescopes like DSA-2000, we can detect 56% of normal pulsars and 84% of MSPs in addition to those detected using non-imaging, time-domain surveys. These detected pulsars cannot be verified by time-domain searches.

We present new time delays, the main ingredient of time delay cosmography, for 22 lensed quasars resulting from high-cadence r-band monitoring on the 2.6 m ESO VLT Survey Telescope and Max-Planck-Gesellschaft 2.2 m telescope. Each lensed quasar was typically monitored for one to four seasons, often shared between the two telescopes to mitigate the interruptions forced by the COVID-19 pandemic. The sample of targets consists of 19 quadruply and 3 doubly imaged quasars, which received a total of 1 918 hours of on-sky time split into 21 581 wide-field frames, each 320 seconds long. In a given field, the 5-{\sigma} depth of the combined exposures typically reaches the 27th magnitude, while that of single visits is 24.5 mag - similar to the expected depth of the upcoming Vera-Rubin LSST. The fluxes of the different lensed images of the targets were reliably de-blended, providing not only light curves with photometric precision down to the photon noise limit, but also high-resolution models of the targets whose features and astrometry were systematically confirmed in Hubble Space Telescope imaging. This was made possible thanks to a new photometric pipeline, lightcurver, and the forward modelling method STARRED. Finally, the time delays between pairs of curves and their uncertainties were estimated, taking into account the degeneracy due to microlensing, and for the first time the full covariance matrices of the delay pairs are provided. Of note, this survey, with 13 square degrees, has applications beyond that of time delays, such as the study of the structure function of the multiple high-redshift quasars present in the footprint at a new high in terms of both depth and frequency. The reduced images will be available through the European Southern Observatory Science Portal.

We report long baseline interferometric observations with the CHARA Array that resolve six previously known double-lined spectroscopic binary systems in the Hyades cluster, with orbital periods ranging from 3 to 358 days: HD 27483, HD 283882, HD 26874, HD 27149, HD 30676, and HD 28545. We combine those observations with new and existing radial-velocity measurements, to infer the dynamical masses for the components as well as the orbital parallaxes. For most stars the masses are determined to better than 1%. Our work significantly increases the number of systems with mass determinations in the cluster. We find that while current models of stellar evolution for the age and metallicity of the Hyades are able to reproduce the overall shape of the empirical mass-luminosity relation, they overestimate the V-band fluxes by about 0.1 mag between 0.5 and 1.4 M_{odot}. The disagreement is smaller in H, and near zero in K, and depends somewhat on the model. We also make use of the TESS light curves to estimate rotation periods for our targets, and detect numerous flares in one of them (HD 283882), estimating an average flaring rate of 0.44 events per day.

The Laser Interferometer Space Antenna (LISA) will be the first space-based gravitational wave (GW) observatory. It will measure gravitational wave signals in the frequency regime from 0.1 mHz to 1 Hz. The success of these measurements will depend on the suppression of the various instrument noises. One important noise source in LISA will be tilt-to-length (TTL) coupling. Here, it is understood as the coupling of angular jitter, predominantly from the spacecraft, into the interferometric length readout. The current plan is to subtract this noise in-flight in post-processing as part of a noise minimization strategy. It is crucial to distinguish TTL coupling well from the GW signals in the same readout to ensure that the noise will be properly modeled. Furthermore, it is important that the subtraction of TTL noise will not degrade the GW signals. In the present manuscript, we show on simulated LISA data and for four different GW signal types that the GW responses have little effect on the quality of the TTL coupling fit and subtraction. Also, the GW signal characteristics were not altered by the TTL coupling subtraction.

The coupling of the angular jitter of the spacecraft and their sub-assemblies with the optical bench and the telescope into the interferometric length readout will be a major noise source in the LISA mission. We refer to this noise as tilt-to-length (TTL) coupling. It will be reduced directly by realignments, and the residual noise will then be subtracted in post-processing. The success of these mitigation strategies depends on an accurate computation of the TTL coupling coefficients. We present here a thorough analysis of the accuracy of the coefficient estimation under different jitter characteristics, angular readout noise levels, and gravitational wave sources. We analyze in which cases the estimates degrade using two estimators, the common least squares estimator and the instrumental variables estimator. Our investigations show that angular readout noise leads to a bias of the least squares estimator, depending on the TTL coupling coefficients, jitter and readout noise level, while the instrumental variable estimator is not biased. We present an equation that predicts the estimation bias of the least squares method due to angular readout noise.

Gravitational waves from asymmetric mass-ratio black-hole binaries carry unique information about their astrophysical environment. For instance, the Laser Interferometer Space Antenna (LISA) could potentially measure the amplitude and slope of gas torques in binaries embedded in the accretion disks of Active Galactic Nuclei, helping differentiate competing accretion disk models. However, this relies on simplified analytic models, which do not account for the stochastic variability of torques seen in hydrodynamic simulations. In this work, we use hydrodynamic simulations to create gravitational waveforms for extreme and intermediate mass-ratio inspirals in the LISA band. We then analyze these simulated waveforms using simpler templates that assume analytic torques, without stochastic time variability. By performing realistic Bayesian parameter estimation, we find no bias at 90% confidence in the binary parameters; however, estimates of accretion disk parameters, such as torque amplitude and slope, may be biased. Typically, the posterior distribution is centered around the average value of the torques, but when stochastic variability is large, the posterior can indicate no torques, even though they are present in the simulation. Our results suggest that while simplified analytic torque models work well for estimating binary parameters, caution is needed when using them to infer properties of the accretion disk. This work moves towards a more realistic assessment of one of the LISA science objectives, i.e., probing the properties of the astrophysical environments of black holes.

The inspiral, merger, and ringdown of Massive Black Hole Binaries (MBHBs) is one the main sources of Gravitational Waves (GWs) for the future Laser Interferometer Space Antenna (LISA), an ESA-led mission in the implementation phase. It is expected that LISA will detect these systems throughout the entire observable universe. Robust and efficient data analysis algorithms are necessary to detect and estimate physical parameters for these systems. In this work, we explore the application of Sequential Neural Likelihood, a simulation-based inference algorithm, to detect and characterize MBHB GW signals in synthetic LISA data. We describe in detail the different elements of the method, their performance and possible alternatives that can be used to enhance the performance. Instead of sampling from the conventional likelihood function, which requires a forward simulation for each evaluation, this method constructs a surrogate likelihood that is ultimately described by a neural network trained from a dataset of simulations of the MBHB signals and noise. One important advantage of this method is that, given that the likelihood is independent of the priors, we can iteratively train models that target specific observations in a fraction of the time and computational cost that other traditional and machine learning-based strategies would require. Because of the iterative nature of the method, we are able to train models to obtain qualitatively similar posteriors with less than 2\% of the simulator calls that Markov Chain Monte Carlo methods would require. We compare these posteriors with those obtained from Markov Chain Monte Carlo techniques and discuss the differences that appear, in particular in relation with the important role that data compression has in the modular implementation of the method that we present. We also discuss different strategies to improve the performance of the algorithms.

This paper describes the 2018 Planck CMB likelihoods, following a hybrid approach similar to the 2015 one, with different approximations at low and high multipoles, and implementing several methodological and analysis refinements. With more realistic simulations, and better correction and modelling of systematics, we can now make full use of the High Frequency Instrument polarization data. The low-multipole 100x143 GHz EE cross-spectrum constrains the reionization optical-depth parameter tau to better than 15% (in combination with with the other low- and high-ell likelihoods). We also update the 2015 baseline low-ell joint TEB likelihood based on the Low Frequency Instrument data, which provides a weaker tau constraint. At high multipoles, a better model of the temperature-to-polarization leakage and corrections for the effective calibrations of the polarization channels (polarization efficiency or PE) allow us to fully use the polarization spectra, improving the constraints on the LambdaCDM parameters by 20 to 30% compared to TT-only constraints. Tests on the modelling of the polarization demonstrate good consistency, with some residual modelling uncertainties, the accuracy of the PE modelling being the main limitation. Using our various tests, simulations, and comparison between different high-ell implementations, we estimate the consistency of the results to be better than the 0.5sigma level. Minor curiosities already present before (differences between ell<800 and ell>800 parameters or the preference for more smoothing of the C_ell peaks) are shown to be driven by the TT power spectrum and are not significantly modified by the inclusion of polarization. Overall, the legacy Planck CMB likelihoods provide a robust tool for constraining the cosmological model and represent a reference for future CMB observations. (Abridged)

The statistical power of weak lensing measurements is principally driven by the number of high redshift galaxies whose shapes are resolved. Conventional wisdom and physical intuition suggest this is optimised by deep imaging at long (red or near IR) wavelengths, to avoid losing redshifted Balmer break and Lyman break galaxies. We use the synthetic Emission Line EL-COSMOS catalogue to simulate lensing observations using different filters, from various altitudes. Here were predict the number of exposures to achieve a target z > 0.3 source density, using off-the-shelf and custom filters. Ground-based observations are easily better at red wavelengths, as (more narrowly) are space-based observations. However, we find that SuperBIT, a diffraction-limited observatory operating in the stratosphere, should instead perform its lensing-quality observations at blue wavelengths.

We show that pairs of widely separated interferometers are advantageous for measuring the Stokes parameter V of a stochastic background of gravitational waves. This parameter characterizes asymmetry of amplitudes of right- and left-handed waves and generation of the asymmetry is closely related to parity violation in the early universe. The advantageous pairs include LIGO(Livingston)-LCGT and AIGO-Virgo that are relatively insensitive to Omega_GW (the simple intensity of the background). Using at least three detectors, information of the intensity Omega_GW and the degree of asymmetry V can be separately measured.

We present a systematic reassessment of 5,062 high-Galactic latitude gamma-ray sources from the Fermi-LAT 4FGL-DR4 catalog using Firmamento, a web-based platform for multi-frequency source discovery and analysis. Our goal is to provide an independent evaluation of LAT gamma-ray source associations through alternative spectral and spatial methods that combine recent and legacy survey data, supplemented by human supervision of spectral energy distributions (SEDs), source morphology, flux variability, and template-based comparisons. Firmamento confirms the 4FGL-DR4 and 4LAC-DR3 counterparts or unassociated sources in 4,493 cases (88.8%), demonstrating the robustness of both approaches. Beyond this general agreement, we identify 421 new blazar counterparts among previously unassociated sources, thereby reducing the fraction of unidentified extragalactic Fermi-LAT sources from 25% to 17%. In addition, in 64 cases we find alternative blazar associations, while in 49 instances we do not confirm the 4FGL-DR4 association. For all confirmed blazar counterparts we provide homogeneous estimates of synchrotron peak frequency and peak flux using machine-learning and template-based methods; these agree with 4LAC-DR3 values in most cases, though significant discrepancies appear for a few dozen sources, often due to improved X-ray coverage. The primary outcome of this work is the 1st Firmamento LAT AGN table (1FLAT), made publicly available through the Firmamento platform (https://firmamento.nyuad.nyu.edu), where all related multi-wavelength data and images are available. The project involved extensive manual validation and benefited from the active participation of graduate and undergraduate students, highlighting the platform's value for both research and education.

We present a new approach to constructing and fitting dipoles and higher-order multipoles in synthetic galaxy samples over the sky. Within our Bayesian paradigm, we illustrate that this technique is robust to masked skies, allowing us to make credible inferences about the relative contributions of each multipole. We also show that dipoles can be recovered in surveys with small footprints, determining the requisite source counts required for concrete estimation of the dipole parameters. This work is motivated by recent probes of the cosmic dipole in galaxy catalogues. Namely, the kinematic dipole of the Cosmic Microwave Background, as arising from the motion of our heliocentric frame at approx 370 km,s^{-1}, implies that an analogous dipole should be observed in the number counts of galaxies in flux-density-limited samples. Recent studies have reported a dipole aligning with the kinematic dipole but with an anomalously large amplitude. Accordingly, our new technique will be important as forthcoming galaxy surveys are made available and for revisiting previous data.

A low frequency stochastic background of gravitational waves may be detected by pulsar timing experiments in the next five to ten years. Using methods developed to analyze interferometric gravitational wave data, in this paper we lay out the optimal techniques to detect a background of gravitational waves using a pulsar timing array. We show that for pulsar distances and gravitational wave frequencies typical of pulsar timing experiments, neglecting the effect of the metric perturbation at the pulsar does not result in a significant deviation from optimality. We discuss methods for setting upper limits using the optimal statistic, show how to construct skymaps using the pulsar timing array, and consider several issues associated with realistic analysis of pulsar timing data.

A sample of 60,410 bona fide optical quasars with astrometric proper motions in Gaia EDR3 and spectroscopic redshifts above 0.5 in an oval 8400 square degree area of the sky is constructed. Using orthogonal Zernike functions of polar coordinates, the proper motion fields are fitted in a weighted least-squares adjustment of the entire sample and of six equal bins of sorted redshifts. The overall fit with 37 Zernike functions reveals a statistically significant pattern, which is likely to be of instrumental origin. The main feature of this pattern is a chain of peaks and dips mostly in the R.A. component with an amplitude of 25~muas yr^{-1}. This field is subtracted from each of the six analogous fits for quasars grouped by redshifts covering the range 0.5 through 7.03, with median values 0.72, 1.00, 1.25, 1.52, 1.83, 2.34. The resulting residual patterns are noisier, with formal uncertainties up to 8~muas yr^{-1} in the central part of the area. We detect a single high-confidence Zernike term for R.A. proper motion components of quasars with redshifts around 1.52 representing a general gradient of 30 muas yr^{-1} over 150degr on the sky. We do not find any small- or medium-scale systemic variations of the residual proper motion field as functions of redshift above the 2.5,sigma significance level.

Next-generation telescopes will bring groundbreaking discoveries but they will also present new technological challenges. The Square Kilometre Array Observatory (SKAO) will be one of the most demanding scientific infrastructures, with a projected data output of 700 PB per year to be distributed to a network of SKA Regional Centres. Current tools are not fully suited to manage such massive data volumes, therefore, new research is required to transform science archives from data providers into service providers. In this paper we examine how a science archive can deliver advanced visualisation capabilities for the SKA science archive. In particular, we have conducted a thorough exploration of existing visualisation software for astronomy and other fields to identify tools capable of addressing Big Data requirements. Using selected technologies, we have developed a prototype archive that provides access to interactive visualisations of 3D radio data through web-based interfaces, adhering to International Virtual Observatory Alliance (IVOA) recommendations to favour interoperability and Open Science practices. In addition, we discuss how current IVOA recommendations support these visualisation capabilities and how they could be expanded. Our prototype archive includes a service to generate 3D models on the fly as a server operation, enabling remote visualisations in a flexible manner; for instance, a set of parameters can be used to customise the models and their visualisation. We have used SKA precursor and pathfinder data to test its usability and scalability, concluding that remote visualisation is a viable solution for handling high-volume data. However, our prototype is constrained by memory limitations, requiring techniques to reduce memory usage.

Detecting a stochastic gravitational wave background, particularly radiation from individually unresolvable super-massive black hole binary systems, is one of the primary targets for Pulsar Timing Arrays. Increasingly more stringent upper limits are being set on these signals under the assumption that the background radiation is isotropic. However, some level of anisotropy may be present and the characterisation of the power at different angular scales carries important information. We show that the standard analysis for isotropic backgrounds can be generalised in a conceptually straightforward way to the case of generic anisotropic background radiation by decomposing the angular distribution of the gravitational wave power on the sky into multipole moments. We introduce the concept of generalised overlap reduction functions which characterise the effect of the anisotropy multipoles on the correlation of the timing residuals from the pulsars timed by a Pulsar Timing Array. In a search for a signal characterised by a generic anisotropy, the generalised overlap reduction functions play the role of the so-called Hellings and Downs curve used for isotropic radiation. We compute the generalised overlap reduction functions for a generic level of anisotropy and Pulsar Timing Array configuration. We also provide an order of magnitude estimate of the level of anisotropy that can be expected in the background generated by super-massive black hole binary systems.

Low Earth orbit (LEO) satellite constellations bring broadband internet and cellular service to the most remote locations on the planet. Unfortunately, many of these locations also host some of the world's best optical and radio astronomy (RA) observatories. With the number of LEO satellites expected to increase by an order of magnitude in the upcoming decade, satellite downlink radio frequency interference (RFI) is a growing concern in protected radio-quiet areas like the United States National Radio Quiet Zone. When these satellites transmit in the spectrum near protected RA bands, undesired out-of-band emission can leak into these protected bands and impact scientific observations. In this paper, we present a self-reporting system - Operational Data Sharing (ODS) - which enables mutual awareness by publishing radio telescopes' operational information to a protected database that is available to satellite operators through a representational state transfer application programming interface (REST API). Satellite operators can use the ODS data to adapt their downlink tasking algorithms in real time to avoid overwhelming sensitive RA facilities, particularly, through the novel Telescope Boresight Avoidance (TBA) technique. Preliminary results from recent experiments between the NRAO and the SpaceX Starlink teams demonstrate the effectiveness of the ODS and TBA in reducing downlink RFI in the Karl G. Jansky Very Large Array's observations in the 1990-1995 MHz and 10.7-12.7 GHz bands. This automated ODS system is beginning to be implemented by other RA facilities and could be utilized by other satellite operators in the near future.

In this letter, we report the discovery of the highest redshift, heavily obscured, radio-loud QSO candidate selected using JWST NIRCam/MIRI, mid-IR, sub-mm, and radio imaging in the COSMOS-Web field. Using multi-frequency radio observations and mid-IR photometry, we identify a powerful, radio-loud (RL), growing supermassive black hole (SMBH) with significant spectral steepening of the radio SED (f_{1.32 GHz} sim 2 mJy, q_{24mu m} = -1.1, alpha_{1.32-3GHz}=-1.2, Delta alpha = -0.4). In conjunction with ALMA, deep ground-based observations, ancillary space-based data, and the unprecedented resolution and sensitivity of JWST, we find no evidence of QSO contribution to the UV/optical/NIR data and thus infer heavy amounts of obscuration (N_{H} > 10^{23} cm^{-2}). Using the wealth of deep UV to sub-mm photometric data, we report a singular solution photo-z of z_phot = 7.65^{+0.4}_{-0.3} and estimate an extremely massive host-galaxy (log M_{star} = 11.92 pm 0.06,M_{odot}). This source represents the furthest known obscured RL QSO candidate, and its level of obscuration aligns with the most representative but observationally scarce population of QSOs at these epochs.

We present starkiller, an open-source Python package for forward-modeling flux retrieval from integral field unit spectrograph (IFU) datacubes. Starkiller simultaneously provides stellar spectral classification, relative velocity, and line-of-sight extinction for all sources in a catalog, alongside a source-subtracted datacube. It performs synthetic difference imaging by simulating all catalog sources in the field of view, using the catalog for positions and fluxes to scale stellar models, independent of the datacube. This differencing method is particularly powerful for subtracting both point-sources and trailed or even streaked sources from extended astronomical objects. We demonstrate starkiller's effectiveness in improving observations of extended sources in dense stellar fields for VLT/MUSE observations of comets, asteroids and nebulae. We also show that starkiller can treat satellite-impacted VLT/MUSE observations. The package could be applied to tasks as varied as dust extinction in clusters and stellar variability; the stellar modeling using Gaia fluxes is provided as a standalone function. The techniques can be expanded to imagers and to other IFUs.

The pattern of individual mode frequencies in solar-like oscillators provides valuable insight into their properties and interior structures. The identification and characterisation of these modes requires high signal-to-noise and frequency resolution. The KEYSTONE project unlocks the asteroseismic potential of the K2 mission by providing individually reduced, high-quality time series data, global asteroseismic parameters, and spectroscopic analysis for 173 solar-like oscillators. In this work, we build on the KEYSTONE project and present the first analysis of the pattern of individual modes in the oscillation spectra for the K2 KEYSTONE stars. We perform a robust identification and characterisation of the modes through peakbagging methods in the open-source analysis tool PBjam. We present over 6000 mode frequencies, widths, and heights for 168 stars in the sample, covering the HR diagram from FGK dwarfs to sub-giants and the lower red giant branch, providing a significant increase in the number of individual mode frequency detections for main sequence and sub-giant oscillators. This study also presents sample-wide trends of oscillation patterns as a function of the fundamental stellar properties, and improves the precision of the global asteroseismic parameters. These measurements are part of the legacy of the K2 mission, and can be used to perform detailed modelling to improve the precision of fundamental properties of these stars. The results of this analysis provides evidence for the validity of using PBjam to identify and characterise the modes resulting from the observations of the future PLATO mission.

The Superpressure Balloon-borne Imaging Telescope (SuperBIT) is a diffraction-limited, wide-field, 0.5 m, near-infrared to near-ultraviolet observatory designed to exploit the stratosphere's space-like conditions. SuperBIT's 2023 science flight will deliver deep, blue imaging of galaxy clusters for gravitational lensing analysis. In preparation, we have developed a weak lensing measurement pipeline with modern algorithms for PSF characterization, shape measurement, and shear calibration. We validate our pipeline and forecast SuperBIT survey properties with simulated galaxy cluster observations in SuperBIT's near-UV and blue bandpasses. We predict imaging depth, galaxy number (source) density, and redshift distribution for observations in SuperBIT's three bluest filters; the effect of lensing sample selections is also considered. We find that in three hours of on-sky integration, SuperBIT can attain a depth of b = 26 mag and a total source density exceeding 40 galaxies per square arcminute. Even with the application of lensing-analysis catalog selections, we find b-band source densities between 25 and 30 galaxies per square arcminute with a median redshift of z = 1.1. Our analysis confirms SuperBIT's capability for weak gravitational lensing measurements in the blue.

Deep Learning (DL) has shown remarkable results in solving inverse problems in various domains. In particular, the Tikhonet approach is very powerful to deconvolve optical astronomical images (Sureau et al. 2020). Yet, this approach only uses the ell_2 loss, which does not guarantee the preservation of physical information (e.g. flux and shape) of the object reconstructed in the image. In Nammour et al. (2021), a new loss function was proposed in the framework of sparse deconvolution, which better preserves the shape of galaxies and reduces the pixel error. In this paper, we extend Tikhonet to take into account this shape constraint, and apply our new DL method, called ShapeNet, to optical and radio-interferometry simulated data set. The originality of the paper relies on i) the shape constraint we use in the neural network framework, ii) the application of deep learning to radio-interferometry image deconvolution for the first time, and iii) the generation of a simulated radio data set that we make available for the community. A range of examples illustrates the results.

This paper presents the specification, design, and development of the Visible Camera (VIS) on the ESA Euclid mission. VIS is a large optical-band imager with a field of view of 0.54 deg^2 sampled at 0.1" with an array of 609 Megapixels and spatial resolution of 0.18". It will be used to survey approximately 14,000 deg^2 of extragalactic sky to measure the distortion of galaxies in the redshift range z=0.1-1.5 resulting from weak gravitational lensing, one of the two principal cosmology probes of Euclid. With photometric redshifts, the distribution of dark matter can be mapped in three dimensions, and, from how this has changed with look-back time, the nature of dark energy and theories of gravity can be constrained. The entire VIS focal plane will be transmitted to provide the largest images of the Universe from space to date, reaching m_AB>24.5 with S/N >10 in a single broad I_E~(r+i+z) band over a six year survey. The particularly challenging aspects of the instrument are the control and calibration of observational biases, which lead to stringent performance requirements and calibration regimes. With its combination of spatial resolution, calibration knowledge, depth, and area covering most of the extra-Galactic sky, VIS will also provide a legacy data set for many other fields. This paper discusses the rationale behind the VIS concept and describes the instrument design and development before reporting the pre-launch performance derived from ground calibrations and brief results from the in-orbit commissioning. VIS should reach fainter than m_AB=25 with S/N>10 for galaxies of full-width half-maximum of 0.3" in a 1.3" diameter aperture over the Wide Survey, and m_AB>26.4 for a Deep Survey that will cover more than 50 deg^2. The paper also describes how VIS works with the other Euclid components of survey, telescope, and science data processing to extract the cosmological information.

We revisit the flat-sky approximation for evaluating the angular power spectra of projected random fields by retaining information about the correlations along the line of sight. With broad, overlapping radial window functions, these line-of-sight correlations are suppressed and are ignored in the Limber approximation. However, retaining the correlations is important for narrow window functions or unequal-time spectra but introduces significant computational difficulties due to the highly oscillatory nature of the integrands involved. We deal with the integral over line-of-sight wave-modes in the flat-sky approximation analytically, using the FFTlog expansion of the 3D power spectrum. This results in an efficient computational method, which is a substantial improvement compared to any full-sky approaches. We apply our results to galaxy clustering (with and without redshift-space distortions), CMB lensing and galaxy lensing observables. For clustering, we find excellent agreement with the full-sky results on large (percent-level agreement) and intermediate or small (subpercent agreement) scales, dramatically out-performing the Limber approximation for both wide and narrow window functions, and in equal- and unequal-time cases. In the case of lensing, we show on the full sky that the angular power spectrum of the convergence can be very well approximated by projecting the 3D Laplacian (rather than the correct angular Laplacian) of the gravitational potential, even on large scales. Combining this approximation with our flat-sky techniques provides an efficient and accurate evaluation of the CMB lensing angular power spectrum on all scales.

Aims: The aim of the present study is to explore how to disentangle energy-dependent time delays due to a possible Lorentz invariance violation (LIV) at Planck scale from intrinsic delays expected in standard blazar flares. Methods: We first characterise intrinsic time delays in BL Lacs and Flat Spectrum Radio Quasars in standard one-zone time-dependent synchrotron self-Compton or external Compton models, during flares produced by particle acceleration and cooling processes. We simulate families of flares with both intrinsic and external LIV-induced energy-dependent delays. Discrimination between intrinsic and LIV delays is then investigated in two different ways. A technique based on Euclidean distance calculation between delays obtained in the synchrotron and in the inverse-Compton spectral bumps is used to assess their degree of correlation. A complementary study is performed using spectral hardness versus intensity diagrams in both energy ranges. Results: We show that the presence of non-negligible LIV effects, which essentially act only at very high energies (VHE), can drastically reduce the strong correlation expected between the X-ray and the VHE gamma-ray emission in leptonic scenarios. The LIV phenomenon can then be hinted at measuring the Euclidean distance d_{E} from simultaneous X-ray and gamma-ray flare monitoring. Large values of minimal distance d_{E,min} would directly indicate the influence of non-intrinsic time delays possibly due to LIV in SSC flares. LIV effects can also significantly modify the VHE hysteresis patterns in hardness-intensity diagrams and even change their direction of rotation as compared to the X-ray behaviour. Both observables could be used to discriminate between LIV and intrinsic delays, provided high quality flare observations are available.

General-purpose large language models, despite their broad capabilities, often struggle with specialized domain knowledge, a limitation particularly pronounced in more accessible, lower-parameter versions. This gap hinders their deployment as effective agents in demanding fields such as astronomy. Building on our prior work with AstroSage-8B, this study introduces AstroSage-70B, a significantly larger and more advanced domain-specialized natural-language AI assistant. It is designed for research and education across astronomy, astrophysics, space science, astroparticle physics, cosmology, and astronomical instrumentation. Developed from the Llama-3.1-70B foundation, AstroSage-70B underwent extensive continued pre-training on a vast corpus of astronomical literature, followed by supervised fine-tuning and model merging. Beyond its 70-billion parameter scale, this model incorporates refined datasets, judiciously chosen learning hyperparameters, and improved training procedures, achieving state-of-the-art performance on complex astronomical tasks. Notably, we integrated reasoning chains into the SFT dataset, enabling AstroSage-70B to either answer the user query immediately, or first emit a human-readable thought process. Evaluated on the AstroMLab-1 benchmark -- comprising 4,425 questions from literature withheld during training -- AstroSage-70B achieves state-of-the-art performance. It surpasses all other tested open-weight and proprietary models, including leading systems like o3, Gemini-2.5-Pro, Claude-3.7-Sonnet, Deepseek-R1, and Qwen-3-235B, even those with API costs two orders of magnitude higher. This work demonstrates that domain specialization, when applied to large-scale models, can enable them to outperform generalist counterparts in specialized knowledge areas like astronomy, thereby advancing the frontier of AI capabilities in the field.

We present a comprehensive evaluation of proprietary and open-weights large language models using the first astronomy-specific benchmarking dataset. This dataset comprises 4,425 multiple-choice questions curated from the Annual Review of Astronomy and Astrophysics, covering a broad range of astrophysical topics. Our analysis examines model performance across various astronomical subfields and assesses response calibration, crucial for potential deployment in research environments. Claude-3.5-Sonnet outperforms competitors by up to 4.6 percentage points, achieving 85.0% accuracy. For proprietary models, we observed a universal reduction in cost every 3-to-12 months to achieve similar score in this particular astronomy benchmark. Open-source models have rapidly improved, with LLaMA-3-70b (80.6%) and Qwen-2-72b (77.7%) now competing with some of the best proprietary models. We identify performance variations across topics, with non-English-focused models generally struggling more in exoplanet-related fields, stellar astrophysics, and instrumentation related questions. These challenges likely stem from less abundant training data, limited historical context, and rapid recent developments in these areas. This pattern is observed across both open-weights and proprietary models, with regional dependencies evident, highlighting the impact of training data diversity on model performance in specialized scientific domains. Top-performing models demonstrate well-calibrated confidence, with correlations above 0.9 between confidence and correctness, though they tend to be slightly underconfident. The development for fast, low-cost inference of open-weights models presents new opportunities for affordable deployment in astronomy. The rapid progress observed suggests that LLM-driven research in astronomy may become feasible in the near future.

A new golden age in astronomy is upon us, dominated by data. Large astronomical surveys are broadcasting unprecedented rates of information, demanding machine learning as a critical component in modern scientific pipelines to handle the deluge of data. The upcoming Legacy Survey of Space and Time (LSST) of the Vera C. Rubin Observatory will raise the big-data bar for time-domain astronomy, with an expected 10 million alerts per-night, and generating many petabytes of data over the lifetime of the survey. Fast and efficient classification algorithms that can operate in real-time, yet robustly and accurately, are needed for time-critical events where additional resources can be sought for follow-up analyses. In order to handle such data, state-of-the-art deep learning architectures coupled with tools that leverage modern hardware accelerators are essential. We showcase how the use of modern deep compression methods can achieve a 18times reduction in model size, whilst preserving classification performance. We also show that in addition to the deep compression techniques, careful choice of file formats can improve inference latency, and thereby throughput of alerts, on the order of 8times for local processing, and 5times in a live production setting. To test this in a live setting, we deploy this optimised version of the original time-series transformer, t2, into the community alert broking system of FINK on real Zwicky Transient Facility (ZTF) alert data, and compare throughput performance with other science modules that exist in FINK. The results shown herein emphasise the time-series transformer's suitability for real-time classification at LSST scale, and beyond, and introduce deep model compression as a fundamental tool for improving deploy-ability and scalable inference of deep learning models for transient classification.

Extreme mass-ratio inspirals (EMRIs) are one of the key sources of gravitational waves for space-based detectors such as LISA. However, their detection remains a major data analysis challenge due to the signals' complexity and length. We present a semi-coherent, time-frequency search strategy for detecting EMRI harmonics without relying on full waveform templates. We perform an injection and search campaign of single mildly-eccentric equatorial EMRIs in stationary Gaussian noise. The detection statistic is constructed solely from the EMRI frequency evolution, which is modeled phenomenologically using a Singular Value Decomposition basis. The pipeline and the detection statistic are implemented in time-frequency, enabling efficient searches over one year of data in approximately one hour on a single GPU. The search pipeline achieves 94% detection probability at SNR = 30 for a false-alarm probability of 10^{-2}, recovering the frequency evolution of the dominant harmonic to 1% relative error. By mapping the EMRI parameters consistent with the recovered frequency evolution, we show that the semi-coherent detection statistic enables a sub-percent precision estimation of the EMRI intrinsic parameters. These results establish a computationally efficient framework for constructing EMRI proposals for the LISA global fit.

We present new limits on an isotropic stochastic gravitational-wave background (GWB) using a six pulsar dataset spanning 18 yr of observations from the 2015 European Pulsar Timing Array data release. Performing a Bayesian analysis, we fit simultaneously for the intrinsic noise parameters for each pulsar, along with common correlated signals including clock, and Solar System ephemeris errors, obtaining a robust 95% upper limit on the dimensionless strain amplitude A of the background of A<3.0times 10^{-15} at a reference frequency of 1yr^{-1} and a spectral index of 13/3, corresponding to a background from inspiralling super-massive black hole binaries, constraining the GW energy density to Omega_gw(f)h^2 < 1.1times10^{-9} at 2.8 nHz. We also present limits on the correlated power spectrum at a series of discrete frequencies, and show that our sensitivity to a fiducial isotropic GWB is highest at a frequency of sim 5times10^{-9}~Hz. Finally we discuss the implications of our analysis for the astrophysics of supermassive black hole binaries, and present 95% upper limits on the string tension, Gmu/c^2, characterising a background produced by a cosmic string network for a set of possible scenarios, and for a stochastic relic GWB. For a Nambu-Goto field theory cosmic string network, we set a limit Gmu/c^2<1.3times10^{-7}, identical to that set by the {\it Planck} Collaboration, when combining {\it Planck} and high-ell Cosmic Microwave Background data from other experiments. For a stochastic relic background we set a limit of Omega^relic_gw(f)h^2<1.2 times10^{-9}, a factor of 9 improvement over the most stringent limits previously set by a pulsar timing array.

We performed variability analysis of the multiwavelength light curves for the flat-spectrum radio quasar PKS 0727-11. Using the generalized Lomb-Scargle periodogram, we identified a possible quasi-periodic oscillation (QPO) of sim 168.6 days (persisted for 6 cycles, with a significance of 3.8sigma) in the gamma-ray light curve during the flare period (MJD 54687-55738). It is the first time that periodic variations have been detected in this source, and further supported by other methods: weighted wavelet z-transform, phase dispersion minimization, REDFIT, autoregressive integrated moving average model, and structure function analysis. Cross-correlation analysis shows that there is a strong correlation between multi-band light variations, indicating that gamma-ray and radio flares may originate from the same disturbance, and the distance between the emission regions of gamma-ray and radio flares is calculated based on the time lag. We demonstrate that QPO arising from the non-ballistic helical jet motion driven by the orbital motion in a supermassive binary black hole is a plausible physical explanation. In this scenario, the estimated mass of the primary black hole is Msim3.66times10^8-5.79times10^{9}M_odot.

We study future observational constraints on cosmic string parameters from various types of next-generation experiments: direct detection of gravitational waves (GWs), pulsar timing array, and the cosmic microwave background (CMB). We consider both GW burst and stochastic GW background searches by ground- and space-based interferometers as well as GW background detection in pulsar timing experiments. We also consider cosmic string contributions to the CMB temperature and polarization anisotropies. These different types of observations offer independent probes of cosmic strings and may enable us to investigate cosmic string properties if the signature is detected. In this paper, we evaluate the power of future experiments to constrain cosmic string parameters, such as the string tension Gmu, the initial loop size alpha, and the reconnection probability p, by performing Fisher information matrix calculations. We find that combining the information from the different types of observations breaks parameter degeneracies and provides more stringent constraints on the parameters. We also find future space-borne interferometers independently provide a highly precise determination of the parameters.

We study lensing of gravitational waves by a black hole in the deep wave optics regime, i.e. when the wavelength is much larger than the black hole Schwarzschild radius. We apply it to triple systems, with a binary of stellar mass objects in the inspiraling phase orbiting around a central massive black hole. We describe the full polarisation structure of the wave and derive predictions for the polarisation modes of the scattered wave measured by the observer. We show that lensing in the wave optics regime is not helicity preserving, as opposed to lensing in the geometric optics regime. The amplitude of the total wave is modulated due to interference between the directly transmitted and lensed components. The relative amplitude of the modulation is fixed by the lensing geometry and can reach unity in the most favourable settings. This indicates that wave optics lensing is potentially detectable by LISA for sufficiently high SNR systems. Our findings show that in the wave optics regime it is necessary to go beyond the usual lensing description where the amplification factor is assumed to be the same for both helicity modes. While motivated by GW190521 and the AGN formation scenario, our results apply more broadly to stellar-mass binaries orbiting a third body described as a Schwarzschild black hole, with a period comparable to the GW observation time.

We present Hubble Space Telescope (HST) imaging of Pegasus V and Pisces VII, along with a re-analysis of the archival imaging of Pegasus W, and Jansky Very Large Array (VLA) neutral gas (HI) observations of all three. These three ultra-faint dwarfs (UFDs) are all within the Local Group in the approximate direction of M31. The VLA observations place stringent upper limits on their HI content, with all having M_HI < 10^4;M_odot. As the red giant branches of these UFDs are sparsely populated, we determined distances from the HST photometry of horizontal branch (HB) stars in comparison to a fiducial HB population (from M92), with all three falling in the range 0.7-1 Mpc. Using a new Python-based star formation history (SFH) fitting code (based on StarFISH), we derive SFHs of all three UFDs. As found previously, the best fit SFH for Pegasus W includes significant star formation well beyond the end of reionization, while the SFHs calculated for Pegasus V and Pisces VII are consistent with them having quenched shortly after reionization. These findings for the latter two objects indicate that, like those in the vicinity of the Milky Way, lower mass UFDs in the vicinity of M31 likely quenched at early times.

Time series data from observations of black hole ringdown gravitational waves are often analyzed in the time domain by using damped sinusoid models with acyclic boundary conditions. Data conditioning operations, including downsampling, filtering, and the choice of data segment duration, reduce the computational cost of such analyses and can improve numerical stability. Here we analyze simulated damped sinsuoid signals to illustrate how data conditioning operations, if not carefully applied, can undesirably alter the analysis' posterior distributions. We discuss how currently implemented downsampling and filtering methods, if applied too aggressively, can introduce systematic errors and skew tests of general relativity. These issues arise because current downsampling and filtering methods do not operate identically on the data and model. Alternative downsampling and filtering methods which identically operate on the data and model may be achievable, but we argue that the current operations can still be implemented safely. We also show that our preferred anti-alias filtering technique, which has an instantaneous frequency-domain response at its roll-off frequency, preserves the structure of posterior distributions better than other commonly used filters with transient frequency-domain responses. Lastly, we highlight that exceptionally long data segments may need to be analyzed in cases where thin lines in the noise power spectral density overlap with central signal frequencies. Our findings may be broadly applicable to any analysis of truncated time domain data with acyclic boundary conditions.

Super-resolution (SR) advances astronomical imaging by enabling cost-effective high-resolution capture, crucial for detecting faraway celestial objects and precise structural analysis. However, existing datasets for astronomical SR (ASR) exhibit three critical limitations: flux inconsistency, object-crop setting, and insufficient data diversity, significantly impeding ASR development. We propose STAR, a large-scale astronomical SR dataset containing 54,738 flux-consistent star field image pairs covering wide celestial regions. These pairs combine Hubble Space Telescope high-resolution observations with physically faithful low-resolution counterparts generated through a flux-preserving data generation pipeline, enabling systematic development of field-level ASR models. To further empower the ASR community, STAR provides a novel Flux Error (FE) to evaluate SR models in physical view. Leveraging this benchmark, we propose a Flux-Invariant Super Resolution (FISR) model that could accurately infer the flux-consistent high-resolution images from input photometry, suppressing several SR state-of-the-art methods by 24.84% on a novel designed flux consistency metric, showing the priority of our method for astrophysics. Extensive experiments demonstrate the effectiveness of our proposed method and the value of our dataset. Code and models are available at https://github.com/GuoCheng12/STAR.

The spectral smoothness properties of the low-frequency array of the Square Kilometer Array (SKA), namely SKA-Low, are an important issue for its scientific objectives to be attainable. A large array of 256 log-periodic dipole antennas, installed on top of a 42~m circular ground plane, will work as an SKA-Low station in the frequency range 50-350 MHz. In this article, the ground plane induced effects are examined in terms of antenna beam spectral characteristics, while different antenna placements are considered. Results are produced both at isolated antenna and at array level in the band 50-100 MHz, by employing an approximate method for the speeding-up of array simulations. We attempt to distinguish the ground plane effect from that of mutual coupling among antennas, which appears to be more severe at specific frequencies, using 2 figures of merit. The Discrete Fourier Transform (DFT) components of gain pattern ratios identify the fundamental spatial components of the ripple, while the Envelope Correlation Coefficient quantifies the penalty to considering an infinite ground plane.

Galactic double white dwarfs are predominant sources of gravitational waves in the millihertz frequencies accessible to space-borne gravitational wave detectors. With advances in multi-messenger astronomy, an increasing number of double white dwarf systems will be discovered through both electromagnetic and gravitational wave observations. In this paper, we simulated two populations of double white dwarfs originating from different star formation histories (hereafter referred to as Model 1 and Model 2) using the binary population synthesis method. We predicted the number of double white dwarfs in our Galaxy detectable by TianQin and Laser Interferometer Space Antenna (LISA) individually, as well as through their joint observation. In addition, we performed an analysis to evaluate the accuracy of the parameter estimation using the Fisher information matrix. Furthermore, we predicted the number of detached eclipsing double white dwarfs detectable by Gaia and the Vera C. Rubin Observatory (VRO). Our study found that over the nominal mission durations, TianQin, LISA, and their joint observation can detect at least five thousand and potentially several tens of thousands of double white dwarfs with signal-to-noise ratios greater than 7. Gaia and VRO are expected to detect at least several dozen and up to several hundred eclipsing double white dwarfs with orbital periods less than 30 hours. We also found that several dozen eclipsing double white dwarfs can be detected jointly through electromagnetic and gravitational wave observations.

Since their discovery, AGN light curves are known to be intrinsically variable. In the optical/UV band, this variability is consistent with correlated or red noise and is particularly well described by the damped random walk (DRW) model. In this work, we evaluate the feasibility of a new method for identifying spatially unresolved couples of AGN through a fully Bayesian time-domain analysis of the observed light curves (LCs). More specifically, we check whether observed LCs are better described by a single DRW, which we interpret as emitted by a single massive black hole (MBH), or a pair of independent DRWs, generated by a pair of MBHs. We test the method on mock LCs associated with a single MBH and pairs generated with different cadences and lengths of observational campaigns. We constrained the occurrence of false positives, that is, the percentage of single MBH LCs that show substantial evidence in favour of the unresolved MBH pair scenario, finding a fraction of 0.2% and 0.59% in the even and uneven sampling scenarios. We discuss how well the method recovers the model parameters, showing that about 51% and 7% of the simulated LCs have all the recovered parameters within 20% of their true values in our best scenario of evenly sampled LCs for the single MBH and MBH pair scenarios, respectively. We finally study the region of the parameter space in which the detection of an MBH pair is possible, finding that such objects can be correctly identified if the timescales of the process describing the noise are very different, with a ratio smaller than ~0.2, and the variability amplitudes are similar, with their ratio bigger than ~0.2. When limiting to such a region of the parameter space, the fraction of pairs with all the recovered parameters within 20% of the injected values increases up to about 14% and 8% for evenly and unevenly sampled LCs, respectively.

The data collected by the current network of gravitational-wave detectors are largely dominated by instrumental noise. Total variation methods based on L1-norm minimization have recently been proposed as a powerful technique for noise removal in gravitational-wave data. In particular, the regularized Rudin-Osher-Fatemi (rROF) model has proven effective to denoise signals embedded in either simulated Gaussian noise or actual detector noise. Importing the rROF model to existing search pipelines seems therefore worth considering. In this paper, we discuss the implementation of two variants of the rROF algorithm as two separate plug-ins of the coherent Wave Burst (cWB) pipeline designed to conduct searches of unmodelled gravitational-wave burst sources. The first approach is based on a single-step rROF method and the second one employs an iterative rROF procedure. Both approaches are calibrated using actual gravitational-wave events from the first three observing runs of the LIGO-Virgo-KAGRA collaboration, namely GW1501914, GW151226, GW170817, and GW190521, encompassing different types of compact binary coalescences. Our analysis shows that the iterative version of the rROF denoising algorithm implemented in the cWB pipeline effectively eliminates noise while preserving the waveform signals intact. Therefore, the combined approach yields higher signal-to-noise values than those computed by the cWB pipeline without the rROF denoising step. The incorporation of the iterative rROF algorithm in the cWB pipeline might hence impact the detectability capabilities of the pipeline along with the inference of source properties.

In the axion model, electromagnetic waves interacting with axions induce frequency-dependent time delays, determined by the axion mass and decay constant. These small delays are difficult to detect, making traditional methods ineffective. To address this, we computed time delays for various parameters and found a prominent dispersion signal when the wave frequency equals half the axion mass. Based on this, we developed a machine learning-based pipeline, achieving 95\% classification accuracy and demonstrating strong detection capability in low signal-to-noise data. Applying this to PSR J1933-6211, we found no axion-induced delays within current sensitivity limits. While existing constraints are limited by atomic clock resolution in radio telescopes, future advances in optical clocks and broader bandwidths will enable more extensive searches. In particular, combining high-precision optical clocks with next-generation radio telescopes, such as the Qitai Radio Telescope, could improve decay constant constraints by four orders of magnitude for axion masses in the 10^{-6} sim 10^{-4} eV range.

Fast X-ray transients (FXRTs) are short-lived X-ray outbursts with diverse progenitor scenarios, including compact object mergers, stellar core-collapses and tidal disruption events. The Einstein Probe (EP) has enabled the rapid discovery and follow-up of dozens of FXRTs, revealing that while some of them overlap with traditional gamma-ray bursts (GRBs), a larger fraction of FXRTs have no associated gamma-ray counterpart down to deep limits. The origin of these gamma-ray dark FXRTs and their connection to the diverse landscape of stellar explosions remains an open question, which can be tackled through the study of their multi-wavelength counterparts and environment. In this paper, we present long-term radio observations of the gamma-ray dark EP241021a, which exhibits sustained radio emission for over 100 days, placing it among the longest-lived radio afterglows. We detect signature of interstellar scintillation in early epochs, allowing us to constrain the angular size and Lorentz factor of the emitting region. Our observations point to an outflow that is at least mildly relativistic with Lorentz factor > 4. Afterglow modeling favors a moderately relativistic and collimated outflow interacting with a low-density interstellar medium. The derived beaming-corrected kinetic energy and low radiative efficiency are consistent with a standard relativistic explosion which did not produce bright gamma-rays. Alternatively, a highly-relativistic structured jet remains consistent with our observations if seen substantially off-axis. In the latter case, the initial X-ray flare detected by EP would be caused by the slower ejecta from the lateral wings intercepting our line of sight rather than by traditional prompt-emission mechanisms within the jet core.

Through gravitational lensing, galaxy clusters can magnify supernovae (SNe) and create multiple images of the same SN. This enables measurements of cosmological parameters, which will be increasingly important in light of upcoming telescopic surveys. We study the prospects of detecting strongly lensed SNe in cluster fields with the Nancy Grace Roman Space Telescope (Roman)'s High Latitude Time Domain Survey (HLTDS) and the Vera C. Rubin Observatory's Legacy Survey of Space and Time (LSST). We employed two approaches: one focusing on known multiply imaged galaxies behind clusters, along with the SN rates specific to those galaxies, and another based on the expected number of lensed SNe exploding in a given volume behind a galaxy cluster. We collected all the clusters in the literature that feature a well-constrained lens model and multiply imaged galaxies behind clusters with high-quality data for the lensed galaxies. This allowed us to determine the SN rate for each galaxy. We provide predictions for 46 clusters visible to the Vera C. Rubin Observatory, as well as for 9 observable by Roman's HLTDS, depending on whether the clusters fall within the survey's observing field. We predict that the number of multiply imaged SNe discovered by LSST in its first three years is 3.95 pm 0.89 from the first approach or 4.94 pm 1.02 from the second. For the HLTDS, the expected number of multiply imaged SNe ranges from 0.38 pm 0.15 to 5.2 pm 2.2, depending on the specific cluster observed, however, the fields to be targeted remain a matter of discussion. We conclude that LSST offers great prospects for detecting multiply imaged SNe. Our predictions are effectively lower limits, as we only considered the most massive and well-studied clusters. We provide a recommendation for HLTDS observing field selection, namely: either MACS J0553.4-3342 or Abell 1758a should be observed by the survey.

Deep wide spectral line surveys with the Square Kilometre Array (SKA) will expand the cosmic frontiers of neutral atomic hydrogen (HI) in galaxies. However, at cosmologically significant redshifts (z gtrsim 0.5), detections will typically be spatially unresolved and limited to the highest mass systems. Gravitational lensing could potentially alleviate these limitations, enabling lower mass systems to be studied at higher redshift and spatially resolved dynamical studies of some HI discs. Additionally, lensed HI systems would select foreground dark matter haloes using a different, more extended baryonic tracer compared to other lens surveys. This may result in a wider selected range of foreground dark matter halo properties, such as the concentration parameter. This paper uses the distortion of the observed HI mass function (HIMF) produced by strong gravitational lensing to find a flux density criterion for selecting lensed HI sources in future SKA-Mid spectral line surveys. This selection approach could yield lensed HI source densities in the range of sim 0.1--10 galaxies per square degree out to a redshift of z simeq 3 covered by SKA-MID Band 1. Although the sample sizes are modest, even with the proposed SKA-Mid surveys, the selection approach is straightforward and should have a 50% efficiency without any additional information, such as low-impact-factor or lower-redshift massive galaxies. The efficiency of selecting high-redshift, neutral-hydrogen-rich, lensed galaxies should then be greatly enhanced by using SKA-MID data in concert with the Vera C. Rubin Large Survey of Space and Time.

Vision-Language Models (VLMs), such as recent Qwen and Gemini models, are positioned as general-purpose AI systems capable of reasoning across domains. Yet their capabilities in scientific imaging, especially on unfamiliar and potentially previously unseen data distributions, remain poorly understood. In this work, we assess whether generic VLMs, presumed to lack exposure to astronomical corpora, can perform morphology-based classification of radio galaxies using the MiraBest FR-I/FR-II dataset. We explore prompting strategies using natural language and schematic diagrams, and, to the best of our knowledge, we are the first to introduce visual in-context examples within prompts in astronomy. Additionally, we evaluate lightweight supervised adaptation via LoRA fine-tuning. Our findings reveal three trends: (i) even prompt-based approaches can achieve good performance, suggesting that VLMs encode useful priors for unfamiliar scientific domains; (ii) however, outputs are highly unstable, i.e. varying sharply with superficial prompt changes such as layout, ordering, or decoding temperature, even when semantic content is held constant; and (iii) with just 15M trainable parameters and no astronomy-specific pretraining, fine-tuned Qwen-VL achieves near state-of-the-art performance (3% Error rate), rivaling domain-specific models. These results suggest that the apparent "reasoning" of VLMs often reflects prompt sensitivity rather than genuine inference, raising caution for their use in scientific domains. At the same time, with minimal adaptation, generic VLMs can rival specialized models, offering a promising but fragile tool for scientific discovery.

We have submitted to MAST the 1.5 version data release of the Hubble Legacy Fields (HLF) project covering a 25 x 25 arcmin area over the GOODS-S (ECDF-S) region from the HST archival program AR-13252. The release combines exposures from Hubble's two main cameras, the Advanced Camera for Surveys (ACS/WFC) and the Wide Field Camera 3 (WFC3/IR), taken over more than a decade between mid-2002 to the end of 2016. The HLF includes essentially all optical (ACS/WFC F435W, F606W, F775W, F814W and F850LP filters) and infrared (WFC3/ IR F098M, F105W, F125W, F140W and F160W filters) data taken by Hubble over the original CDF-S region including the GOODS-S, ERS, CANDELS and many other programs (31 in total). The data has been released at https://archive.stsci.edu/prepds/hlf/ as images with a common astrometric reference frame, with corresponding inverse variance weight maps. We provide one image per filter of WFC3/IR images at 60 mas per pixel resolution and two ACS/WFC images per filter, at both 30 and 60 mas per pixel. Since this comprehensive dataset combines data from 31 programs on the GOODS-S/CDF-S, the AR proposal identified the MAST products by the global name "Hubble Legacy Field", with this region being identified by "HLF-GOODS-S". This dataset complements that of the Frontier Fields program. The total incorporated in the HLF-GOODS-S is 5.8 Msec in 7211 exposures from 2442 orbits. This is ~70% of a HST full cycle!

Direct exo-Earth imaging is a key science goal for astronomy in the next decade. This ambitious task imposes a target contrast of ~10^-7 at wavelengths from I to J-band. In our prior study, we determined that polarization aberrations can limit the achievable contrast to 10^-5 to 10^-6 in the infrared. However, these results assumed a perfect coronagraph coupled to a telescope with an ideal coating on each of the mirrors. In this study we seek to understand the influence of polarization aberrations from segment-to-segment coating variations on coronagraphy and polarimetry. We use the Poke open-source polarization ray tracing package to compute the Jones pupil of each GSMT with spatially-varying coatings applied to the segments. The influence of the resultant polarization aberrations is simulated by propagating the Jones pupil through physical optics models of coronagraphs using HCIPy. After applying wavefront control from an ideal adaptive optics system, we determine that the segment-to-segment variations applied limit the performance of coronagraphy to a raw contrast of approximately 10^-8 in I-band, which is 2-3 orders of magnitude lower the target performance for high-contrast imaging systems on the ground. This is a negligible addition to the nominal polarization aberrations for ground-based systems. We further observe negligible degradation in polarimetric imaging of debris disks from segment-to-segment aberrations above and beyond the impact of nominal polarization aberration.

The repeating fast radio burst FRB20190520B is an anomaly of the FRB population thanks to its high dispersion measure (DM=1205,pc/cc) despite its low redshift of z_frb=0.241. This excess has been attributed to a large host contribution of DM_{host}approx 900,pc/cc, far larger than any other known FRB. In this paper, we describe spectroscopic observations of the FRB20190520B field obtained as part of the FLIMFLAM survey, which yielded 701 galaxy redshifts in the field. We find multiple foreground galaxy groups and clusters, for which we then estimated halo masses by comparing their richness with numerical simulations. We discover two separate M_{halo} >10^{14},M_odot galaxy clusters, at z=0.1867 and z=0.2170, respectively, that are directly intersected by the FRB sightline within their characteristic halo radius . Subtracting off their estimated DM contributions as well that of the diffuse intergalactic medium, we estimate a host contribution of DM_{host}=430^{+140}_{-220},pc/cc or DM_{host}=280^{+140}_{-170},pc/cc (observed frame) depending on whether we assume the halo gas extends to r_{200} or 2times r_{200}. This significantly smaller DM_{host} -- no longer the largest known value -- is now consistent with Halpha emission measures of the host galaxy without invoking unusually high gas temperatures. Combined with the observed FRB scattering timescale, we estimate the turbulent fluctuation and geometric amplification factor of the scattering layer to be F Gapprox4.5 - 11,(pc^2;km)^{-1/3}, suggesting most of the gas is close to the FRB host. This result illustrates the importance of incorporating foreground data for FRB analyses, both for understanding the nature of FRBs and to realize their potential as a cosmological probe.

We use the Wide Field Camera 3 (WFC3) on the Hubble Space Telescope (HST) to reduce the uncertainty in the local value of the Hubble constant (H_0) from 3.3% to 2.4%. Improvements come from new, near-infrared observations of Cepheid variables in 11 new hosts of recent SNe~Ia, more than doubling the sample of SNe~Ia having a Cepheid-calibrated distance for a total of 19; these leverage the magnitude-z relation based on 300 SNe~Ia at z<0.15. All 19 hosts and the megamaser system NGC4258 were observed with WFC3, thus nullifying cross-instrument zeropoint errors. Other improvements include a 33% reduction in the systematic uncertainty in the maser distance to NGC4258, more Cepheids and a more robust distance to the LMC from late-type DEBs, HST observations of Cepheids in M31, and new HST-based trigonometric parallaxes for Milky Way (MW) Cepheids. We consider four geometric distance calibrations of Cepheids: (i) megamasers in NGC4258, (ii) 8 DEBs in the LMC, (iii) 15 MW Cepheids with parallaxes, and (iv) 2 DEBs in M31. H_0 from each is 72.25+/-2.51, 72.04+/-2.67, 76.18+/-2.37, and 74.50+/-3.27 km/sec/Mpc, respectively. Our best estimate of 73.24+/-1.74 km/sec/Mpc combines the anchors NGC4258, MW, and LMC, and includes systematic errors for a final uncertainty of 2.4%. This value is 3.4 sigma higher than 66.93+/-0.62 km/sec/Mpc predicted by LambdaCDM with 3 neutrinos with mass 0.06 eV and the Planck data, but reduces to 2.1 sigma relative to the prediction of 69.3+/-0.7 km/sec/Mpc with the combination of WMAP+ACT+SPT+BAO, suggesting systematic uncertainties in CMB measurements may play a role in the tension. If we take the conflict between Planck and H_0 at face value, one plausible explanation could involve an additional source of dark radiation in the early Universe in the range of Delta N_eff=0.4-1. We anticipate significant improvements in H_0 from upcoming parallax measurements.

Extreme-mass-ratio inspirals (EMRIs) and intermediate-mass-ratio inspirals (IMRIs) are important gravitational wave (GW) sources for the Laser Interferometer Space Antenna (LISA). It has been recently suggested that EMRIs and IMRIs can both form in the accretion disk of an active galactic nucleus (AGN). Considering the likely encounter between a sBH and an IMBH during the migration in the AGN disk, Paper I showed that a gap-opening IMBH can drive a surrounding sBH to migrate synchronously. In this work, we extend the study in Paper I with a more sophisticated model. We first use 3D hydrodynamical simulations to study the co-evolution of the disk and the migration of a sBH in the vicinity of an IMBH. We find that the gaseous torque, together with the tidal torque exerted by the IMBH, can drive synchronized migration until sim 10 Schwarzschild radii from the central supermassive black hole (SMBH). We further use a relativistic three-body code to study the final fate of the sBH in the GW-dominated regime. We find that the sBH can be either captured or kicked out by the IMBH, which will result in either two subsequent IMRIs or an EMRI followed by an IMRI. These events will bring rich information about the formation and evolution of sBHs and IMBHs in AGNs.

Active galactic nuclei (AGNs) have been proposed as plausible sites for hosting a sizable fraction of the binary black hole (BBH) mergers measured through gravitational waves (GWs) by the LIGO-Virgo-Kagra (LVK) experiment. These GWs could be accompanied by radiation feedback due to the interaction of the BBH merger remnant with the AGN disc. We present a new predicted radiation signature driven by the passage of a kicked BBH remnant throughout a thin AGN disc. We analyse the situation of a merger occurring outside the thin disc, where the merger is of second or higher generation in a merging hierarchical sequence. The coalescence produces a kicked BH remnant that eventually plunges into the disc, accretes material, and inflates jet cocoons. We consider the case of a jet cocoon propagating quasi-parallel to the disc plane and study the outflow that results when the cocoon emerges from the disc. We calculate the transient emission of the emerging cocoon using a photon diffusion model typically employed to describe the light curves of supernovae. Depending on the parameter configuration, the flare produced by the emerging cocoon could be comparable to or exceed the AGN background emission at optical, and extreme ultraviolet wavelengths. For instance, in AGNs with central engines of sim 5times10^{6} M_odot, flares driven by BH remnants with masses of sim 100 M_odot can appear in about sim[10-100] days after the GW, lasting for few days.

Post-merger gravitational wave echoes provide a unique opportunity to probe the near-horizon structure of astrophysical black holes, that may be modified due to non-perturbative quantum gravity phenomena. However, since the waveform is subject to large theoretical uncertainties, it is necessary to develop model-agnostic search methods for detecting echoes from observational data. A promising strategy is to identify the characteristic quasinormal modes (QNMs) associated with echoes, {\it in frequency space}, which complements existing searches of quasiperiodic pulses in time. In this study, we build upon our previous work targeting these modes by incorporating relative phase information to optimize the Bayesian search algorithm. Using a new phase-marginalized likelihood, the performance can be significantly improved for well-resolved QNMs. This enables an efficient model-agnostic search for QNMs of different shapes by using a simple search template. To demonstrate the robustness of the search algorithm, we construct four complementary benchmarks for the echo waveform that span a diverse range of different theoretical possibilities for the near-horizon structure. We then validate our Bayesian search algorithms by injecting the benchmark models into different realizations of Gaussian noise. Using two types of phase-marginalized likelihoods, we find that the search algorithm can efficiently detect the corresponding QNMs. Therefore, our search strategy provides a concrete Bayesian and model-agnostic approach to "quantum black hole seismology".

Time series data and their time-frequency representation from gravitational-wave interferometers present multiple opportunities for the use of artificial intelligence methods associated with signal and image processing. Closely connected with this is the real-time aspect associated with gravitational-wave interferometers and the astrophysical observations they perform; the discovery potential of these instruments can be significantly enhanced when data processing can be achieved in O(1s) timescales. In this work, we introduce a novel signal and noise identification tool based on the YOLO (You Only Look Once) object detection framework. For its application into gravitational waves, we will refer to it as GW-YOLO. This tool can provide scene identification capabilities and essential information regarding whether an observed transient is any combination of noise and signal. Additionally, it supplies detailed time-frequency coordinates of the detected objects in the form of pixel masks, an essential property that can be used to understand and characterize astrophysical sources, as well as instrumental noise. The simultaneous identification of noise and signal, combined with precise pixel-level localization, represents a significant advancement in gravitational-wave data analysis. Our approach yields a 50\% detection efficiency for binary black hole signals at a signal-to-noise ratio (SNR) of 15 when such signals overlap with transient noise artifacts. When noise artifacts overlap with binary neutron star signals, our algorithm attains 50\% detection efficiency at an SNR of 30. This presents the first quantitative assessment of the ability to detect astrophysical events overlapping with realistic, instrument noise present in gravitational-wave interferometers.

This work, together with its companion paper, Secco and Samuroff et al. (2021), presents the Dark Energy Survey Year 3 cosmic shear measurements and cosmological constraints based on an analysis of over 100 million source galaxies. With the data spanning 4143 deg^2 on the sky, divided into four redshift bins, we produce the highest significance measurement of cosmic shear to date, with a signal-to-noise of 40. We conduct a blind analysis in the context of the ΛCDM model and find a 3% constraint of the clustering amplitude, S_8equiv σ_8 (Ω_{rm m}/0.3)^{0.5} = 0.759^{+0.025}_{-0.023}. A ΛCDM-Optimized analysis, which safely includes smaller scale information, yields a 2% precision measurement of S_8= 0.772^{+0.018}_{-0.017} that is consistent with the fiducial case. The two low-redshift measurements are statistically consistent with the Planck Cosmic Microwave Background result, however, both recovered S_8 values are lower than the high-redshift prediction by 2.3σ and 2.1σ (p-values of 0.02 and 0.05), respectively. The measurements are shown to be internally consistent across redshift bins, angular scales and correlation functions. The analysis is demonstrated to be robust to calibration systematics, with the S_8 posterior consistent when varying the choice of redshift calibration sample, the modeling of redshift uncertainty and methodology. Similarly, we find that the corrections included to account for the blending of galaxies shifts our best-fit S_8 by 0.5σ without incurring a substantial increase in uncertainty. We examine the limiting factors for the precision of the cosmological constraints and find observational systematics to be subdominant to the modeling of astrophysics. Specifically, we identify the uncertainties in modeling baryonic effects and intrinsic alignments as the limiting systematics.

Creating radio galaxy catalogues from next-generation deep surveys requires automated identification of associated components of extended sources and their corresponding infrared hosts. In this paper, we introduce RadioGalaxyNET, a multimodal dataset, and a suite of novel computer vision algorithms designed to automate the detection and localization of multi-component extended radio galaxies and their corresponding infrared hosts. The dataset comprises 4,155 instances of galaxies in 2,800 images with both radio and infrared channels. Each instance provides information about the extended radio galaxy class, its corresponding bounding box encompassing all components, the pixel-level segmentation mask, and the keypoint position of its corresponding infrared host galaxy. RadioGalaxyNET is the first dataset to include images from the highly sensitive Australian Square Kilometre Array Pathfinder (ASKAP) radio telescope, corresponding infrared images, and instance-level annotations for galaxy detection. We benchmark several object detection algorithms on the dataset and propose a novel multimodal approach to simultaneously detect radio galaxies and the positions of infrared hosts.

The recently launched James Webb Space Telescope (JWST) is opening new observing windows on the distant universe. Among JWST's instruments, the Mid Infrared Instrument (MIRI) offers the unique capability of imaging observations at wavelengths lambda > 5mum. This enables unique access to the rest frame near infra-red (NIR, lambda ge 1\mum) emission from galaxies at redshifts z>4 and the visual (lambda gtrsim 5000\AA) rest frame for z>9. We here report on the guaranteed time observations (GTO) from the MIRI European Consortium, of the Hubble Ultra Deep Field (HUDF), forming the MIRI Deep Imaging Survey (MIDIS), consisting of an on source integration time of sim41 hours in the MIRI/F560W (5.6 mum) filter. To our knowledge, this constitutes the longest single filter exposure obtained with JWST of an extragalactic field as yet.

We present an extragalactic HI 21-cm absorption lines catalog from a blind search at z leqslant 0.35, using drift-scan data collected in 1325.6 hours by the ongoing Commensal Radio Astronomy FasT Survey (CRAFTS) and FAST All Sky HI Survey (FASHI), which spans a sky area of 6072.0 deg^{2} and covers 84533 radio sources with a flux density greater than 12 mJy. 14 previously identified HI absorbers and 20 newly discovered HI absorbers were detected, comprising 15 associated systems, 10 intervening systems, and 9 systems with undetermined classifications. Through spectral stacking, the mean peak optical path, mean velocity-integrated optical path, mean FWHM and mean HI column density are measured to be 0.47 and 0.30; 27.19 and 4.36 km s^{-1}; 42.61 and 9.33 km s^{-1}; 0.49 and 0.08 T_{s} times 10^{20}cm^{-2}K^{-1}, for the associated and intervening samples, respectively. Statistical analysis also reveals that associated systems tend to be hosted by red (g-r>0.7) galaxies at lower redshifts, whereas galaxies hosting intervening HI absorption are typically found at higher redshifts and are of a bluer (g-rleqslant0.7) type. A noticeable difference is observed in the positions of foregrounds, backgrounds of intervening systems, and high-redshift and low-redshift associated systems on the WISE color-color diagram. All identified foreground sources in our sample have W1-W2 magnitudes below 0.8, suggesting no Active Galactic Nuclei (AGN). In contrast, backgrounds of intervening systems tend to have W1-W2 magnitudes above 0.8, indicating AGN presence. For associated absorption, most low-redshift (zleqslant0.5) systems show W1-W2 values below 0.8, while higher-redshift associated absorption (z>0.5) displays a broader range of W1-W2 values.

We present a machine learning search for local, low-mass galaxies (z < 0.02 and 10^6 M_odot < M_* < 10^9 M_odot) using the combined photometric data from the DESI Imaging Legacy Surveys and the WISE survey. We introduce the spectrally confirmed training sample, discuss evaluation metrics, investigate the features, compare different machine learning algorithms, and find that a 7-class neural network classification model is highly effective in separating the signal (local, low-mass galaxies) from various contaminants, reaching a precision of 95% and a recall of 76%. The principal contaminants are nearby sub-L^* galaxies at 0.02 < z < 0.05 and nearby massive galaxies at 0.05 < z < 0.2. We find that the features encoding surface brightness information are essential to achieving a correct classification. Our final catalog, which we make available, consists of 112,859 local, low-mass galaxy candidates, where 36,408 have high probability (p_{rm signal} > 0.95), covering the entire Legacy Surveys DR9 footprint. Using DESI-EDR public spectra and data from the SAGA and ELVES surveys, we find that our model has a precision of sim 100%, 96%, and 97%, respectively, and a recall of sim 51%, 68% and 53%, respectively. The results of those independent spectral verification demonstrate the effectiveness and efficiency of our machine learning classification model.

Ground-based time-domain observatories require minute-by-minute, site-scale awareness of cloud cover, yet existing all-sky datasets are short, daylight-biased, or lack astrometric calibration. We present LenghuSky-8, an eight-year (2018-2025) all-sky imaging dataset from a premier astronomical site, comprising 429,620 512 times 512 frames with 81.2% night-time coverage, star-aware cloud masks, background masks, and per-pixel altitude-azimuth (Alt-Az) calibration. For robust cloud segmentation across day, night, and lunar phases, we train a linear probe on DINOv3 local features and obtain 93.3% pm 1.1% overall accuracy on a balanced, manually labeled set of 1,111 images. Using stellar astrometry, we map each pixel to local alt-az coordinates and measure calibration uncertainties of approximately 0.37 deg at zenith and approximately 1.34 deg at 30 deg altitude, sufficient for integration with telescope schedulers. Beyond segmentation, we introduce a short-horizon nowcasting benchmark over per-pixel three-class logits (sky/cloud/contamination) with four baselines: persistence (copying the last frame), optical flow, ConvLSTM, and VideoGPT. ConvLSTM performs best but yields only limited gains over persistence, underscoring the difficulty of near-term cloud evolution. We release the dataset, calibrations, and an open-source toolkit for loading, evaluation, and scheduler-ready alt-az maps to boost research in segmentation, nowcasting, and autonomous observatory operations.

Strongly lensed variable quasars can serve as precise cosmological probes, provided that time delays between the image fluxes can be accurately measured. A number of methods have been proposed to address this problem. In this paper, we explore in detail a new approach based on kernel regression estimates, which is able to estimate a single time delay given several datasets for the same quasar. We develop realistic artificial data sets in order to carry out controlled experiments to test of performance of this new approach. We also test our method on real data from strongly lensed quasar Q0957+561 and compare our estimates against existing results.

We present the largest ground-based catalogue of M-dwarf flares to date, comprising 1,229 time-resolved events identified in Zwicky Transient Facility Data Release 17. Using high-cadence ZTF observations collected between April 2018 and September 2020, we analyzed over 93 million variable light curves containing 4.1 billion photometric measurements. Flare candidates were identified through a machine-learning pipeline trained on simulated light curves generated by injecting TESS-based flare templates into ZTF data and then refined through an extensive post-filtering stage combining an additional classifier, metadata checks, and human inspection. For 655 flares with reliable Gaia-based distances and well-sampled light curves, we derived bolometric energies ranging from 10^31 to 10^35 erg. A clear correlation is observed between flare frequency and spectral subtype, with a sharp increase toward later M dwarfs, particularly near M4-M5, coinciding with the transition to full convection. Using 680 flaring stars with known vertical distances from the Galactic plane, we find that the fraction of flaring stars decreases with increasing Galactic height. The resulting catalogue provides the most comprehensive ground-based sample of M-dwarf flares and establishes a framework for flare detection and classification in upcoming wide-field surveys such as the Vera C. Rubin Observatory Legacy Survey of Space and Time.

In this paper, we present GALEX-SDSS-WISE Legacy Catalog (GSWLC), a catalog of physical properties (stellar masses, dust attenuations and star formation rates (SFRs)) of ~700,000 galaxies with SDSS redshifts below 0.3. GSWLC contains galaxies within the GALEX footprint, regardless of a UV detection, covering 90% of SDSS. The physical properties were obtained from UV/optical SED fitting following Bayesian methodology of Salim et al. (2007), with improvements such as blending corrections for low-resolution UV photometry, flexible dust attenuation laws, and emission line corrections. GSWLC includes mid-IR SFRs derived from IR templates based upon 22 micron WISE observations. These estimates are independent of UV/optical SED fitting, in order to separate possible systematics. The paper argues that the comparison of specific SFRs (SSFRs) is more informative and physically motivated than the comparison of SFRs. SSFRs resulting from the UV/optical SED fitting are compared to the mid-IR SSFRs, and to SSFRs from three published catalogs. For "main sequence" galaxies with no AGN contribution all SSFRs are in very good agreement (within 0.1 dex on average). In particular, the widely-used aperture-corrected SFRs from MPA/JHU catalog show no systematic offsets, in contrast to some integral-field spectroscopy results. For galaxies below the main sequence (log SSFR<-11), mid-IR (S)SFRs based on fixed luminosity-SFR conversion are severely biased (up to 2 dex) because the dust is primarily heated by old stars. Furthermore, mid-IR (S)SFRs are overestimated by up to 0.6 dex for galaxies with AGN, presumably due to non-stellar dust heating. UV/optical (S)SFRs are thus preferred to IR-based (S)SFRs for quenched galaxies and those which host AGN.

We present the results of HI spectral stacking analysis of Giant Metrewave Radio Telescope (GMRT) observations targeting the COSMOS field. The GMRT data cube contains 474 field galaxies with redshifts known from the zCOSMOS-bright 10k catalogue. Spectra for the galaxies are co-added and the stacked spectrum allows us to make a sim 3σ measurement of the average HI mass. Using this average HI mass along with the integral optical B-band luminosity of the galaxies and the luminosity density of the COSMOS field, a volume normalisation is applied to obtain the cosmic HI mass density (Ω_{rm HI}). We find a cosmic HI mass density of Ω_{rm HI} = (0.42 pm 0.16) times 10^{-3} at z sim 0.37, which is the highest-redshift measurement of Ω_{rm HI} ever made using HI spectral stacking. The value we obtained for Ω_{rm HI} at z sim 0.37 is consistent with that measured from large blind 21-cm surveys at z = 0 as well as measurements from other HI stacking experiments at lower redshifts. Our measurement in conjunction with earlier measurements indicates that there has been no significant evolution of HI gas abundance over the last 4 Gyr. A weighted mean of Ω_{rm HI} from all 21-cm measurements at redshifts z lesssim 0.4 gives Ω_{rm HI} = (0.35 pm 0.01) times 10^{-3}. The Ω_{rm HI} measured (from HI 21-cm emission measurements) at z lesssim 0.4 is however approximately half that measured from Damped Lyman-α Absorption (DLA) systems at z gtrsim 2. Deeper surveys with existing and upcoming instruments will be critical to understand the evolution of Ω_{rm HI} in the redshift range intermediate between z sim 0.4 and the range probed by DLA observations.

Modern astronomical surveys, such as the Zwicky Transient Facility (ZTF), are capable of detecting thousands of transient events per year, necessitating the use of automated and scalable data analysis techniques. Recent advances in machine learning have enabled the efficient classification and characterization of these transient phenomena. We aim to develop a fully systematic pipeline to identify candidate stellar collision events in galactic nuclei, which may otherwise be identified as tidal disruption events or other transients. We also seek to validate our simulations by comparing key physical parameters derived from observations and used in modeling these events. We generate a comprehensive bank of simulated light curves spanning a range of physical parameters and employ an approximate nearest neighbor algorithm (via the annoy library) to match these with observed ZTF light curves. Our pipeline is successfully able to associate observed ZTF light curves with simulated events. The resulting estimated parameters, including supermassive black hole masses and ejecta mass, are presented and compared to known values when applicable. We demonstrate that a systematic, machine learning-based approach can effectively identify and characterize stellar collision candidate events from large-scale transient surveys. This methodology is especially promising for future surveys which will provide us with significantly high volumes of data, such as LSST, where automated, data-intensive analysis will be critical for advancing our understanding of transient astrophysical phenomena.

We investigate the relationship between the Lyman-alpha (Lya) forest transmission in the intergalactic medium (IGM) and the environmental density of galaxies, focusing on its implications for the measurement of ionizing radiation escape fractions. Using a sample of 268 spectroscopically confirmed background galaxies at 2.7<z<3.0 and a galaxy density map at z~2.5 within the COSMOS field, we measure the Lya transmission photometrically, leveraging the multiwavelength data available from the COSMOS2020 catalog. Our results reveal a weak but statistically significant positive correlation between Lya optical depth and galaxy density contrast, suggesting that overdense regions are enriched in neutral gas, which could bias escape fraction measurements. This emphasizes the need to account for the large-scale structure of the IGM in analyses of ionizing radiation escape fractions, and highlights the advantages of a photometric approach for increasing the number of sampled lines of sight across large fields. The photometric redshifts provided by upcoming all-sky surveys, such as Euclid, will make it possible to account for this effect across widely separated fields.

We present the results of simulated injections testing the first Bayesian search-pipeline capable of investigating the angular-structure of a gravitational-wave (GW) background influencing pulsar signals. A stochastic background of GWs from the incoherent superposition of many inspiraling supermassive black hole binaries at nHz frequencies is likely to be the dominant GW signal detectable by pulsar timing arrays (PTAs). Even though one might expect a background composed of a high-redshift cosmological population of sources to be fairly isotropic, deviations from isotropy may be indicative of local GW hotspots or some form of continuous anisotropy in the angular-distribution of GW-power. A GWB induces time-of-arrival deviations in pulsar signals which are correlated between separated pulsars. In an isotropic background this cross-correlation follows a distinctive relationship, known as the Hellings and Downs curve, that depends only on the angular separation of the pulsars. If the background is anisotropic, the cross-correlation is different, but predictable, and also depends on the absolute position of the pulsars. By simulating datasets containing GWBs with various anisotropic configurations, we have explored the prospects for constraining anisotropy using near future data. We find that at moderate to high signal to noise ratio the assumption of isotropy is no longer an appropriate description of the simulated background. Furthermore, we can recover the nature of the injected anisotropy in a Bayesian parameter-estimation search, and propose a prior on the anisotropy search-space motivated by the physicality of the implied distribution of sources.

We use deep, mu_{r} lesssim 28,mag,arcsec^{-2}, r-band imaging from the Dark Energy Camera Legacy Survey (DECaLS) to search for past, or ongoing, merger activity in a sample of 282 Low Excitation Radio Galaxies (LERGs) at z<0.07. Our principle aim is to assess the the role of mergers in the evolution of LERGs. Exploiting the imaging depth, we classify tidal remnants around galaxies as both minor and major morphological disturbances for our LERG sample and 1,622 control galaxies matched in redshift, stellar mass, and environment. In groups and in the field, the LERG minor merger fraction is consistent with the control population. In galaxy clusters, 8.8 pm 2.9, % of LERGs show evidence of recent minor mergers in contrast to 23.0pm 2.0, % of controls. This sim 4 sigma deficit of minor mergers in cluster LERGs suggests these events may inhibit this type of nuclear activity for galaxies within the cluster environment. We observe a > 4sigma excess of major mergers in the LERGs with M_{*} lesssim 10^{11},M_{odot}, with 10 pm 1.5, % of these AGN involved in such large-scale interactions compared to 3.2 pm 0.4,% of control galaxies. This excess of major mergers in LERGs decreases with increasing stellar mass, vanishing by M_{*} > 10^{11.3},M_{odot}. These observations show that minor mergers do not fuel LERGs, and are consistent with typical LERGs being powered by accretion of matter from their halo. Where LERGs are associated with major mergers, these objects may evolve into more efficiently accreting active galactic nuclei as the merger progresses and more gas falls on to the central engine.

We present results from a long-term monitoring of frequency dependent eclipses of the radio emission from PSR J1544+4937 which is a ``black widow spider'' millisecond pulsar (MSP) in a compact binary system. The majority of such systems often exhibit relatively long duration radio eclipses caused by ablated material from their companion stars. With the wide spectral bandwidth of upgraded Giant Metrewave Radio Telescope (uGMRT), we present first systematic study of temporal variation of eclipse cut-off frequency. With decade-long monitoring of 39 eclipses for PSR J1544+4937, we notice significant changes in the observed cut-off frequency ranging from 343 pm 7 MHz to > 740 MHz. We also monitored changes in eclipse cut-off frequency on timescales of tens of days and observed a maximum change of ge 315 MHz between observations that were separated by 22 days. In addition, we observed a change of sim 47 MHz in eclipse cut-off frequency between adjacent orbits, i.e. on timescales of sim 2.9 hours. We infer that such changes in the eclipse cut-off frequency depict an eclipse environment for the PSR J1544+4937 system that is dynamically evolving, where, along with the change in electron density, the magnetic field could also be varying. We also report a significant correlation between the eclipse cut-off frequency and the mass loss rate of the companion. This study provides the first direct evidence of mass loss rate affecting the frequency dependent eclipsing in a spider MSP.

Passive space-borne radiometers operating in the 1400-1427 MHz protected frequency band face radio frequency interference (RFI) from terrestrial sources. With the growth of wireless devices and the appearance of new technologies, the possibility of sharing this spectrum with other technologies would introduce more RFI to these radiometers. This band could be an ideal mid-band frequency for 5G and Beyond, as it offers high capacity and good coverage. Current RFI detection and mitigation techniques at SMAP (Soil Moisture Active Passive) depend on correctly detecting and discarding or filtering the contaminated data leading to the loss of valuable information, especially in severe RFI cases. In this paper, we propose an autoencoder-based RFI mitigation method to remove the dominant RFI caused by potential coexistent terrestrial users (i.e., 5G base station) from the received contaminated signal at the passive receiver side, potentially preserving valuable information and preventing the contaminated data from being discarded.

We present observations and timing analyses of 68 millisecond pulsars (MSPs) comprising the 15-year data set of the North American Nanohertz Observatory for Gravitational Waves (NANOGrav). NANOGrav is a pulsar timing array (PTA) experiment that is sensitive to low-frequency gravitational waves. This is NANOGrav's fifth public data release, including both "narrowband" and "wideband" time-of-arrival (TOA) measurements and corresponding pulsar timing models. We have added 21 MSPs and extended our timing baselines by three years, now spanning nearly 16 years for some of our sources. The data were collected using the Arecibo Observatory, the Green Bank Telescope, and the Very Large Array between frequencies of 327 MHz and 3 GHz, with most sources observed approximately monthly. A number of notable methodological and procedural changes were made compared to our previous data sets. These improve the overall quality of the TOA data set and are part of the transition to new pulsar timing and PTA analysis software packages. For the first time, our data products are accompanied by a full suite of software to reproduce data reduction, analysis, and results. Our timing models include a variety of newly detected astrometric and binary pulsar parameters, including several significant improvements to pulsar mass constraints. We find that the time series of 23 pulsars contain detectable levels of red noise, 10 of which are new measurements. In this data set, we find evidence for a stochastic gravitational-wave background.

The James Webb Space Telescope (JWST) has recently discovered a new population of objects at high redshift referred to as `Little Red Dots' (LRDs). Their nature currently remains elusive, despite their surprisingly high inferred number densities. This emerging population of red point-like sources is reshaping our view of the early Universe and may shed light on the formation of high-redshift supermassive black holes. Here we present a spectroscopically confirmed LRD CANUCS-LRD-z8.6 at z_{rm spec}=8.6319pm 0.0005 hosting an Active Galactic Nucleus (AGN), using JWST data. This source shows the typical spectral shape of an LRD (blue UV and red optical continuum, unresolved in JWST imaging), along with broad Hbeta line emission, detection of high-ionization emission lines (CIV, NIV]) and very high electron temperature indicative of the presence of AGN. This is also combined with a very low metallicity (Z<0.1 Z_odot). The presence of all these diverse features in one source makes CANUCS-LRD-z8.6 unique. We show that the inferred black hole mass of CANUCS-LRD-z8.6 (M_{rm BH}=1.0^{+0.6}_{-0.4}times 10^{8}rm ~M_odot) strongly challenges current standard theoretical models and simulations of black hole formation, and forces us to adopt `ad hoc' prescriptions. Indeed if massive seeds, or light seeds with super-Eddington accretion, are considered, the observed BH mass of CANUCS-LRD-z8.6 at z=8.6 can be reproduced. Moreover, the black hole is over-massive compared to its host, relative to the local M_{rm BH}-M_* relations, pointing towards an earlier and faster evolution of the black hole compared to its host galaxy.

We present photometric properties and distance measurements of 252 high redshift Type Ia supernovae (0.15 < z < 1.1) discovered during the first three years of the Supernova Legacy Survey (SNLS). These events were detected and their multi-colour light curves measured using the MegaPrime/MegaCam instrument at the Canada-France-Hawaii Telescope (CFHT), by repeatedly imaging four one-square degree fields in four bands. Follow-up spectroscopy was performed at the VLT, Gemini and Keck telescopes to confirm the nature of the supernovae and to measure their redshifts. Systematic uncertainties arising from light curve modeling are studied, making use of two techniques to derive the peak magnitude, shape and colour of the supernovae, and taking advantage of a precise calibration of the SNLS fields. A flat LambdaCDM cosmological fit to 231 SNLS high redshift Type Ia supernovae alone gives Omega_M = 0.211 +/- 0.034(stat) +/- 0.069(sys). The dominant systematic uncertainty comes from uncertainties in the photometric calibration. Systematic uncertainties from light curve fitters come next with a total contribution of +/- 0.026 on Omega_M. No clear evidence is found for a possible evolution of the slope (beta) of the colour-luminosity relation with redshift.

Next-generation radio astronomy surveys are delivering millions of resolved sources, but robust and scalable morphology analysis remains difficult across heterogeneous telescopes and imaging pipelines. We present STRADAViT, a self-supervised Vision Transformer continued-pretraining framework for learning transferable encoders from radio astronomy imagery. The framework combines mixed-survey data curation, radio astronomy-aware training-view generation, and a ViT-MAE-initialized encoder family with optional register tokens, and supports reconstruction-only, contrastive-only, and two-stage branches. Our pretraining dataset comprises radio astronomy cutouts drawn from four complementary sources: MeerKAT, ASKAP, LOFAR/LoTSS, and SKA SDC1 simulated data. We evaluate transfer with linear probing and fine-tuning on three morphology benchmarks spanning binary and multi-class settings: MiraBest, LoTSS DR2, and Radio Galaxy Zoo. Relative to the ViT-MAE initialization used for continued pretraining, the best two-stage models improve Macro-F1 in all reported linear-probe settings and in two of three fine-tuning settings, with the largest gain on RGZ DR1. Relative to DINOv2, gains are selective: the best two-stage models achieve higher mean Macro-F1 than the strongest DINOv2 baseline on LoTSS DR2 and RGZ DR1 under linear probing, and on MiraBest and RGZ DR1 under fine-tuning. A targeted DINOv2 initialization ablation further indicates that the adaptation recipe is not specific to the ViT-MAE starting point. The ViT-MAE-based STRADAViT checkpoint is retained as the released checkpoint because it combines competitive transfer with lower token count and downstream cost than the DINOv2-based alternative.

Continual pretraining of large language models on domain-specific data has been proposed to enhance performance on downstream tasks. In astronomy, the previous absence of astronomy-focused benchmarks has hindered objective evaluation of these specialized LLM models. Leveraging a recent initiative to curate high-quality astronomical MCQs, this study aims to quantitatively assess specialized LLMs in astronomy. We find that the previously released AstroLLaMA series, based on LLaMA-2-7B, underperforms compared to the base model. We demonstrate that this performance degradation can be partially mitigated by utilizing high-quality data for continual pretraining, such as summarized text from arXiv. Despite the observed catastrophic forgetting in smaller models, our results indicate that continual pretraining on the 70B model can yield significant improvements. However, the current supervised fine-tuning dataset still constrains the performance of instruct models. In conjunction with this study, we introduce a new set of models, AstroLLaMA-3-8B and AstroLLaMA-2-70B, building upon the previous AstroLLaMA series.

The planned space-based gravitational wave detector, LISA, will provide a fundamentally new means of studying the orbital alignment of close white dwarf binaries. However, due to the inherent symmetry of their gravitational wave signals, a fourfold degeneracy arises in the transverse projections of their angular momentum vectors. In this paper, we demonstrate that by incorporating timing information from electromagnetic observations, such as radial velocity modulations and light curves, this degeneracy can be reduced to twofold.

The observation of the shadow of the supermassive black hole M87^{*} by the Event Horizon Telescope (EHT) is sensitive to the spacetime geometry near the circular photon orbit and beyond, and it thus has the potential to test general relativity in the strong field regime. Obstacles to this program, however, include degeneracies between putative deviations from general relativity and both the description of the accretion flow and the uncertainties on "calibration parameters", such as e.g. the mass and spin of the black hole. In this work, we introduce a formalism, based on a principal component analysis, capable of reconstructing the black hole metric (i.e. the "signal") in an agnostic way, while subtracting the "foreground" due to the uncertainties in the calibration parameters and the modelling of the accretion flow. We apply our technique to simulated mock data for spherically symmetric black holes surrounded by a thick accretion disk. We show that separation of signal and foreground may be possible with next generation EHT-like experiments.

In the next decade gravitational waves might be detected using a pulsar timing array. In an effort to develop optimal detection strategies for stochastic backgrounds of gravitational waves in generic metric theories of gravity, we investigate the overlap reduction functions for these theories and discuss their features. We show that the sensitivity to non-transverse gravitational waves is greater than the sensitivity to transverse gravitational waves and discuss the physical origin of this effect. We calculate the overlap reduction functions for the current NANOGrav Pulsar Timing Array (PTA) and show that the sensitivity to the vector and scalar-longitudinal modes can increase dramatically for pulsar pairs with small angular separations. For example, the J1853+1303-J1857+0943 pulsar pair, with an angular separation of about 3 degrees, is about 10^4 times more sensitive to the longitudinal component of the stochastic background, if it is present, than the transverse components.

This paper presents optical night sky brightness measurements from the stratosphere using CCD images taken with the Super-pressure Balloon-borne Imaging Telescope (SuperBIT). The data used for estimating the backgrounds were obtained during three commissioning flights in 2016, 2018, and 2019 at altitudes ranging from 28 km to 34 km above sea level. For a valid comparison of the brightness measurements from the stratosphere with measurements from mountain-top ground-based observatories (taken at zenith on the darkest moonless night at high Galactic and high ecliptic latitudes), the stratospheric brightness levels were zodiacal light and diffuse Galactic light subtracted, and the airglow brightness was projected to zenith. The stratospheric brightness was measured around 5.5 hours, 3 hours, and 2 hours before the local sunrise time in 2016, 2018, and 2019 respectively. The B, V, R, and I brightness levels in 2016 were 2.7, 1.0, 1.1, and 0.6 mag arcsec^{-2} darker than the darkest ground-based measurements. The B, V, and R brightness levels in 2018 were 1.3, 1.0, and 1.3 mag arcsec^{-2} darker than the darkest ground-based measurements. The U and I brightness levels in 2019 were 0.1 mag arcsec^{-2} brighter than the darkest ground-based measurements, whereas the B and V brightness levels were 0.8 and 0.6 mag arcsec^{-2} darker than the darkest ground-based measurements. The lower sky brightness levels, stable photometry, and lower atmospheric absorption make stratospheric observations from a balloon-borne platform a unique tool for astronomy. We plan to continue this work in a future mid-latitude long duration balloon flight with SuperBIT.

We continue our program of investigation of the proper motions of spectrally separated structures in the Herbig-Haro outflows with the aid of Fabry-Perot scanning interferometry. This work mainly focuses on the physical nature of various structures in the jets. The aim of the present study is to measure the proper motions of the previously discovered kinematically separated structures in the working surface of the HH 83 collimated outflow. We used observations from two epochs separated by 15 years, which were performed on the 6m telescope with Fabry-Perot scanning interferometer. We obtained images corresponding to different radial velocities for the two separate epochs, and used them to measure proper motions. In the course of our data analysis, we discovered a counter bow-shock of HH 83 flow with positive radial velocity, which makes this flow a relatively symmetric bipolar system. The second epoch observations confirm that the working surface of the flow is split into two structures with an exceptionally large (250 km\ s^{-1}) difference in radial velocity. The proper motions of these structures are almost equal, which suggests that they are physically connected. The asymmetry of the bow shock and the turning of proper motion vectors suggests a collision between the outflow and a dense cloud. The profile of the Halpha line for the directly invisible infrared source HH 83 IRS, obtained by integration of the data within the reflection nebula, suggests it to be of P Cyg type with a broad absorption component characteristic of the FU Ori like objects. If this object underwent an FU Ori type outburst, which created the HH 83 working surfaces, its eruption took place about 1500 years ago according to the kinematical age of the outflow.

We study the problem of estimating the time delay between two signals representing delayed, irregularly sampled and noisy versions of the same underlying pattern. We propose and demonstrate an evolutionary algorithm for the (hyper)parameter estimation of a kernel-based technique in the context of an astronomical problem, namely estimating the time delay between two gravitationally lensed signals from a distant quasar. Mixed types (integer and real) are used to represent variables within the evolutionary algorithm. We test the algorithm on several artificial data sets, and also on real astronomical observations of quasar Q0957+561. By carrying out a statistical analysis of the results we present a detailed comparison of our method with the most popular methods for time delay estimation in astrophysics. Our method yields more accurate and more stable time delay estimates: for Q0957+561, we obtain 419.6 days for the time delay between images A and B. Our methodology can be readily applied to current state-of-the-art optical monitoring data in astronomy, but can also be applied in other disciplines involving similar time series data.

Mergers play a complex role in galaxy formation and evolution. Continuing to improve our understanding of these systems require ever larger samples, which can be difficult (even impossible) to select from individual surveys. We use the new platform ESA Datalabs to assemble a catalogue of interacting galaxies from the Hubble Space Telescope science archives; this catalogue is larger than previously published catalogues by nearly an order of magnitude. In particular, we apply the Zoobot convolutional neural network directly to the entire public archive of HST F814W images and make probabilistic interaction predictions for 126 million sources from the Hubble Source Catalogue. We employ a combination of automated visual representation and visual analysis to identify a clean sample of 21,926 interacting galaxy systems, mostly with z < 1. Sixty five percent of these systems have no previous references in either the NASA Extragalactic Database or Simbad. In the process of removing contamination, we also discover many other objects of interest, such as gravitational lenses, edge-on protoplanetary disks, and `backlit' overlapping galaxies. We briefly investigate the basic properties of this sample, and we make our catalogue publicly available for use by the community. In addition to providing a new catalogue of scientifically interesting objects imaged by HST, this work also demonstrates the power of the ESA Datalabs tool to facilitate substantial archival analysis without placing a high computational or storage burden on the end user.

We present cosmological analysis of 12 nearby (z<0.06) Type IIP supernovae (SNe IIP) observed with the ROTSE-IIIb telescope. To achieve precise photometry, we present a new image differencing technique that is implemented for the first time on the ROTSE SN photometry pipeline. With this method, we find up to a 20\% increase in the detection efficiency and significant reduction in residual RMS scatter of the SN lightcurves when compared to the previous pipeline performance. We use the published optical spectra and broadband photometry of well studied SNe IIP to establish temporal models for ejecta velocity and photospheric temperature evolution for our SNe IIP population. This study yields measurements that are competitive to other methods even when the data are limited to a single epoch during the photospheric phase of SNe IIP. Using the fully reduced ROTSE photometry and optical spectra, we apply these models to the respective photometric epochs for each SN in the ROTSE IIP sample. This facilitates the use of the Expanding Photosphere Method (EPM) to obtain distance estimates to their respective host galaxies. We then perform cosmological parameter fitting using these EPM distances from which we measure the Hubble constant to be 72.9^{+5.7}_{-4.3}~{rm kms^{-1}~Mpc^{-1}}, which is consistent with the standard Lambda CDM model values derived using other independent techniques.

High to ultrahigh energy neutrino detectors can uniquely probe the properties of dark matter χ by searching for the secondary products produced through annihilation and/or decay processes. We evaluate the sensitivities to dark matter thermally averaged annihilation cross section langleσvrangle and partial decay width into neutrinos Γ_{χrightarrowνbarν} (in the mass scale 10^7 leq m_χ/{rm GeV} leq 10^{15}) for next generation observatories like POEMMA and GRAND. We show that in the range 10^7 leq m_χ/{rm GeV} leq 10^{11}, space-based Cherenkov detectors like POEMMA have the advantage of full-sky coverage and rapid slewing, enabling an optimized dark matter observation strategy focusing on the Galactic center. We also show that ground-based radio detectors such as GRAND can achieve high sensitivities and high duty cycles in radio quiet areas. We compare the sensitivities of next generation neutrino experiments with existing constraints from IceCube and updated 90\% C.L. upper limits on langleσvrangle and Γ_{χrightarrowνbarν} using results from the Pierre Auger Collaboration and ANITA. We show that in the range 10^7 leq m_χ/{rm GeV} leq 10^{11} POEMMA and GRAND10k will improve the neutrino sensitivity to particle dark matter by factors of 2 to 10 over existing limits, whereas GRAND200k will improve this sensitivity by two orders of magnitude. In the range 10^{11} leq m_χ/{rm GeV} leq 10^{15}, POEMMA's fluorescence observation mode will achieve an unprecedented sensitivity to dark matter properties. Finally, we highlight the importance of the uncertainties related to the dark matter distribution in the Galactic halo, using the latest fit and estimates of the Galactic parameters.

While the temporal variations of the spectro-polarimetric nature of pulsars remains unexplored, this investigation offers significant potential for uncovering key insights into pulsar emission mechanisms, magnetic field geometry, and propagation effects within the magnetosphere. We developed a package for investigating time-varying spectral behavior for full Stokes parameters and demonstrate it on a millisecond pulsar (MSP) J2144-5237 in a binary system (orbital period ~10 days) using the Parkes UWL receiver. In this study we report rotation measure (RM) variation with orbital phase. We find that the temporal variations in the spectra of Stokes I, Q, and V are generally correlated throughout the orbit, while Stokes U exhibits intervals of both correlation and anticorrelation with Stokes I, depending on the orbital phase. We also provide a Poincare sphere representation of the polarization properties of J2144-5237, demonstrating a systematic temporal change of Poincare sphere location for the main component with orbital phase. To our knowledge, this is the first investigation of time-varying properties of the spectro-polarimetric nature of any pulsars or MSPs. Extending this study to probe the spectro-temporal nature of full Stokes data on a larger sample of MSPs or pulsars has the potential to provide vital information on emission mechanisms inside the magnetosphere, interstellar propagation effects, and binary interactions.

We conducted 22~GHz 1" JVLA imaging of 100 radio-quiet X-ray selected AGN from the Swift-BAT survey. We find AGN-driven kiloparsec-scale radio structures inconsistent with pure star formation in 11 AGN. The host galaxies of these AGN lie significantly below the star-forming main sequence, indicating suppressed star formation. While these radio structures tend to be physically small compared to the host galaxy, the global star formation rate of the host is affected. We evaluate the energetics of the radio structures interpreted first as immature radio jets, and then as consequences of an AGN-driven radiative outflow, and compare them to two criteria for successful feedback: the ability to remove the CO-derived molecular gas mass from the galaxy gravitational potential and the kinetic energy transfer to molecular clouds leading to v_cloud > sigma_*. In most cases, the jet interpretation is insufficient to provide the energy necessary to cause the star formation suppression. Conversely, the wind interpretation provides ample energy in all but one case. We conclude that it is more likely that the observed suppression of star formation in the global host galaxy is due to ISM interactions of a radiative outflow, rather than a small-scale radio jet.

We increase the spectroscopic completeness of the 100 pc white dwarf sample in the SDSS footprint with 840 additional spectra. Our spectroscopy is 86% complete for white dwarfs hotter than T_{rm eff}= 5000 K, where Halpha remains visible and provides reliable constraints on the atmospheric composition. We identify 2108 DA white dwarfs with pure hydrogen atmospheres, and show that ultramassive DA white dwarfs with Mgeq1.1~M_{odot} are an order of magnitude less common below 10,000 K. This is consistent with a fraction of them getting stuck on the crystallization sequence due to ^{22}Ne distillation. In addition, there are no ultramassive DA white dwarfs with Mgeq1.1~M_{odot} and T_{rm eff}leq6000 K in our sample, likely because Debye cooling makes them rapidly fade away. We detect a significant trend in the fraction of He-atmosphere white dwarfs as a function of temperature; the fraction increases from 9% at 20,000 K to 32% at 6000 K. This provides direct evidence of convective mixing in cool DA white dwarfs. Finally, we detect a relatively tight sequence of low-mass DQ white dwarfs in color-magnitude diagrams for the first time. We discuss the implications of this tight DQ sequence, and conclude with a discussion of the future prospects from the upcoming ULTRASAT mission and the large-scale multi-fiber spectroscopic surveys.

We present constraints on the spacetime variation of the fine-structure constant alpha at redshifts 2.5le z<9.5 using JWST emission-line galaxies. The galaxy sample consists of 621 high-quality spectra with strong and narrow [O III] lambdalambda4959,5007 doublet emission lines from 578 galaxies, including 232 spectra at z>5. The [O III] doublet lines are arguably the best emission lines to probe the variation in alpha. We divide our sample into six subsamples based on redshift and calculate the relative variation Deltaalpha/alpha for the individual subsamples. The calculated Deltaalpha/alpha values are consistent with zero within 1sigma at all redshifts, suggesting no time variation in alpha above a level of (1-2) times10^{-4} (1sigma) in the past 13.2 billion years. When the whole sample is combined, the constraint is improved to be Deltaalpha/alpha = (0.2pm0.7) times10^{-4}. We further test the spatial variation in alpha using four subsamples of galaxies in four different directions on the sky. The measured Deltaalpha/alpha values are consistent with zero at a 1sigma level of sim 2times10^{-4}. While the constraints in this work are not as stringent as those from lower-redshift quasar absorption lines in previous studies, this work uses an independent tracer and provides the first constraints on Deltaalpha/alpha at the highest redshifts. With the growing number of emission-line galaxies from JWST, we expect to achieve stronger constraints in the future.

In this work, we aim to estimate the stellar parameters of the primary (Aa) by performing asteroseismic analysis on its period-spacing pattern. We use the C-3PO neural network to perform asteroseismic modelling of the g-mode period-spacing pattern of Aa, discussing the interplay of this information with external constraints from spectroscopy (T_{rm eff} and log(g)) and eclipse modelling (R). To estimate the level of uncertainty due to different frequency extraction and pattern identification processes, we consider four different variations on the period-spacing patterns. To better understand the correlations between and the uncertainty structure of our parameter estimates, we also employed a classical, parameter-based MCMC grid search on four different stellar grids. The best-fitting, externally constrained model to the period-spacing pattern arrives at estimates of the stellar properties for Aa of: M=1.51 pm 0.05 M_odot, X_c =0.43 pm 0.04, R=1.66 pm 0.1 R_odot, f_{rm ov}=0.010, Omega_c=1.58 pm 0.01 d^{-1} with rigid rotation to within the measurement errors, log(T_{rm eff})=3.856 pm 0.008 dex, log(g)=4.18 pm 0.04 dex, and log(L)=0.809 pm 0.005 dex, which agree well with previous measurements from eclipse modelling, spectroscopy, and the Gaia DR3 luminosity. We find that the near-core properties of the best-fitting asteroseismic models are consistent with external constraints from eclipse modelling and spectroscopy. Aa appears to be a typical example of a gamma Dor star, fitting well within existing populations. We find that Aa is quasi-rigidly rotating to within the uncertainties, and note that the asteroseismic age estimate for Aa (1100 pm 100 Myr) is considerably older than the young (35 Myr) age implied by previous isochrone fits to the B binary in the literature. Our MCMC parameter-based grid-search agrees well with our pattern-modelling approach.

Strong gravitational lensing of variable sources, such as quasars or supernovae, can be used to constrain cosmological parameters through a technique known as "time-delay cosmography''. Competitive constraints on the Hubble constant have been achieved with electromagnetic observations of lensed quasars and lensed supernovae. Gravitational wave (GW) astronomy may open up a new channel for time-delay cosmography with GW signal replacing the electromagnetic (EM) one. We highlight the similarities of using GW signals to be applied to time-delay cosmography compared to EM signal. We then discuss key differences between GW and EM signals and their resulting advantages and inconveniences from the angle of the current state-of-the-art using quasars and lensed supernovae for time-delay cosmography. We identify the astrometric precision requirement of the images as a key challenge to overcome and highlight the potentially significant impact that near-perfect time-delay measurements of lensed GWs can bring to the table.

In the coming years, surveys such as the Rubin Observatory's Legacy Survey of Space and Time (LSST) are expected to increase the number of observed Tidal Disruption Events (TDEs) substantially. We employ Monte Carlo integration to calculate the unlensed and lensed TDE rate as a function of limiting magnitude in u, g, r, and i-bands. We investigate the impact of multiple luminosity models, black hole mass functions (BHMFs), and flare temperatures on the TDE rate. Notably, this includes a semi-analytical model, which enables the determination of the TDE temperature in terms of black hole (BH) mass. We predict the highest unlensed TDE rate to be in g-band. It ranges from 16 to 5,440;yr^{-1};(20,000;deg^2)^{-1} for the Zwicky Transient Facility, being more consistent with the observed rate at the low end. For LSST, we expect a rate in g-band between 3,580 and 82,060;yr^{-1};(20,000;deg^2)^{-1}. A higher theoretical prediction is understandable, as we do not consider observational effects such as completeness. The unlensed and lensed TDE rates are insensitive to the redshift evolution of the BHMF, even for LSST limiting magnitudes. The best band for detecting lensed TDEs is also g-band. Its predicted rates range from 0.43 to 15;yr^{-1};(20,000;deg^2)^{-1} for LSST. The scatter of predicted rates reduces when we consider the fraction of lensed TDEs; that is, a few in ten thousand TDEs will be lensed. Despite the large scatter in the rates of lensed TDEs, our comprehensive considerations of multiple models suggest that lensed TDEs will occur in the 10-year LSST lifetime, providing an exciting prospect for detecting such events. We expect the median redshift of a lensed TDE to be between 1.5 and 2. In this paper, we additionally report on lensed TDE properties, such as the BH mass and time delays.

Supermassive black hole binaries (SMBHBs) are among the most powerful known sources of gravitational waves (GWs). Accordingly, these systems could dominate GW emission in the micro- and millihertz frequency range. Within this domain, SMBHs evolve rapidly and merge with each other. Dynamical friction from stars and gas at the centers of galaxies typically helps to bring together two SMBHs when they are at relatively far separations (approx kpc - 100 pc), but becomes less efficient at smaller separations. However, dark matter (DM) spikes around SMBHs could enhance dynamical friction at close separations and, thus, shorten the evolution times. In this paper, we simulate the effects of DM spikes on GW signals in the micro- to millihertz frequency range and confirm that the GW signals from SMBHBs with DM spikes can be clearly distinguished from those without any additional matter. Making use of the projected sensitivity curve of the Laser Interferometer Space Antenna (LISA), we forecast upper limits for the (dark) matter density for given future SMBHB observations. We then compare these thresholds with the theoretical density profiles expected for self-interacting dark matter (SIDM) spikes.

Future surveys such as the Legacy Survey of Space and Time (LSST) of the Vera C. Rubin Observatory will observe an order of magnitude more astrophysical transient events than any previous survey before. With this deluge of photometric data, it will be impossible for all such events to be classified by humans alone. Recent efforts have sought to leverage machine learning methods to tackle the challenge of astronomical transient classification, with ever improving success. Transformers are a recently developed deep learning architecture, first proposed for natural language processing, that have shown a great deal of recent success. In this work we develop a new transformer architecture, which uses multi-head self attention at its core, for general multi-variate time-series data. Furthermore, the proposed time-series transformer architecture supports the inclusion of an arbitrary number of additional features, while also offering interpretability. We apply the time-series transformer to the task of photometric classification, minimising the reliance of expert domain knowledge for feature selection, while achieving results comparable to state-of-the-art photometric classification methods. We achieve a logarithmic-loss of 0.507 on imbalanced data in a representative setting using data from the Photometric LSST Astronomical Time-Series Classification Challenge (PLAsTiCC). Moreover, we achieve a micro-averaged receiver operating characteristic area under curve of 0.98 and micro-averaged precision-recall area under curve of 0.87.

We present the requirements, design and evaluation of the cryogenic continuously rotating half-wave plate (CHWP) for the Simons Observatory (SO). SO is a cosmic microwave background (CMB) polarization experiment at Parque Astron\'{o}mico Atacama in northern Chile that covers a wide range of angular scales using both small (0.42 m) and large (6 m) aperture telescopes. In particular, the small aperture telescopes (SATs) focus on large angular scales for primordial B-mode polarization. To this end, the SATs employ a CHWP to modulate the polarization of the incident light at 8 Hz, suppressing atmospheric 1/f noise and mitigating systematic uncertainties that would otherwise arise due to the differential response of detectors sensitive to orthogonal polarizations. The CHWP consists of a 505 mm diameter achromatic sapphire HWP and a cryogenic rotation mechanism, both of which are cooled down to sim50 K to reduce detector thermal loading. Under normal operation the HWP is suspended by a superconducting magnetic bearing and rotates with a constant 2 Hz frequency, controlled by an electromagnetic synchronous motor. We find that the number of superconductors and magnets that make up the superconducting magnetic bearing are important design parameters, especially for the rotation mechanism's vibration performance. The rotation angle is detected through an angular encoder with a noise level of 0.07 muradmathrm{s}. During a cooldown, the rotor is held in place by a grip-and-release mechanism that serves as both an alignment device and a thermal path. In this paper we provide an overview of the SO SAT CHWP: its requirements, hardware design, and laboratory performance.

Kilonovae are key to advancing our understanding of r-process nucleosynthesis. To date, only two kilonovae have been spectroscopically observed, AT 2017gfo and AT 2023vfi. Here, we present an analysis of the James Webb Space Telescope (JWST) spectra obtained +29 and +61 days post-merger for AT 2023vfi (the kilonova associated with GRB 230307A). After re-reducing and photometrically flux-calibrating the data, we empirically model the observed X-ray to mid-infrared continua with a power law and a blackbody, to replicate the non-thermal afterglow and apparent thermal continuum gtrsim 2 , mum. We fit Gaussians to the apparent emission features, obtaining line centroids of 20218_{-38}^{+37}, 21874 pm 89 and 44168_{-152}^{+153}\,\AA, and velocity widths spanning 0.057 - 0.110\,c. These line centroid constraints facilitated a detailed forbidden line identification search, from which we shortlist a number of r-process species spanning all three r-process peaks. We rule out Ba II and Ra II as candidates and propose Te I-III, Er I-III and W III as the most promising ions for further investigation, as they plausibly produce multiple emission features from one (W III) or multiple (Te I-III, Er I-III) ion stages. We compare to the spectra of AT 2017gfo, which also exhibit prominent emission at sim 2.1 , mum, and conclude that [Te III] lambda21050 remains the most plausible cause of the observed sim 2.1 , mum emission in both kilonovae. However, the observed line centroids are not consistent between both objects, and they are significantly offset from [Te III] lambda21050. The next strongest [Te III] transition at 29290\,\AA\ is not observed, and we quantify its detectability. Further study is required, with particular emphasis on expanding the available atomic data to enable quantitative non-LTE spectral modelling.

The exact location of the gamma-ray emitting region in blazar jets has long been a matter of debate. However, the location has important implications about the emission processes, geometric and physical parameters of the jet, as well as the nature of interaction of the jet with the interstellar and intergalactic medium. Diverse conclusions have been drawn by various authors based on a variety of methods applied to different data sets of many blazars, e.g., the location is less than 0.1 pc from the central engine within the broad line region (BLR) or a few or tens of pc downstream beyond the dusty torus or at some intermediate distance. Here we use a method, established in a previous work, in which the location of the GeV/optical emission is determined using the ratio of energy dissipated during contemporaneous outbursts at those wave bands. We apply it to a total of 47 multi-wavelength outbursts in 10 blazars. We find that the location of the GeV/optical emission is beyond the BLR for all cases. This result is consistent with other studies, in which the location has been determined for a large sample of blazars. We compare the location determined by our method for several GeV outbursts of multiple blazars to that obtained by other authors using different methods. We find that our results are consistent in such one-to-one comparison in most cases, for which the required data were available.

We present the first high-precision model for the group-scale strong lensing system CASSOWARY 19 (CSWA19), utilising images from the Hubble Space Telescope (HST). Sixteen member galaxies identified via the red-sequence method, and the main halo, all modelled as the dual Pseudo Isothermal Elliptical profile (dPIE), are incorporated into a parametric lens model alongside an external shear field. To model the system, we adopt the PyAutoLens software package, employing a progressive search chain strategy for realizing the transition of source model from multiple S\'ersic profiles to a brightness-adaptive pixelization, which uses 1000 pixels in the source plane to reconstruct the background source corresponding to 177,144 image pixels in the image plane. Our results indicate that the total mass within the Einstein radius is M_{theta_E} approx 1.41times10^{13}M_{odot} and the average slope of the total mass density rho (r)propto r^{-gamma} is gamma=1.33 within the effective radius. This slope is shallower than those measured in galaxies and groups but is closer to those of galaxy clusters. In addition, our approach successfully resolves the two merging galaxies in the background source and yields a total magnification of mu=103.18^{+0.23}_{-0.19}, which is significantly higher than the outcomes from previous studies of CSWA19. In summary, our research demonstrates the effectiveness of the brightness-adaptive pixelization source reconstruction technique for modelling group-scale strong lensing systems. It can serve as a technical reference for future investigations into pixel-level modelling of the group- and cluster-scale strong lensing systems.

We present new observations from JWST NIRCam that reveal a striking kpc-wide cavity in the stellar distribution of the central galaxy in the cluster Abell402. Supporting data from HST allow us to rule out extinction due to dust as an explanation and, instead, suggest that this is a localized depression in the stellar density field corresponding to ~2x10^9 Msun in missing stars within a volume of 0.5kpc^3. On larger scales, both the JWST and HST data show evidence for a 2.2kpc flattened core in the stellar distribution (on which the smaller-scale cavity is superimposed), which implies the presence of a central ultra-massive black hole with M_BH = 6 +/- 4 x10^10 Msun. We report evidence for a mid-IR-bright point source at one edge of the cavity, suggesting that this black hole is actively accreting. MUSE spectroscopy reveal that this source is a LINER AGN and that there is a second candidate AGN on the opposite side of the cavity with a relative velocity of 370km/s -- if real, this implies the presence of a kpc-separation dual AGN with a total binary mass of 6 +/- 2 x10^10 Msun, which would make this the most massive binary black hole system discovered to date. We propose that this unique stellar cavity is the result of a short-lived dynamical interaction between at least one supermassive black hole and the background stellar density field, caused either by three-body scattering during binary hardening or the induction of a dipole instability in the stellar density field.

The DESI Legacy Imaging Surveys are a combination of three public projects (the Dark Energy Camera Legacy Survey, the Beijing-Arizona Sky Survey, and the Mayall z-band Legacy Survey) that will jointly image approximately 14,000 deg^2 of the extragalactic sky visible from the northern hemisphere in three optical bands (g, r, and z) using telescopes at the Kitt Peak National Observatory and the Cerro Tololo Inter-American Observatory. The combined survey footprint is split into two contiguous areas by the Galactic plane. The optical imaging is conducted using a unique strategy of dynamically adjusting the exposure times and pointing selection during observing that results in a survey of nearly uniform depth. In addition to calibrated images, the project is delivering a catalog, constructed by using a probabilistic inference-based approach to estimate source shapes and brightnesses. The catalog includes photometry from the grz optical bands and from four mid-infrared bands (at 3.4, 4.6, 12 and 22 micorons) observed by the Wide-field Infrared Survey Explorer (WISE) satellite during its full operational lifetime. The project plans two public data releases each year. All the software used to generate the catalogs is also released with the data. This paper provides an overview of the Legacy Surveys project.

We present the results from four stellar occultations by (486958) Arrokoth, the flyby target of the New Horizons extended mission. Three of the four efforts led to positive detections of the body, and all constrained the presence of rings and other debris, finding none. Twenty-five mobile stations were deployed for 2017 June 3 and augmented by fixed telescopes. There were no positive detections from this effort. The event on 2017 July 10 was observed by SOFIA with one very short chord. Twenty-four deployed stations on 2017 July 17 resulted in five chords that clearly showed a complicated shape consistent with a contact binary with rough dimensions of 20 by 30 km for the overall outline. A visible albedo of 10% was derived from these data. Twenty-two systems were deployed for the fourth event on 2018 Aug 4 and resulted in two chords. The combination of the occultation data and the flyby results provides a significant refinement of the rotation period, now estimated to be 15.9380 pm 0.0005 hours. The occultation data also provided high-precision astrometric constraints on the position of the object that were crucial for supporting the navigation for the New Horizons flyby. This work demonstrates an effective method for obtaining detailed size and shape information and probing for rings and dust on distant Kuiper Belt objects as well as being an important source of positional data that can aid in spacecraft navigation that is particularly useful for small and distant bodies.

Blazars, a class of active galactic nuclei (AGN) powered by supermassive black holes, are known for their remarkable variability across multiple timescales and wavelengths. With advancements in both ground- and space-based telescopes, our understanding of AGN central engines has significantly improved. However, the mechanisms driving this variability remain elusive, and continue to fascinate both theorists and observers alike. The primary objective of this study is to constrain the X-ray variability properties of the TeV blazar PKS 2155-304. We conduct a comprehensive X-ray spectral and timing analysis, focusing on both long-term and intra-day variability. This analysis uses data from 22 epochs of XMM-Newton EPIC-pn observations, collected over 15 years (2000-2014). To investigate the variability of the source, we applied both timing and spectral analyses. For the timing analysis, we estimated fractional variability, variability amplitude, minimum variability timescales, flux distribution, and power spectral density (PSD). In the spectral analysis, we fitted the X-ray spectra using power-law, log-parabola, and broken power-law (BPL) models to determine the best-fitting parameters. Additionally, we studied the hardness ratio (HR). We observed moderate intra-day variability in most of the light curves. Seven out of the twenty-two observations showed a clear bimodal flux distribution, indicating the presence of two distinct flux states. Our analysis revealed a variable power-law PSD slope. Most HR plots did not show significant variation with flux, except for one observation (OBSID 0124930501), where HR increased with flux (Count/s). The fitted X-ray spectra favored the BPL model for the majority of observations. The findings of this work shed light on the intraday variability of blazars, providing insights into the non-thermal jet processes that drive the observed flux variations.

Inflation typically predicts a quasi scale-invariant spectrum of gravitational waves. In models of slow-roll inflation, the amplitude of such a background is too small to allow direct detection without a dedicated space-based experiment such as the proposed BBO or DECIGO. In this paper we note that particle production during inflation can generate a feature in the spectrum of primordial gravitational waves. We discuss the possibility that such a feature might be detected by ground-based laser interferometers such as Advanced LIGO and Advanced Virgo, which will become operational in the next few years. We also discuss the prospects of detection by a space interferometer like LISA. We first study gravitational waves induced by nonperturbative, explosive particle production during inflation: while explosive production of scalar quanta does not generate a significant bump in the primordial tensor spectrum, production of vectors can. We also show that chiral gravitational waves produced by electromagnetic fields amplified by an axion-like inflaton could be detectable by Advanced LIGO.

We propose a simple modification of space-based gravitational wave (GW) detector optical benches which would enable the measurement of vacuum birefringence of light induced by axion dark matterthrough its coupling to electromagnetism. Specifically, we propose to change a half-wave plate by a circular polarizer. While marginally affecting the sensitivity to GW by a factor 2, we show that such an adjustment would make future detectors such as LISA, TianQin, Taiji and Big-Bang Observer the most sensitive experiments at low axion masses

As ground-based all-sky astronomical surveys will gather millions of images in the coming years, a critical requirement emerges for the development of fast deconvolution algorithms capable of efficiently improving the spatial resolution of these images. By successfully recovering clean and high-resolution images from these surveys, the objective is to deepen the understanding of galaxy formation and evolution through accurate photometric measurements. We introduce a two-step deconvolution framework using a Swin Transformer architecture. Our study reveals that the deep learning-based solution introduces a bias, constraining the scope of scientific analysis. To address this limitation, we propose a novel third step relying on the active coefficients in the sparsity wavelet framework. We conducted a performance comparison between our deep learning-based method and Firedec, a classical deconvolution algorithm, based on an analysis of a subset of the EDisCS cluster samples. We demonstrate the advantage of our method in terms of resolution recovery, generalisation to different noise properties, and computational efficiency. The analysis of this cluster sample not only allowed us to assess the efficiency of our method, but it also enabled us to quantify the number of clumps within these galaxies in relation to their disc colour. This robust technique that we propose holds promise for identifying structures in the distant universe through ground-based images.

The X-ray polarization observations made possible with the Imaging X-ray Polarimetry Explorer (IXPE) offer new ways of probing high-energy emission processes in astrophysical jets from blazars. Here we report on the first X-ray polarization observation of the blazar S4 0954+65 in a high optical and X-ray state. During our multi-wavelength campaign on the source, we detected an optical flare whose peak coincided with the peak of an X-ray flare. This optical-X-ray flare most likely took place in a feature moving along the parsec-scale jet, imaged at 43 GHz by the Very Long Baseline Array. The 43 GHz polarization angle of the moving component underwent a rotation near the time of the flare. In the optical band, prior to the IXPE observation, we measured the polarization angle to be aligned with the jet axis. In contrast, during the optical flare the optical polarization angle was perpendicular to the jet axis; after the flare, it reverted to being parallel to the jet axis. Due to the smooth behavior of the optical polarization angle during the flare, we favor shocks as the main acceleration mechanism. We also infer that the ambient magnetic field lines in the jet were parallel to the jet position angle. The average degree of optical polarization during the IXPE observation was (14.3pm4.1)%. Despite the flare, we only detected an upper limit of 14% (at 3sigma level) on the X-ray polarization degree; although a reasonable assumption on the X-ray polarization angle results in an upper limit of 8.8% (3sigma). We model the spectral energy distribution (SED) and spectral polarization distribution (SPD) of S4 0954+65 with leptonic (synchrotron self-Compton) and hadronic (proton and pair synchrotron) models. The constraints we obtain with our combined multi-wavelength polarization observations and SED modeling tentatively disfavor hadronic models for the X-ray emission in S4 0954+65.

We present new JWST-NIRSpec IFS data for the luminous infrared galaxy NGC7469: a nearby (70.6Mpc) active galaxy with a Sy 1.5 nucleus that drives a highly ionized gas outflow and a prominent nuclear star-forming ring. Using the superb sensitivity and high spatial resolution of the JWST instrument NIRSpec-IFS, we investigate the role of the Seyfert nucleus in the excitation and dynamics of the circumnuclear gas. Our analysis focuses on the [Fe ii], H2, and hydrogen recombination lines that trace the radiation/shocked-excited molecular and ionized ISM around the AGN. We investigate the gas excitation through H2/Br{\gamma} and [Fe ii]/Paeta emission line ratios and find that photoionization by the AGN dominates within the central 300 pc of the galaxy and together with a small region show ing signatures of shock-heated gas; these shock-heated regions are likely associated with a compact radio jet. In addition, the velocity field and velocity dispersion maps reveal complex gas kinematics. Rotation is the dominant feature, but we also identify non-circular motions consistent with gas inflows as traced by the velocity residuals and the spiral pattern in the Pa{\alpha} velocity dispersion map. The inflow is consistent with the mass outflow rate and two orders of magnitude higher than the AGN accretion rate. The compact nuclear radio jet has enough power to drive the highly ionized outflow. This scenario suggests that the inflow and outflow are in a self-regulating feeding-feedback process, with a contribution from the radio jet helping to drive the outflow.

Extreme-mass-ratio inspirals (EMRIs) are one of the primary targets for the recently adopted millihertz gravitational-wave (GW) observatory LISA. Some previous studies have argued that a fraction of all EMRIs form in matter-rich environments, and can potentially explain the dozens of soft X-ray band (sim 10^{-1} rm keV), low-frequency (sim 0.1 mHz) periodic phenomena known as quasi-periodic eruptions (QPEs) and quasi-periodic oscillations (QPOs). Here, using a representative EMRI population retrofitted with cutoffs on LISA-band SNRs and luminosity distances to account for the sensitivity of current instruments, we estimate the mean frequency band in which QPEs and QPOs originating from detectable LISA EMRIs may be emitting an X-ray signal ``today'' (i.e., in 2024) to be 0.46 pm 0.22 mHz. We also model the well-known QPO source, RE J1034+396, which falls in this frequency band, as an EMRI assuming its primary black hole mass to be 10^6-10^7 M_odot. Through a prior-predictive analysis, we estimate the orbiting compact object's mass to be 46^{+ 10}_{-40} M_odot and the source's LISA-band SNR as approx 14, highlighting it as a candidate multi-messenger EMRI target. We also highlight the role of current and near-future X-ray and UV observatories in enabling multi-messenger observations of EMRIs in conjunction with LISA, and conclude with a discussion of caveats of the current analysis, such as the exclusion of eccentricity and inclination from the model, and the measurability of sub-solar mass compact object EMRIs.

Ground deformation is regarded in volcanology as a key precursor signal preceding volcanic eruptions. Satellite-based Interferometric Synthetic Aperture Radar (InSAR) enables consistent, global-scale deformation tracking; however, deep learning methods remain largely unexplored in this domain, mainly due to the lack of a curated machine learning dataset. In this work, we build on the existing Hephaestus dataset, and introduce Hephaestus Minicubes, a global collection of 38 spatiotemporal datacubes offering high resolution, multi-source and multi-temporal information, covering 44 of the world's most active volcanoes over a 7-year period. Each spatiotemporal datacube integrates InSAR products, topographic data, as well as atmospheric variables which are known to introduce signal delays that can mimic ground deformation in InSAR imagery. Furthermore, we provide expert annotations detailing the type, intensity and spatial extent of deformation events, along with rich text descriptions of the observed scenes. Finally, we present a comprehensive benchmark, demonstrating Hephaestus Minicubes' ability to support volcanic unrest monitoring as a multi-modal, multi-temporal classification and semantic segmentation task, establishing strong baselines with state-of-the-art architectures. This work aims to advance machine learning research in volcanic monitoring, contributing to the growing integration of data-driven methods within Earth science applications.

We use the First Light And Reionisation Epoch Simulations (FLARES) to study the evolution of the rest-frame ultraviolet (UV) and far-infrared (FIR) sizes for a statistical sample of massive (gtrsim10^{9}M_{odot}) high redshift galaxies (z in [5,10]). Galaxies are post-processed using the SKIRT radiative transfer code, to self-consistently obtain the full spectral energy distribution and surface brightness distribution. We create mock observations of the galaxies for the Near Infrared Camera (NIRCam) to study the rest-frame UV 1500 xC5 morphology. We also generate mock rest-frame FIR (50 mum) photometry and mock ALMA (158 mum) (0.01"-0.03" and approx0.3" angular resolution) observations to study the dust-continuum. We find the effect of dust on observed sizes reduces with increasing wavelength from the UV to optical (sim0.6 times the UV at 0.4mum), with no evolution in FIR sizes. Observed sizes vary within 0.4-1.2 times the intrinsic sizes at different signal to noise ratios (SNR = 5-20) across redshifts. The effect of PSF and noise makes bright structures prominent, whereas fainter regions blend with noise, leading to an underestimation (factor of 0.4-0.8) of sizes at SNR=5. At SNR=15-20, the underestimation reduces (factor of 0.6-0.9) at z=5-8 but due to PSF, at z=9-10, bright cores are dominant, resulting in an overestimation (factor of 1.0-1.2). For ALMA, low resolution sizes are effected by noise which acts as extended emission. The size evolution in UV broadly agrees with current observational samples and other simulations. This work is one of the first to analyse the panchromatic sizes of a statistically significant sample of simulated high-redshift galaxies, complementing a growing body of research highlighting the importance of conducting an equivalent comparison between observed galaxies and their simulated counterparts in the early Universe.

We present a multi-modal foundation model for astrophysical galaxy data, designed to map between simulation- and observation-based galactic features. Our encoder-only transformer flexibly ingests scalar quantities (e.g., redshifts, galaxy masses) and vectors (e.g., star formation histories, spectra), supporting multi-task training that includes within-modality reconstruction and cross-modality prediction. With a dynamic masking strategy, the model can query arbitrary galaxy properties from partial inputs -- including predicting spectra from redshift and mass, or estimating photometric redshifts from broadband magnitudes -- while also recovering missing segments within a modality. Trained on 185,000 simulated galaxies from a gigaparsec-scale Cosmology simulation, the model yields a 50% improvement in redshift estimation when combining LSST and SPHEREx photometry over LSST photometry alone, and a 63% improvement in stellar mass inference when combining late-time SFH with LSST photometry over early-time SFH with LSST photometry. The model demonstrates strong generalization across multi-modal tasks and lays the groundwork for future integration of higher-dimensional and structured data such as images, merger trees, and 3D fields. This approach provides a unified framework for connecting simulations and observations, advancing the development of generalizable astrophysical foundation models.

The PRObabilistic Value-Added Bright Galaxy Survey (PROVABGS) catalog will provide measurements of galaxy properties, such as stellar mass (M_*), star formation rate ({rm SFR}), stellar metallicity (Z_{rm MW}), and stellar age (t_{rm age, MW}), for >10 million galaxies of the DESI Bright Galaxy Survey. Full posterior distributions of the galaxy properties will be inferred using state-of-the-art Bayesian spectral energy distribution (SED) modeling of DESI spectroscopy and Legacy Surveys photometry. In this work, we present the SED model, Bayesian inference framework, and methodology of PROVABGS. Furthermore, we apply the PROVABGS SED modeling on realistic synthetic DESI spectra and photometry, constructed using the L-GALAXIES semi-analytic model. We compare the inferred galaxy properties to the true galaxy properties of the simulation using a hierarchical Bayesian framework to quantify accuracy and precision. Overall, we accurately infer the true M_*, {rm SFR}, Z_{rm MW}, and t_{rm age, MW} of the simulated galaxies. However, the priors on galaxy properties induced by the SED model have a significant impact on the posteriors. They impose a {rm SFR}{>}10^{-1} M_odot/{rm yr} lower bound on {rm SFR}, a {sim}0.3 dex bias on log Z_{rm MW} for galaxies with low spectral signal-to-noise, and t_{rm age, MW} < 8,{rm Gyr} upper bound on stellar age. This work also demonstrates that a joint analysis of spectra and photometry significantly improves the constraints on galaxy properties over photometry alone and is necessary to mitigate the impact of the priors. With the methodology presented and validated in this work, PROVABGS will maximize information extracted from DESI observations and provide a probabilistic value-added galaxy catalog that will extend current galaxy studies to new regimes and unlock cutting-edge probabilistic analyses.