We present radial profiles of surface brightness in UV and IR bands, estimate stellar mass surface density ($\Sigma_\star$) and star formation rate surface density ($\Sigma_\mathrm{SFR}$), and predict the CO-to-H$_2$ conversion factor ($\alpha_\mathrm{CO}$) for over 5,000 local galaxies with stellar mass $M_\star\,{\geq}\,10^{9.3}\rm\,M_\odot$. We build these profiles and measure galaxy half-light radii using GALEX and WISE images from the $z$0MGS program, with special care given to highly inclined galaxies. From the UV and IR surface brightness profiles, we estimate $\Sigma_\star$ and $\Sigma_\mathrm{SFR}$ and use them to predict $\alpha_\mathrm{CO}$ with state-of-the-art empirical prescriptions. We validate our (kpc-scale) $\alpha_\mathrm{CO}$ predictions against observational estimates, finding the best agreement when accounting for CO-dark gas as well as CO emissivity and excitation effects. The CO-dark correction plays a primary role in lower-mass galaxies, whereas CO emissivity and excitation effects become more important in higher-mass and more actively star-forming galaxies, respectively. We compare our estimated $\alpha_\mathrm{CO}$ to observed galaxy-integrated SFR to CO luminosity ratio as a function of $M_\star$. A large compilation of literature data suggests that star-forming galaxies with $M_\star = 10^{9.5{-}11}\,M_\odot$ show strong anti-correlations of SFR/$L^\prime_\mathrm{CO(1{-}0)} \propto M_\star^{-0.29}$ and SFR/$L^\prime_\mathrm{CO(2{-}1)} \propto M_\star^{-0.40}$. The estimated $\alpha_\mathrm{CO}$ trends, when combined with a constant molecular gas depletion time $t_\mathrm{dep}$, can only explain ${\approx}1/3$ of these SFR/$L^\prime_\mathrm{CO}$ trends. This suggests that $t_\mathrm{dep}$ being systematically shorter in lower-mass star-forming galaxies is the main cause of the observed SFR/$L^\prime_\mathrm{CO}$ variations. (Abridged)
The fate of hot Jupiters is thought to be engulfment by their host stars, the outcome of tidal orbital decay. Transit timing has revealed a few systems with apparently shrinking orbital periods, but such signals can be mimicked by light travel-time effects (LTTE) of a distant companion. Combining transit timings with precise radial-velocity data, including new data, we reassessed three reported cases of orbital decay: WASP-4, WASP-12, and Kepler-1658. For WASP-4, the period change is best explained by LTTE due to a 10-Jupiter-mass companion at 4 AU, with no need to invoke orbital decay. For WASP-12, in contrast, the data firmly exclude LTTE and confirm genuine orbital decay. For Kepler-1658, spectroscopic and photometric anomalies reveal the "planet" to be an eclipsing K/M binary bound to the F-type primary, with LTTE explaining the observed period change. Thus, among the known hot Jupiters, only WASP-12 b currently shows compelling evidence for orbital decay.
The black-hole occupation fraction ($f_\mathrm{occ}$) defines the fraction of galaxies that harbor central massive black holes (MBHs), irrespective of their accretion activity level. While it is widely accepted that $f_\mathrm{occ}$ is nearly 100% in local massive galaxies with stellar masses $M_\star \gtrsim 10^{10}~M_\odot$, it is not yet clear whether MBHs are ubiquitous in less-massive galaxies. In this work, we present new constraints on $f_\mathrm{occ}$ based on over 20 years of Chandra imaging data for 1606 galaxies within 50 Mpc. We employ a Bayesian model to simultaneously constrain $f_\mathrm{occ}$ and the specific accretion-rate distribution function, $p(\lambda)$, where the specific accretion rate is defined as $\lambda=L_\mathrm{X}/M_\star$, and $L_\mathrm{X}$ is the MBH accretion luminosity in the 2-10 keV range. Notably, we find that $p(\lambda)$ peaks around $10^{28}~\mathrm{erg~s^{-1}}~M_\odot^{-1}$; above this value, $p(\lambda)$ decreases with increasing $\lambda$, following a power-law that smoothly connects with the probability distribution of bona-fide active galactic nuclei. We also find that the occupation fraction decreases dramatically with decreasing $M_\star$: in high mass galaxies ($M_\star \approx 10^{11-12}M_\odot$), the occupation fraction is $>93\%$ (a $2\sigma$ lower limit), and then declines to $66_{-7}^{+8}\%$ ($1\sigma$ errors) between $M_\star\approx10^{9-10}M_\odot$, and to $33_{-9}^{+13}\%$ in the dwarf galaxy regime between $M_\star\approx10^{8-9}~M_\odot$. Our results have significant implications for the normalization of the MBH mass function over the mass range most relevant for tidal disruption events, extreme mass ratio inspirals, and MBH merger rates that upcoming facilities are poised to explore.
We utilize a large sample of $\sim$113,000 galaxies ($z < 0.3$) from the Sloan Digital Sky Survey with high-quality data to compare star formation rates (SFRs) across multiple diagnostic methods and examine their connection to Active Galactic Nuclei (AGNs) strength, indicated by Eddington ratio. Our sample encompassed star-forming (SF), composite, Seyfert, and LINER galaxies. Our analysis utilizes various SFRs indicators, including observed infrared flux ($\rm SFR_{FIR}$) from AKARI/Herschel ($\sim$4,100 sources), the MPA-JHU catalog ($\rm SFR_{Dn4000}$), the ANN catalog ($\rm SFR_{ANN}$), the GSWLC catalog ($\rm SFR_{SED}$ and $\rm SFR_{MIR}$), as well as \OII\ and \Ha\ emission lines ($\rm SFR_{[OII]}$ and $\rm SFR_{H\alpha}$). Within SF galaxies, SFRs measurements from different tracers exhibited differences, with offsets and scatter below 0.26 dex and 0.29 dex, respectively. Moreover, non-SF galaxies (composite, Seyfert, and LINER) displayed discrepancies among SFR tracers, particularly for LINER galaxies, with offsets below 0.86 dex and a scatter of 0.57 dex. Additionally, our findings revealed robust correlations between SFRs and specific SFRs (sSFRs) with Eddington ratios. Eddington ratio exhibited gradual transitions in the (s)SFRs-stellar mass diagrams. Galaxies with high Eddington ratios displayed high star formation activity, similar to blue SF galaxies. Furthermore, we observed decreasing sSFR trends from SF galaxies to composite, Seyfert, and LINER galaxies. Our results may provide insight into our understanding of (s)SFRs traced by different approaches and their connection to AGN activities.
Star clusters host the massive stars responsible for feedback in star-forming galaxies. Stellar feedback shapes the interstellar medium (ISM), affecting the formation of future star clusters. To self-consistently capture the interplay between feedback and star formation, a model must resolve the parsec-scale star formation sites and the multiphase ISM. Additionally, the dynamical impact of cosmic rays (CRs) on star formation rates (SFRs) must also be considered. We present the first simulations of the formation of an ensemble of star clusters with dynamically-coupled CRs, near-individual star particles, and a feedback-regulated ISM. We analyze tallbox simulations performed using the CRISP model in the moving-mesh code AREPO. We apply varied implementations of CR transport under the theory of self-confinement. We find that CRs simultaneously reduce the SFR, the power law slope of the cluster mass function, and the cluster formation efficiency. Each simulation is compatible with observations, and CR feedback tends to move results along observed star cluster relations. We see only modest changes in cluster radius and velocity dispersions, but significant differences in the virial parameters. Ultimately, the primary impact of CRs is to reduce SFRs. Lower SFRs imply fewer supernovae, and consequently a lower turbulent energy budget for gas. Star clusters formed in a CR-regulated ISM have lower velocity dispersions, and are therefore more bound under self-gravity. The effective clustering of SNe is unchanged by CRs. Through this work, we demonstrate the predictive power of the CRISP feedback model, despite this idealized setup.
Time series foundation models (TSFMs) are increasingly being adopted as highly-capable general-purpose time series representation learners. Although their training corpora are vast, they exclude astronomical time series data. Observations of stars produce peta-scale time series with unique challenges including irregular sampling and heteroskedasticity. We introduce StarEmbed, the first public benchmark for rigorous and standardized evaluation of state-of-the-art TSFMs on stellar time series observations (``light curves''). We benchmark on three scientifically-motivated downstream tasks: unsupervised clustering, supervised classification, and out-of-distribution source detection. StarEmbed integrates a catalog of expert-vetted labels with multi-variate light curves from the Zwicky Transient Facility, yielding ~40k hand-labeled light curves spread across seven astrophysical classes. We evaluate the zero-shot representation capabilities of three TSFMs (MOIRAI, Chronos, Chronos-Bolt) and a domain-specific transformer (Astromer) against handcrafted feature extraction, the long-standing baseline in the astrophysics literature. Our results demonstrate that these TSFMs, especially the Chronos models, which are trained on data completely unlike the astronomical observations, can outperform established astrophysics-specific baselines in some tasks and effectively generalize to entirely new data. In particular, TSFMs deliver state-of-the-art performance on our out-of-distribution source detection benchmark. With the first benchmark of TSFMs on astronomical time series data, we test the limits of their generalization and motivate a paradigm shift in time-domain astronomy from using task-specific, fully supervised pipelines toward adopting generic foundation model representations for the analysis of peta-scale datasets from forthcoming observatories.
arXiv:2508.03800 (accepted to ApJ) with 2 Appendices, 6 figures, 2 tables (21 pages total)