The fundamental metallicity relation (FMR) - the three-way trend between galaxy stellar masses, star-formation rates (SFRs) and gaseous metallicities - remains amongst the most studied extragalactic relations. Furthermore, metallicity correlates particularly tightly with gravitational potential. Simulations support a shared origin for these relations relating to long-term gas inflow history variations; however, differences between simulated and observed galaxy samples make it unclear whether this holds for real galaxies. We use MaNGA integral field observations to probe these relations in star-forming galaxies at one effective radius. We confirm the FMR and equivalent relations for stellar metallicity (FMR*) and gaseous N/O (fundamental nitrogen relation, FNR). We find that all relations persist when considering gravitational potential in place of stellar mass and/or considering stellar ages in place of SFR, with the gaseous relations strengthened significantly by considering potential. The gaseous FMR disappears at high masses/potentials, while the FNR persists and the FMR* strengthens. Our results suggest a unified interpretation of galaxies' gaseous and stellar metallicities and their N/O abundances in terms of their formation histories. Deeper gravitational potentials correspond to earlier star-formation histories (SFHs) and faster gas consumption, producing tight potential-abundance relations for stars and gas. In weak potentials, galaxy SFR variations primarily result from recent gas inflows, mostly affecting gas abundances. In deeper potentials, SFR variations instead correspond to broad differences in SFH shapes resulting from differences in long-term gas consumption histories, which is most visible in stellar abundances. This unified interpretation could be confirmed with upcoming higher redshift spectroscopic surveys. less

The interstellar medium (ISM) consists of a multiphase gas, including the warm neutral medium (WNM), the unstable neutral medium (UNM), and the cold neutral medium (CNM). While significant attention has been devoted to understanding the WNM and CNM, the formation of a substantial fraction of the UNM, with temperatures ranging from a few hundred to a few thousand Kelvin, remains less well understood. In this study, we present three-dimensional hydrodynamical and magnetohydrodynamical simulations of turbulent multiphase ISM to investigate the roles of turbulence and magnetic fields in regulating the multiphase ISM. Our results confirm that turbulence is crucial in redistributing energy and producing the UNM. The turbulent mixing effect smooths the phase diagram, flattens the pressure-density relationship, and increases the fraction of gas in the UNM. We find that magnetic fields not only contribute to sustaining the UNM but also influence the dynamics and distribution of gas across all phases. Magnetic fields introduce anisotropy to the turbulent cascade, reducing the efficiency of turbulent mixing in the direction perpendicular to the magnetic field. We find the anisotropy results in a less flat phase diagram compared to hydrodynamical cases. Furthermore, the inclusion of magnetic fields shallowens the second-order velocity structure functions across multiple ISM phases, suggesting that more small-scale fluctuations are driven. These fluctuations contribute to the formation of the UNM by altering the energy cascade and thermodynamic properties of the gas. Our findings suggest that the combined effects of turbulence and magnetic fields are important in regulating the multiphase ISM. less

3D Galactic magnetic fields are critical for understanding the interstellar medium, Galactic foreground polarization, and the propagation of ultra-high-energy cosmic rays. Leveraging recent theoretical insights into anisotropic magnetohydrodynamic (MHD) turbulence, we introduce a deep learning framework to predict the full 3D magnetic field structure-including the plane-of-sky (POS) position angle, line-of-sight (LOS) inclination, magnetic field strength, sonic Mach number ($M_s$), and Alfv\'en Mach number ($M_A$)-from spectroscopic H~I observations. The deep learning model is trained on synthetic H~I emission data generated from multiphase 3D MHD simulations. We then apply the trained model to observational data from the Commensal Radio Astronomy FAST Survey, presenting maps of 3D magnetic field orientation, magnetic field strength, $M_s$, and $M_A$ for two H~I clouds, a low-velocity cloud (LVC) and an intermediate-velocity cloud (IVC), which overlap in the POS yet reside at different LOS distances. The deep-learning-predicted POS magnetic field position angles align closely with those determined using the velocity gradient technique, whose integrated results are consistent with independent measurements from Planck 353~GHz polarization data. This study demonstrates the potential of deep learning approaches as powerful tools for modeling the 3D distributions of 3D Galactic magnetic fields and turbulence properties throughout the Galaxy. less

Context. We present simulations of a massive young star cluster using \textsc{Nbody6++GPU} and \textsc{MOCCA}. The cluster is initially more compact than previously published models, with one million stars, a total mass of $5.86 \times 10^5~\mathrm{M}_{\odot}$, and a half-mass radius of $0.1~\mathrm{pc}$. Aims. We analyse the formation and growth of a very massive star (VMS) through successive stellar collisions and investigate the subsequent formation of an intermediate-mass black hole (IMBH) in the core of a dense star cluster. Methods. We use both direct \textit{N}-body and Monte Carlo simulations, incorporating updated stellar evolution prescriptions (SSE/BSE) tailored to massive stars and VMSs. These include revised treatments of stellar radii, rejuvenation, and mass loss during collisions. While the prescriptions represent reasonable extrapolations into the VMS regime, the internal structure and thermal state of VMSs formed through stellar collisions remain uncertain, and future work may require further refinement. Results. We find that runaway stellar collisions in the cluster core produce a VMS exceeding $5 \times 10^4~\mathrm{M}_{\odot}$ within 5 Myr, which subsequently collapses into an IMBH. Conclusions. Our model suggests that dense stellar environments may enable the formation of very massive stars and massive black hole seeds through runaway stellar collisions. These results provide a potential pathway for early black hole growth in star clusters and offer theoretical context for interpreting recent JWST observations of young, compact clusters at high redshift. less

Dwarf AGN serve as the ideal systems for identifying intermediate mass black holes (IMBHs) down to the most elusive regimes ($\sim 10^3 - 10^4 M_{\odot}$). However, the ubiquitously metal-poor nature of dwarf galaxies gives rise to ultraluminous X-ray sources (ULXs) that can mimic the spectral signatures of IMBH excitation. We present a novel photoionization model suite that simultaneously incorporates IMBHs and ULXs in a metal-poor, highly star-forming environment. We account for changes in $M_{BH}$ according to formation seeding channels and metallicity, and changes in ULX populations with post-starburst age and metallicity. We find that broadband X-rays and UV emission lines are insensitive to $M_{BH}$ and largely unable to distinguish between ULXs and IMBHs. Many optical diagnostic diagrams cannot correctly identify dwarf AGN. The notable exceptions include He~II~$\lambda$4686 and [O~I]~$\lambda$6300, for which we redefine typical demarcations to account for ULX contributions. Emission lines in the mid-IR show the most promise in separating stellar, ULX, IMBH, and shock excitation while presenting sensitivity to $M_{BH}$ and $f_{\text{AGN}}$. Overall, our results expose the potential biases in identifying and characterizing dwarf AGN purely on strong line ratios and diagnostic diagrams rather than holistically evaluating the entire spectrum. As a proof of concept, we argue that recently discovered over-massive BHs in high-$z$ JWST AGN might not represent the overall BH population, with many galaxies in these samples potentially being falsely classified as purely star-forming. less

One of the most profound empirical laws of star formation is the Gao-Solomon relation, a linear correlation between the star formation rate (SFR) and the dense molecular gas mass. It is puzzling how the complicated physics in star-formation results in this surprisingly simple proportionality. Using archival Herschel and Atacama Large Millimeter/submillimeter Array Observations, we derived the masses of the most massive cores ($M^{\rm max}_{\rm core}$) and masses of the gravitationally bound gas ($ M_{\rm gas}^{\rm bound}$) in the parent molecular clouds for a sample of low-mass and high-mass star-forming regions. We discovered a significant correlation $\log(M^{\rm max}_{\rm core}/M_{\odot}) = 0.506 \log(M_{\rm gas}^{\rm bound}/M_{\odot})-0.32$. Our discovered $M^{\rm max}_{\rm core}$-$M_{\rm gas}^{\rm bound}$ correlation can be approximately converted to the Gao-Solomon relation if there is (1) a constant 30% efficiency of converting $M^{\rm max}_{\rm core}$ to the mass of the most massive star ($m^{\rm max}_{\rm star}$), and (2) if SFR and $m^{\rm max}_{\rm star}$ are tightly related through $\log({\rm SFR}/(M_{\odot} {\rm yr}^{-1})) = 2.04 \log(m^{\rm max}_{\rm star}/M_{\odot})-5.80$. Intriguingly, both requirements have been suggested by previous theoretical studies (c.f. Yan et al. 2017). Based on this result, we hypothesize that the Gao-Solomon relation is a consequence of combining the following three non-trivial relations (i) SFR vs. $m^{\rm max}_{\rm star}$, (ii) $m^{\rm max}_{\rm star}$ vs. $M^{\rm max}_{\rm core}$, and (iii) $M^{\rm max}_{\rm core}$ vs. $M_{\rm gas}^{\rm bound}$. This finding may open a new possibility to understand the Gao-Solomon relation in an analytic sense. less

One of the most remarkable results from the \emph{James Webb Space Telescope} has been the discovery of a large population of compact sources exhibiting strong broad H$\alpha$ emission, typically interpreted to be low-luminosity broad-line (Type 1) active galactic nuclei (BLAGN). An important question is whether these observations are in tension with galaxy formation models, and if so how? While comparisons have been made using physical properties (i.e.~black hole mass and accretion rate) inferred from observations, these require the use of SED modelling assumptions, or locally inferred scaling relations, which may be unjustified, at least in the distant high-redshift Universe. In this work we take an alternative approach and forward model predictions from the First Light And Reionisation Epoch Simulations (FLARES) suite of cosmological hydrodynamical zoom simulations to predict the observable properties of BLAGN. We achieve this by first coupling \flares\ with the \qsosed\ model to predict the ionising photon luminosities of high-redshift ($z>5$) AGN. To model the observed broad H$\alpha$ emission we then assume a constant conversion factor and covering fraction, and the fraction of AGN that have observable broad-lines. With a reasonable choice of these parameters, \flares\ is able to reproduce observational constraints on the H$\alpha$ luminosity function and equivalent width distribution at $z=5$. less

Star formation (SF) in the interstellar medium (ISM) is fundamental to understanding galaxy evolution and planet formation. However, efforts to develop closed-form analytic expressions that link SF with key influencing physical variables, such as gas density and turbulence, remain challenging. In this work, we leverage recent advancements in machine learning (ML) and use symbolic regression (SR) techniques to produce the first data-driven, ML-discovered analytic expressions for SF using the publicly available FIRE-2 simulation suites. Employing a pipeline based on training the genetic algorithm of SR from an open software package called PySR, in tandem with a custom loss function and a model selection technique which compares candidate equations to analytic approaches to describing SF, we produce symbolic representations of a predictive model for the star formation rate surface density ($\Sigma_\mathrm{SFR}$) averaged over both 10 Myr and 100 Myr based on eight extracted variables from FIRE-2 galaxies. The resulting model that PySR finds best describes SF, on both averaging timescales, features equations that incorporates the surface density of gas, $\Sigma_\mathrm{gas}$, the velocity dispersion of gas $\sigma_{\mathrm{gas,~z}}$ and the surface density of stars $\Sigma_\mathrm{*}$. Furthermore, we find that the equations found for the longer SFR timescale all converge to a scaling-relation-like equation, all of which also closely capture the intrinsic physical scatter of the data within the Kennicutt-Schmidt (KS) plane. This observed convergence to physically interpretable scaling relations at longer SFR timescales demonstrates that our method successfully identifies robust physical relationships rather than fitting to stochastic fluctuations. less

We present the results of our pipeline for discovering strong gravitational lenses in the ongoing Ultraviolet Near-Infrared Optical Northern Survey (UNIONS). We successfully train the deep residual neural network (ResNet) based on CMU-Deeplens architecture, which is designed to detect strong lenses in ground-based imaging surveys. We train on images of real strong lenses and deploy on a sample of 8 million galaxies in areas with full coverage in the g, r, and i filters, the first multi-band search for strong gravitational lenses in UNIONS. Following human inspection and grading, we report the discovery of a total of 1346 new strong lens candidates of which 146 are grade A, 199 grade B, and 1001 grade C. Of these candidates, 283 have lens-galaxy spectroscopic redshifts from the Sloan Digital Sky Survey (SDSS) and an additional 297 from the Dark Energy Spectroscopic Instrument (DESI) Data Release 1 (DR1). We find 15 of these systems display evidence of both lens and source galaxy redshifts in spectral superposition. We additionally report the spectroscopic confirmation of seven lensed sources in highquality systems, all with z > 2.1, using the Keck Near-Infrared Echelle Spectrograph (NIRES) and Gemini Near-Infrared Spectrograph (GNIRS). less

We dissect the kinematics and morphology of the molecular gas within the near-nuclear region of NGC 1068 to understand the mechanisms in the central AGN that might be fueling it, and the impact of its energy output on the surrounding molecular gas. We present high angular and spectral resolution ALMA observations of the HCO$^+$4->3 and CO 3->2 molecular lines in the near-nuclear region of the prototype Seyfert 2 galaxy NGC 1068. The spatial resolution (1.1~pc) is almost two times better than that of previous works studying the same molecular lines at the same transitions and is the highest resolution achievable with ALMA at these frequencies. Our analysis focuses on moment maps, position-velocity (PV) diagrams, and spectra obtained at the position of the nuclear continuum source, along with a simple kinematic model developed using the 3DBarolo software. Our observations reveal significant asymmetry between the eastern and western sides of the nuclear disc in terms of morphology, velocity, and line intensity. The broad lines seen in the inner 2 pc could be accounted for by either beam smearing or highly turbulent gas in this region. Outside this radius the mean velocities drop to $\pm$30 km/s, which cannot be explained by asymmetric drift. We find low velocity connections extending to 13 pc suggesting interactions with larger scale structures. The CO/HCO$^+$ line ratio at the nucleus reported here are extremely low compared to values in the literature of the same galaxy at lower spatial resolutions. less