Galaxy formation and evolution

Abstract:

We present observational evidence that intense ionizing radiation from a luminous quasar suppresses nebular emission in nearby galaxies on intergalactic scales at z = 6.3. Using JWST/NIRCam grism spectroscopy from the Slitless Areal Pure-Parallel High-Redshift Emission survey and Emission-line galaxies and Intergalactic Gas in the Epoch of Reionization programs, we identify a moderate but statistically significant decline in [O iii] λ5008 luminosity relative to the UV continuum (L5008/L1500) among galaxies within ∼7 comoving Mpc (cMpc) of the quasar J0100+2802, the most UV-luminous quasar known at this epoch (M1450 = −29.26). While L1500 remains roughly constant with transverse distance, L5008 increases significantly, suggesting suppression of very recent star formation toward the quasar. The effect persists after controlling for completeness, local density, and UV luminosity, and correlates with the projected photoionization-rate profile Γqso. A weaker but directionally consistent suppression in L5008/L1500 is also observed along the line of sight. The transverse suppression radius (∼7 cMpc) implies a recent radiative episode with a cumulative duration ∼3.1 Myr, shorter than required for thermal photoheating to dominate and thus more naturally explained by rapid H2 photodissociation and related radiative processes. Environmental effects alone appear insufficient to explain the signal. Our results provide direct, geometry-based constraints on large-scale quasar radiative feedback and recent quasar lifetimes.

Abstract:

Radiation pressure on spectral lines is a promising mechanism for powering disc winds from accreting white dwarfs (AWDs) and active galactic nuclei (AGNs). However, in radiation-hydrodynamic simulations, overionization reduces line opacity and quenches the line force, which suppresses outflows. Here, we show that small-scale clumping can resolve this problem. Adopting the microclumping approximation, our new simulations demonstrate that even modest volume filling factors () can dramatically increase the wind mass-loss rate by lowering its ionization state – raising and yielding for such modest filling factors. Clumpy wind models produce the UV resonance lines that are absent from smooth wind models. They can also reprocess a significant fraction of the disc luminosity and thus dramatically modify the broad-band optical/UV SED. Given that theory and observations indicate that disc winds are intrinsically inhomogeneous, clumping offers a physically motivated solution. Together, these results provide the first robust, self-consistent demonstration that clumping can reconcile line-driven wind theory with observations across AWDs and AGNs.

Abstract:

High-resolution JWST images of nearby spiral galaxies reveal polycyclic aromatic hydrocarbon (PAH) structures that potentially trace molecular clouds, even CO-dark regions. For this paper, we identified ISM cloud structures in PHANGS-JWST 7.7μm PAH emission maps for 66 galaxies, smoothed to a common physical resolution of 30 pc and at native resolution. We extracted 108,466 cloud structures in the 30 pc sample and 146,040 clouds in the native resolution sample. We then calculated their molecular properties following a linear conversion from PAH to CO. Given the tendency for clouds in galaxy centers to overlap in velocity space, we opted to flag these clouds and omit them from the analysis in this work. The remaining clouds correspond to giant molecular clouds, such as those detected in CO(2-1) emission by ALMA, or lower surface density clouds that either fall below the ALMA detection limits of existing maps or genuinely have no molecular counterpart. We specifically used the homogenized sample for our analysis. Upon cross-matching the PAH clouds to the ALMA CO clouds at a homogenized resolution of 90 pc in 27 galaxies, we find that 41 $%$ of the PAH clouds are associated with a CO counterpart. We also show that the converted molecular cloud properties of the PAH clouds do not differ much when compared in different galactic environments. However, outside the central environment, the highest molecular mass surface density clouds are preferentially found in spiral arms. We further apply a lognormal fit to the mass spectra to an unprecedented extragalactic completeness limit of 2 , 10^ 3 , and find that spiral arms contain the most massive clouds compared to other galactic environments. Our findings support the idea that spiral arm gravitational potentials foster the formation of high surface density clouds, and that lower surface density clouds form in the interarm regions. The cloud values show a decline of a factor of ∼ 1.5-2 toward the outer 2-3 R_e. However, the trend largely varies in individual galaxies, with flat, decreasing, and even no trend as a function of R_̊m gal. Factors such as large-scale processes, galaxy types, and morphologies might influence the observed trends. We note that combining homogenized molecular properties of individual galaxies leads to the loss of information about the physical processes that are driving deviations in trends of those properties across different galactic environments. We published two catalogs at the CDS, one at the common resolution of 30 pc and another at the native resolution. We expect them to have broad utility for future studies of PAH clouds, molecular clouds, and star formation.

Abstract:

We introduce a neural approach to dynamical modeling of galaxies that replaces traditional imaging-based deprojections with a differentiable mapping. Specifically, we train a neural network to translate Nuker profile parameters into analytically deprojectable Multi Gaussian Expansion components, enabling physically realistic stellar mass models without requiring optical observations. We integrate this model into SuperMAGE, a differentiable dynamical modelling pipeline for Bayesian inference of supermassive black hole masses. Applied to ALMA data, our approach finds results consistent with state-of-the-art models while extending applicability to dust-obscured and active galaxies where optical data analysis is challenging.