arXiv subjects

John Schneider

Publications and source records attributed to John Schneider.

3 recordsLinked to original sources

arXiv2026

GATOS XV: A JWST/MIRI survey of extended circumnuclear dust emission in nearby Seyfert galaxies

The subarcsecond angular resolution and stable background of JWST has given us the first high-fidelity images of the arcsecond-scale environment around Active Galactic Nuclei (AGNs) in the nearby Universe. With mid-infrared (MIR) surface brightness sensitivities that are much deeper than the best ground-based instruments, the Mid-InfraRed Instrument imager (MIRIM) now allows us to understand the structure and thermal properties of dust using information over wavelengths of $5$-$25$ $μ$m, almost all of the MIR range. We present a Cycle 1 JWST MIRIM survey of Seyfert galaxies with the express aim of characterising AGN-heated dust in the central few 100 pcs, and searching for signatures of dust-laden nuclear outflows. This paper outlines the motivation behind the programme, the data reduction and analysis techniques used to isolate the nuclear and extended emission, and a comparison of the observed MIR structures with those seen in other phases (stars, ionised and molecular gas, absorbing dust). In concert with earlier studies that used these data, we conclude that resolved AGN-heated dust is widespread in the Seyfert population, extending out to a few hundred pcs from the nucleus and often displaying a higher surface-brightness compared to the more widespread star-forming dusty circumnuclear disk. Even after accounting for contamination from emission lines in the MIRI filters, we find strong spatial correlations between MIR dust emission and the AGN-ionised gas in the narrow-line region (NLR).

astro-ph.GA↗

arXiv2026

GATOS XI : Excess dust heating in the Narrow Line Regions of nearby AGN revealed with JWST/MIRI

We present JWST/MIRI imaging of eight nearby Active Galactic Nuclei (AGN) from the GATOS survey to investigate the physical conditions of extended dust in their narrow line regions (NLRs). In four galaxies (ESO 428-G14, NGC 4388, NGC 3081, and NGC 5728), we detect spatially resolved dust structures extending ~100-200 pc along the NLR. In these systems, we find a strong link between the morphology of the dust, the radio ejecta, and the coronal [Si VI] emission, implying that dust carries imprints of the processes shaping the NLR. Using spatially resolved spectral energy distributions, we show that dust in the NLR has systematically steeper slopes than star forming clumps. This dust emits at temperatures in the range 150 - 220 K, at a distance of ~150 pc from the nucleus. Using simple models, we show that, even under optimistic assumptions of grain size and AGN luminosity, the excess MIR emission cannot be explained by AGN illumination alone. We interpret this excess heating as in-situ. We show that shocks with velocities of $v_{\rm shock} \sim 200- 400 \, \rm km/s$ in dense gas can close this gap, and in some cases even account for the total observed emission. This, combined with multiple lines of evidence for shocks in these regions, supports a scenario in which shocks not only coexist with dust but may be playing a key role in heating it. Our findings reveal shocks may be an important and previously overlooked driver of extended dust emission in the central hundreds of parsecs in AGN.

astro-ph.GA↗

arXiv2020

A Machine Learning System for Retaining Patients in HIV Care

Retaining persons living with HIV (PLWH) in medical care is paramount to preventing new transmissions of the virus and allowing PLWH to live normal and healthy lifespans. Maintaining regular appointments with an HIV provider and taking medication daily for a lifetime is exceedingly difficult. 51% of PLWH are non-adherent with their medications and eventually drop out of medical care. Current methods of re-linking individuals to care are reactive (after a patient has dropped-out) and hence not very effective. We describe our system to predict who is most at risk to drop-out-of-care for use by the University of Chicago HIV clinic and the Chicago Department of Public Health. Models were selected based on their predictive performance under resource constraints, stability over time, as well as fairness. Our system is applicable as a point-of-care system in a clinical setting as well as a batch prediction system to support regular interventions at the city level. Our model performs 3x better than the baseline for the clinical model and 2.3x better than baseline for the city-wide model. The code has been released on github and we hope this methodology, particularly our focus on fairness, will be adopted by other clinics and public health agencies in order to curb the HIV epidemic.

cs.CY↗