arXiv subjects

Stephanie Campbell

Publications and source records attributed to Stephanie Campbell.

4 recordsLinked to original sources

arXiv2024

Dust beyond the torus: Revealing the mid-infrared heart of local Seyfert ESO 428-G14 with JWST/MIRI

Polar dust has been discovered in a number of local Active Galactic Nuclei (AGN), with radiation-driven torus models predicting a wind to be its main driver. However, little is known about its characteristics, spatial extent, or connection to the larger scale outflows. We present the first JWST/MIRI study aimed at imaging polar dust by zooming onto the centre of ESO 428-G14, part of the Galaxy Activity, Torus, and Outflow Survey (GATOS) survey of local AGN. We detect extended mid-infrared (MIR) emission within 200 pc from the nucleus. This polar structure is co-linear with a radio jet and lies perpendicular to a molecular gas lane that feeds and obscures the nucleus. Its morphology bears a striking resemblance to that of gas ionised by the AGN in the narrow-line region. We demonstrate that part of this spatial correspondence is due to contamination within the JWST filter bands from strong emission lines. Correcting for the contamination, we find the morphology of the dust continuum to be more compact, though still clearly extended out to ~ 100 pc. We estimate the emitting dust has a temperature of ~ 120 K. Using simple models, we find that the heating of small dust grains by the radiation from the central AGN and/or radiative jet-induced shocks is responsible for the extended MIR emission. Radiation-driven dusty winds from the torus is unlikely to be important. This has important implications for scales to which AGN winds can carry dust and dense gas out into their host galaxies.

astro-ph.GA↗

arXiv2024

The Strength of Bisymmetric Modes in SDSS-IV/MaNGA Barred Galaxy Kinematics

The SDSS-IV/MaNGA Survey data provide an unprecedented opportunity to study the internal motions of galaxies and, in particular, represent the largest sample of barred galaxy kinematic maps obtained to date. We present results from Nirvana, our non-axisymmetric kinematic modeling code built with a physically-motivated Bayesian forward modeling approach, which decomposes MaNGA velocity fields into first- and second-order radial and tangential rotational modes in a generalized and minimally-supervised fashion. We use Nirvana to produce models and rotation curves for 1263 unique barred MaNGA galaxies and a matched unbarred control sample We present our modeling approach, tests of its efficacy, and validation against existing visual bar classifications. Nirvana finds elevated non-circular motions in galaxies identified as bars in imaging, and bar position angles that agree well with visual measurements. The Nirvana-MaNGA barred and control samples provide a new opportunity for studying the influence of non-axisymmetric internal disk kinematics in a large statistical sample.

astro-ph.GA↗

arXiv2022

The Seventeenth Data Release of the Sloan Digital Sky Surveys: Complete Release of MaNGA, MaStar and APOGEE-2 Data

This paper documents the seventeenth data release (DR17) from the Sloan Digital Sky Surveys; the fifth and final release from the fourth phase (SDSS-IV). DR17 contains the complete release of the Mapping Nearby Galaxies at Apache Point Observatory (MaNGA) survey, which reached its goal of surveying over 10,000 nearby galaxies. The complete release of the MaNGA Stellar Library (MaStar) accompanies this data, providing observations of almost 30,000 stars through the MaNGA instrument during bright time. DR17 also contains the complete release of the Apache Point Observatory Galactic Evolution Experiment 2 (APOGEE-2) survey which publicly releases infra-red spectra of over 650,000 stars. The main sample from the Extended Baryon Oscillation Spectroscopic Survey (eBOSS), as well as the sub-survey Time Domain Spectroscopic Survey (TDSS) data were fully released in DR16. New single-fiber optical spectroscopy released in DR17 is from the SPectroscipic IDentification of ERosita Survey (SPIDERS) sub-survey and the eBOSS-RM program. Along with the primary data sets, DR17 includes 25 new or updated Value Added Catalogs (VACs). This paper concludes the release of SDSS-IV survey data. SDSS continues into its fifth phase with observations already underway for the Milky Way Mapper (MWM), Local Volume Mapper (LVM) and Black Hole Mapper (BHM) surveys.

astro-ph.GA↗

arXiv2021

Evidence of wind signatures in the gas velocity profiles of Red Geysers

Spatially resolved spectroscopy from SDSS-IV MaNGA survey has revealed a class of quiescent, relatively common early-type galaxies, termed "red geysers", that possibly host large scale active galactic nuclei driven winds. Given their potential importance in maintaining low level of star formation at late times, additional evidence confirming that winds are responsible for the red geyser phenomenon is critical. In this work, we present follow-up observations with the Echellette Spectrograph and Imager (ESI) at the Keck telescope of two red geysers (z$<$0.1) using multiple long slit positions to sample different regions of each galaxy. Our ESI data with a spectral resolution (R) $\sim$ 8000 improves upon MaNGA's resolution by a factor of four, allowing us to resolve the ionized gas velocity profiles along the putative wind cone with an instrumental resolution of $\rm σ= 16~km~s^{-1}$. The line profiles of H$α$ and [NII]$\rm λ6584$ show asymmetric shapes that depend systematically on location $-$ extended blue wings on the red-shifted side of the galaxy and red wings on the opposite side. We construct a simple wind model and show that our results are consistent with geometric projections through an outflowing conical wind oriented at an angle towards the line of sight. An alternative hypothesis that assigns the asymmetric pattern to "beam-smearing" of a rotating, ionized gas disk does a poor job matching the line asymmetry profiles. While our study features just two sources, it lends further support to the notion that red geysers are the result of galaxy-scale winds.

astro-ph.GA↗