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Abstract The Centaurus cluster is one of the most important archetypes of radio-mode active galactic nucleus (AGN) feedback, with its centra… (voir plus)l galaxy, NGC 4696, launching powerful jets that inflate X-ray cavities and regulate cooling and star formation. NGC 4696 lies within a spectacular multiphase nebula of filaments extending over tens of kiloparsecs and spanning 6 decades in temperature, from hot (10 8 K) X-ray-emitting plasma to cold molecular gas. Owing to its proximity, Hubble Space Telescope H α imaging reveals a striking S-shaped ionized-gas swirl within the black hole’s sphere of influence—the first such structure identified in a cluster core. Here we present the first JWST observations of NGC 4696 with NIRSpec, probing the inner 618 × 618 pc at 10 pc resolution. These data reveal that the ionized swirl is a rotating, multiphase circumnuclear disk (CND) physically and kinematically connected to the larger-scale filamentary network. This provides the long-sought missing link between kiloparsec-scale cooling flows and black hole accretion on 100 pc scales. Strikingly, the observed morphology and kinematics are reproduced by tailored magnetohydrodynamic simulations, in which fila
ABSTRACT In astronomy, spectroscopy consists of observing an astrophysical source and extracting its spectrum of electromagnetic radiation. … (voir plus)Once extracted, a model is fit to the spectra to measure the observables, leading to an understanding of the underlying physics of the emission mechanism. One crucial, and often overlooked, aspect of this model is the background emission, which contains foreground and background astrophysical sources, intervening atmospheric emission, and artefacts related to the instrument such as noise. This paper proposes an algorithmic approach to constructing a background model for SITELLE observations using statistical tools and supervised machine learning algorithms. SITELLE is an imaging Fourier transform spectrometer located at the Canada-France-Hawaii Telescope, which produces a three-dimensional data cube containing the position of the emission (two dimensions) and the spectrum of the emission. SITELLE has a wide field of view (11 arcmin × 11 arcmin), which makes the background emission particularly challenging to model. We apply a segmentation algorithm implemented in photutils to divide the data cube into background and source spaxels. After applying a principal component analysis (PCA) on the background spaxels, we train an artificial neural network to interpolate from the background to the source spaxels in the PCA coefficient space, which allows us to generate a local background model over the entire data cube. We highlight the performance of this methodology by applying it to SITELLE observations obtained of a Star-formation, Ionized Gas and Nebular Abundances Legacy Survey galaxy, NGC 4449, and the Perseus galaxy cluster of galaxies, NGC 1275. We discuss the physical interpretation of the principal components and noise reduction in the resulting PCA-based reconstructions. Additionally, we compare the fit results using our new background modelling approach with standard methods used in the literature and find that our method better captures the emission from H ii regions in NGC 4449 and the faint emission regions in NGC 1275. These methods also demonstrate that the background does change as a function of the position of the data cube. While the approach is applied explicitly to SITELLE data in this study, we argue that it can be readily adapted to any integral field unit style data, enabling the user to obtain more robust measurements on the flux of the emission lines.