Extremely Large Telescope

Abstract:

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 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 survey that publicly releases infrared spectra of over 650,000 stars. The main sample from the Extended Baryon Oscillation Spectroscopic Survey (eBOSS), as well as the subsurvey Time Domain Spectroscopic Survey data were fully released in DR16. New single-fiber optical spectroscopy released in DR17 is from the SPectroscipic IDentification of ERosita Survey subsurvey and the eBOSS-RM program. Along with the primary data sets, DR17 includes 25 new or updated value-added catalogs. 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, Local Volume Mapper, and Black Hole Mapper surveys.

Abstract:

Observations of exoplanet atmospheres in high resolution have the potential to resolve individual planetary absorption lines, despite the issues associated with ground-based observations. The removal of contaminating stellar and telluric absorption features is one of the most sensitive steps required to reveal the planetary spectrum and, while many different detrending methods exist, it remains difficult to directly compare the performance and efficacy of these methods. Additionally, though the standard cross-correlation method enables robust detection of specific atmospheric species, it only probes for features that are expected a priori. Here, we present a novel methodology using Gaussian process (GP) regression to directly model the components of high-resolution spectra, which partially addresses these issues. We use two archival CRyogenic Infra-Red Echelle Spectrograph (CRIRES)/Very Large Telescope (VLT) data sets as test cases, observations of the hot Jupiters HD 189733 b and 51 Pegasi b, recovering injected signals with average line contrast ratios of ∼4.37 × 10-3 and ∼1.39 × 10-3, and planet radial velocities ΔKp = 1.45 ± 1.53 km s-1 and ΔKp = 0.12 ± 0.12 km s-1 from the injection velocities, respectively. In addition, we demonstrate an application of the GP method to assess the impact of the detrending process on the planetary spectrum, by implementing injection-recovery tests. We show that standard detrending methods used in the literature negatively affect the amplitudes of absorption features in particular, which has the potential to render retrieval analyses inaccurate. Finally, we discuss possible limiting factors for the non-detections using this method, likely to be remedied by higher signal-to-noise data.

Abstract:

We use high-resolution maps of the molecular interstellar medium (ISM) in the centres of eighty-six nearby galaxies from the millimetre-Wave Interferometric Survey of Dark Object Masses (WISDOM) and Physics at High Angular Resolution in Nearby GalaxieS (PHANGS) surveys to investigate the physical mechanisms setting the morphology of the ISM at molecular cloud scales. We show that early-type galaxies tend to have smooth, regular molecular gas morphologies, while the ISM in spiral galaxy bulges is much more asymmetric and clumpy when observed at the same spatial scales. We quantify these differences using non-parametric morphology measures (Asymmetry, Smoothness and Gini), and compare these measurements with those extracted from idealised galaxy simulations. We show that the morphology of the molecular ISM changes systematically as a function of various large scale galaxy parameters, including galaxy morphological type, stellar mass, stellar velocity dispersion, effective stellar mass surface density, molecular gas surface density, star formation efficiency and the presence of a bar. We perform a statistical analysis to determine which of these correlated parameters best predicts the morphology of the ISM. We find the effective stellar mass surface (or volume) density to be the strongest predictor of the morphology of the molecular gas, while star formation and bars maybe be important secondary drivers. We find that gas self-gravity is not the dominant process shaping the morphology of the molecular gas in galaxy centres. Instead effects caused by the depth of the potential well such as shear, suppression of stellar spiral density waves and/or inflow affect the ability of the gas to fragment.