Enlightening the Chemistry of Infalling Envelopes and Accretion Disks Around Sun-Like Protostars: The ALMA FAUST Project

The huge variety of planetary systems discovered in recent decades likely depends on the early history of their formation. In this contribution, we introduce the FAUST Large Program which focuses specifically on the early history of solar-like protostars and their chemical diversity at scales of ∼ 50 au, where planets are expected to form. In particular, the goal of the project is to reveal and quantify the variety of chemical composition of the envelope/disk system at scales of 50 au in a sample of Class 0 and I protostars representative of the chemical diversity observed at larger scales. For each source, we propose a set of molecules able to (1) disentangle the components of the 50–2000 au envelope/disk system, (2) characterize the organic complexity in each of them, (3) probe their ionization structure, and (4) measure their molecular deuteration. The output will be a homogeneous database of thousands of images from different lines and species, i.e., an unprecedented source survey of the chemical diversity of solar-like protostars. FAUST will provide the community with a legacy dataset that will be a milestone for astrochemistry and star formation studies.

When Qualitative Research is Taught Virtually: Drawing on Experiential Design to Build Deeper Knowledge of Qualitative Observation

This essay discusses the EdD Program design and qualitative research course sequence at Drexel University, a private, non-profit institution. This large program admits up to 140 EdD students annually with approximately 100 attending fully online and 40 attending hybrid offerings at the main campus and at a satellite program in Washington, DC. The essay features a qualitative course observation activity designed by Janesick (2011) to be used face-to-face and details how the activity has been adapted for virtual delivery at East Coast University. As a literature review revealed a paucity of published works on teaching observation qualitatively, the authors seek to contribute to the knowledge base with particular emphasis on faculty teaching in an online program. Based upon the East Coast University faculty’s use of this observation activity, students develop increased understanding of the roles of perception and perspective in qualitative observation.

Systemizing Interprocedural Static Analysis of Large-scale Systems Code with Graspan

There is more than a decade-long history of using static analysis to find bugs in systems such as Linux. Most of the existing static analyses developed for these systems are simple checkers that find bugs based on pattern matching. Despite the presence of many sophisticated interprocedural analyses, few of them have been employed to improve checkers for systems code due to their complex implementations and poor scalability. In this article, we revisit the scalability problem of interprocedural static analysis from a “Big Data” perspective. That is, we turn sophisticated code analysis into Big Data analytics and leverage novel data processing techniques to solve this traditional programming language problem. We propose Graspan , a disk-based parallel graph system that uses an edge-pair centric computation model to compute dynamic transitive closures on very large program graphs. We develop two backends for Graspan, namely, Graspan-C running on CPUs and Graspan-G on GPUs, and present their designs in the article. Graspan-C can analyze large-scale systems code on any commodity PC, while, if GPUs are available, Graspan-G can be readily used to achieve orders of magnitude speedup by harnessing a GPU’s massive parallelism. We have implemented fully context-sensitive pointer/alias and dataflow analyses on Graspan. An evaluation of these analyses on large codebases written in multiple languages such as Linux and Apache Hadoop demonstrates that their Graspan implementations are language-independent, scale to millions of lines of code, and are much simpler than their original implementations. Moreover, we show that these analyses can be used to uncover many real-world bugs in large-scale systems code.

Waves to Weather: Exploring the limits of predictability of weather

Prediction of weather is a main goal of atmospheric science. Its importance to society is growing continuously due to factors such as vulnerability to natural disasters, the move to renewable energy sources, and the risks of climate change. But prediction is also a major scientific challenge due to the inherently limited predictability of a chaotic atmosphere, and has led to a revolution in forecasting methods as we have moved to probabilistic prediction. These changes provide the motivation for Waves to Weather (W2W), a major national research program in Germany with three main university partners in Munich, Mainz, and Karlsruhe. We are currently in the second 4-year phase of our planned duration of 12 years and employ 36 doctoral and post-doctoral scientists. In the context of this large program, we address what we have identified to be the most important and challenging scientific questions in predictability of weather, namely upscale error growth, errors associated with cloud processes, and probabilistic prediction of high impact weather. This paper presents some key results of the first phase of W2W and discusses how they have influenced our understanding of predictability. The key role of interdisciplinary research linking atmospheric scientists with experts in visualization, statistics, numerical analysis, and inverse methods will be highlighted. To ensure a lasting impact on research in our field in Germany and internationally, we have instituted innovative programs for training and support of early career scientists, and to support education, equal opportunities, and outreach, which are also described here.

New Constraints on the 12CO(2 − 1)/(1 − 0) Line Ratio Across Nearby Disc Galaxies

Both the CO(2-1) and CO(1-0) lines are used to trace the mass of molecular gas in galaxies. Translating the molecular gas mass estimates between studies using different lines requires a good understanding of the behaviour of the CO(2-1)-to-CO(1-0) ratio, R21. We compare new, high quality CO(1-0) data from the IRAM 30-m EMPIRE survey to the latest available CO(2-1) maps from HERACLES, PHANGS-ALMA, and a new IRAM 30-m M51 Large Program. This allows us to measure R21 across the full star-forming disc of nine nearby, massive, star-forming spiral galaxies at 27″(∼1 − 2 kpc) resolution. We find an average R21 = 0.64 ± 0.09 when we take the luminosity-weighted mean of all individual galaxies. This result is consistent with the mean ratio for disc galaxies that we derive from single-pointing measurements in the literature, $R_{\rm 21, lit}~=~0.59^{+0.18}_{-0.09}$. The ratio shows weak radial variations compared to the point-to-point scatter in the data. In six out of nine targets the central enhancement in R21 with respect to the galaxy-wide mean is of order $\sim 10{-}20\%$. We estimate an azimuthal scatter of ∼20% in R21 at fixed galactocentric radius but this measurement is limited by our comparatively coarse resolution of 1.5 kpc. We find mild correlations between R21 and CO brightness temperature, IR intensity, 70-to-160 μm ratio, and IR-to-CO ratio. All correlations indicate that R21 increases with gas surface density, star formation rate surface density, and the interstellar radiation field.

Exploring the hydrostatic mass bias in MUSIC clusters: application to the NIKA2 mock sample

Clusters of galaxies are useful tools to constrain cosmological parameters, only if their masses can be correctly inferred from observations. In particular, X-ray and Sunyaev-Zeldovich (SZ) effect observations can be used to derive masses within the framework of the hydrostatic equilibrium. Therefore, it is crucial to have a good control of the possible mass biases that can be introduced when this hypothesis is not valid. In this work, we analyzed a set of 260 synthetic clusters from the MUSIC simulation project, at redshifts 0 ≤ z ≤ 0.82. We estimate the hydrostatic mass of the MUSIC clusters from X-ray only (temperature and density) and from X-ray and SZ (density and pressure). Then, we compare them with the true 3D dynamical mass. The biases are of the order of 20%. We find that using the temperature instead of the pressure leads to a smaller bias, although the two values are compatible within 1σ. Non-thermal contributions to the total pressure support, arising from bulk motion and turbulence of the gas, are also computed and show that they are sufficient to account for this bias. We also present a study of the correlation between the mass bias and the dynamical state of the clusters. A clear correlation is shown between the relaxation state of the clusters and the bias factor. We applied the same analysis on a subsample of 32 objects, already selected for supporting the NIKA2 SZ Large Program.

ALMA Lensing Cluster Survey: a strongly lensed multiply imaged dusty system at z ≥6

We report the discovery of an intrinsically faint, quintuply-imaged, dusty galaxy MACS0600-z6 at a redshift z =6.07 viewed through the cluster MACSJ0600.1-2008 (z=0.46). A ≃ 4σ dust detection is seen at 1.2mm as part of the ALMA Lensing Cluster Survey (ALCS), an on-going ALMA Large program, and the redshift is secured via [C II] 158 μm emission described in a companion paper. In addition, spectroscopic follow-up with GMOS/Gemini-North shows a break in the galaxy’s spectrum, consistent with the Lyman break at that redshift. We use a detailed mass model of the cluster and infer a magnification μ ≳30 for the most magnified image of this galaxy, which provides an unprecedented opportunity to probe the physical properties of a sub-luminous galaxy at the end of cosmic reionisation. Based on the spectral energy distribution, we infer lensing-corrected stellar and dust masses of $\rm {2.9^{+11.5}_{-2.3}\times 10^9}$ and $\rm {4.8^{+4.5}_{-3.4}\times 10^6}$ $\rm {M_{\odot }}$ respectively, a star formation rate of $\rm {9.7^{+22.0}_{-6.6} M_{\odot } yr^{-1}}$, an intrinsic size of $\rm {0.54^{+0.26}_{-0.14}}$ kpc, and a luminosity-weighted age of 200±100 Myr. Strikingly, the dust production rate in this relatively young galaxy appears to be larger than that observed for equivalent, lower redshift sources. We discuss if this implies that early supernovae are more efficient dust producers and the consequences for using dust mass as a probe of earlier star formation.

The Ophiuchus DIsc Survey Employing ALMA (ODISEA)–III: the evolution of substructures in massive discs at 3-5 au resolution

We present 1.3 mm continuum ALMA long-baseline observations at 3-5 au resolution of 10 of the brightest discs from the Ophiuchus DIsc Survey Employing ALMA (ODISEA) project. We identify a total of 26 narrow rings and gaps distributed in 8 sources and 3 discs with small dust cavities (r <10 au). We find that two discs around embedded protostars lack the clear gaps and rings that are ubiquitous in more evolved sources with Class II SEDs. Our sample includes 5 objects with previously known large dust cavities (r >20 au). We find that the 1.3 mm radial profiles of these objects are in good agreement with those produced by numerical simulations of dust evolution and planet-disc interactions, which predict the accumulation of mm-sized grains at the edges of planet-induced cavities. Our long-baseline observations resulted in the largest sample of discs observed at ∼3-5 au resolution in any given star-forming region (15 objects when combined with Ophiuchus objects in the DSHARP Large Program) and allow for a demographic study of the brightest $\sim 5\%$ of the discs in Ophiuchus (i.e. the most likely formation sites of giant planets in the cloud). We use this unique sample to propose an evolutionary sequence and discuss a scenario in which the substructures observed in massive protoplanetary discs are mainly the result of planet formation and dust evolution. If this scenario is correct, the detailed study of disc substructures might provide a window to investigate a population of planets that remains mostly undetectable by other techniques.