FABIO, WHEN DID YOU DECIDE TO GO WATCH AN ECLIPSE IN THE ARCTIC? I’ve been feeling this urge to visit the northernmost parts of Earth for a while now. My PhD in Stockholm gave me the opportunity to explore the Norwegian coastline and Lapland, but the Arctic was a different story. A sort of forbidden dream. Then last year I started a postdoc at Yale, in the research group led by John Wettlaufer, who’s an expert on sea ice and the Arctic. When I heard there was gonna be a total solar eclipse at Svalbard I knew I had to go. WHERE IS SVALBARD, EXACTLY? Svalbard is an archipelago situated about half way between continental Norway and the North Pole, and it is an outpost for research and arctic exploration. In Longyearbyen, a little city of about 2000 people, and Svalbard’s capital, there is the world’s northernmost institution for higher education and research: the University Center in Svalbard.

INTRODUCTION Much of modern Astronomy research depends on software. Digital images and numerical simulations are central to the work of most astronomers today, and anyone who is actively involved in astronomy research has a variety of software techniques in their toolbox. Furthermore, the sheer volume of data has increased dramatically in recent years. The efficient and effective use of large data sets increasingly requires more than rudimentary software skills. Finally, as astronomy moves towards the open code model, propelled by pressure from funding agencies and journals as well as the community itself, readability and reusability of code will become increasingly important (Figure [fig:xkcd]). Yet we know few details about the software practices of astronomers. In this work we aim to gain a greater understanding of the prevalence of software tools, the demographics of their users, and the level of software training in astronomy. The astronomical community has, in the past, provided funding and support for software tools intended for the wider community. Examples of this include the Goddard IDL library (funded by the NASA ADP), IRAF (supported and developed by AURA at NOAO), STSDAS (supported and developed by STScI), and the Starlink suite (funded by PPARC). As the field develops, new tools are required and we need to focus our efforts on ones that will have the widest user base and the lowest barrier to utilization. For example, as our work here shows, the much larger astronomy user base of Python relative to the language R suggests that tools in the former language are likely to get many more users and contributers than the latter. More recently, there has been a growing discussion of the importance of data analysis and software development training in astronomy (e.g., the special sessions at the 225th AAS “Astroinformatics and Astrostatistics in Astronomical Research Steps Towards Better Curricula” and “Licensing Astrophysics Codes”, which were standing room only). Although astronomy and astrophysics went digital long ago, the formal training of astronomy and physics students rarely involves software development or data-intensive analysis techniques. Such skills are increasingly critical in the era of ubiquitous “Big Data” (e.g., , or the 2015 NOAO Big Data conference). Better information on the needs of researchers as well as the current availability of training opportunities (or lack thereof) can be used to inform, motivate and focus future efforts towards improving this aspect of the astronomy curriculum. In 2014 the Software Sustainability Institute carried out an inquiry into the software use of researchers in the UK (, see also the associated presentation). This survey provides useful context for software usage by researchers, as well as a useful definition of “research software”: Software that is used to generate, process or analyze results that you intend to appear in a publication (either in a journal, conference paper, monograph, book or thesis). Research software can be anything from a few lines of code written by yourself, to a professionally developed software package. Software that does not generate, process or analyze results - such as word processing software, or the use of a web search - does not count as ‘research software’ for the purposes of this survey. However, this survey was limited to researchers at UK institutions. More importantly, it was not focused on astronomers, who may have quite different software practices from scientists in other fields. Motivated by these issues and related discussions during the .Astronomy 6 conference, we created a survey to explore software use in astronomy. In this paper, we discuss the methodology of the survey in §[sec:datamethods], the results from the multiple-choice sections in §[sec:res] and the free-form comments in §[sec:comments]. In §[sec:ssicompare] we compare our results to the aforementioned SSI survey and in §[sec:conc] we conclude. We have made the anonymized results of the survey and the code to generate the summary figures available at https://github.com/eteq/software_survey_analysis. This repository may be updated in the future if a significant number of new respondents fill out the survey[1]. [1] http://tinyurl.com/pvyqw59

About the Authors

INTRODUCTION The properties of faint dwarf galaxies at or beyond the outer reaches of the Local Group (1 − 5 Mpc) probe the efficiency of environmentally driven galaxy formation processes and provide direct tests of cosmological predictions \citep[e.g., ][]{kl99ms, moo99ms, stri08commonmass, krav10satrev, kirby10, BKBK11, pontzen12, geha13}. However, searches for faint galaxies suffer from strong luminosity and surface brightness biases that render galaxies with LV ≲ 10⁶ L⊙ difficult to detect beyond the Local Group . Because of these biases, searching for nearby dwarf galaxies with methodologies beyond the standard optical star count methods are essential. This motivates searches for dwarf galaxies using the 21 cm emission line of neutral hydrogen (). While such searches cannot identify passive dwarf galaxies like most Local Group satellites, which lack , they have the potential to find gas-rich, potentially starforming dwarf galaxies. This is exemplified by the case of the Leo P dwarf galaxy, found first in and later confirmed via optical imaging . Here we describe two faint dwarf galaxies identified via emission in the first data release of the Galactic Arecibo L-band Feed Array (GALFA-HI) survey . As described below, they are likely within the Local Volume (<10 Mpc) but just beyond the Local Group (≳1 Mpc), so we refer to them as Pisces A and B. This paper is organized as follows: in Section [sec:data], we present the data used to identify these galaxies. In Section [sec:distance], we consider possible distance scenarios, while in Section [sec:conc] we provide context and some conclusions. Where relevant, we adopt a Hubble constant of $H_0=69.3 \; {\rm km \; s}^{-1}{\rm Mpc}^{-1}$ from WMAP9 .

In the Local Group, nearly all of the dwarf galaxies ($\mstar\lesssim10^9\msun$) that are satellites within $300\kpc$ (the virial radius) of the Milky Way (MW) and Andromeda (M31) have quiescent star formation and little-to-no cold gas. This contrasts strongly with comparatively isolated dwarf galaxies, which are almost all actively star-forming and gas-rich. This near dichotomy implies a _rapid_ transformation after falling into the halos of the MW or M31. We combine the observed quiescent fractions for satellites of the MW and M31 with the infall times of satellites from the ELVIS suite of cosmological simulations to determine the typical timescales over which environmental processes within the MW/M31 halos remove gas and quench star formation in low-mass satellite galaxies. The quenching timescales for satellites with $\mstar<10^8\msun$ are short, $\lesssim2\gyr$, and decrease at lower $\mstar$. These quenching timescales can be $1-2\gyr$ longer if environmental preprocessing in lower-mass groups prior to MW/M31 infall is important. We compare with timescales for more massive satellites from previous works, exploring satellite quenching across the observable range of $\mstar=10^{3-11}\msun$. The environmental quenching timescale increases rapidly with satellite $\mstar$, peaking at $\approx9.5\gyr$ for $\mstar\sim10^9\msun$, and rapidly decreases at higher $\mstar$ to less than $5\gyr$ at $\mstar>5\times10^9\msun$. Thus, satellites with $\mstar\sim10^9\msun$, similar to the Magellanic Clouds, exhibit the longest environmental quenching timescales.

INTRODUCTION Young protostars are observed to launch energetic collimated bipolar mass outflows . These protostellar outflows play a fundamental role in the star formation process on a variety of scales. On sub-pc scales they entrain and unbind core gas, thus setting the efficiency at which dense gas turns into stars . Interaction between outflows and infalling material may regulate protostellar accretion and, ultimately, terminate it . On sub-pc up to cloud scales, outflows inject substantial energy into their surroundings, potentially providing a means of sustaining cloud turbulence over multiple dynamical times. The origin of outflows is attributed to the presence of magnetic fields, and a variety of different models have been proposed to explain the launching mechanism \citep[e.g.,][]{arce07}. Of these, the “disk-wind" model , in which the gas is centrifugally accelerated from the accretion disk surface, and the “X-wind" model , in which gas is accelerated along tightly wound field lines, are most commonly invoked to explain observed outflow signatures. However, investigating the launching mechanism is challenging because launching occurs on scales of a few stellar radii and during times when the protostar is heavily extincted by its natal gas. Consequently, separating outflow gas from accreting core gas, discriminating between models, and determining fundamental outflow properties are nontrivial. Three main approaches have been applied to studying outflows. First, single-dish molecular line observations have been successful in mapping the extent of outflows and their kinematics on core to cloud scales \citep[][]{bourke97,arce10,dunham14}. However, outflow gas with velocities comparable to the cloud turbulent velocity can only be extracted with additional assumptions and modeling \citep[e.g.,][]{arce01b,dunham14}, which are difficult to apply to confused, clustered star forming environments . Second, interferometry provide a means of mapping outflows down to 1,000 AU scales scales , and the Atacama Large Millimeter/submilllimeter Antenna (ALMA) is extending these limits down to sub-AU scales . However, interferometry is not suitable for producing large high-resolution maps and it resolves out larger scale structure. Consequently, it is difficult to assemble a complete and multi-scale picture of outflow properties with these observations. Finally, numerical simulations provide a complementary approach that supplies three-dimensional predictions for launching, entrainment and energy injection . The most promising avenue for understanding outflows lies at the intersection of numerical modeling and observations. By performing synthetic observations to model molecular and atomic lines, continuum, and observational effects, simulations can be mapped into the observational domain where they can be compared directly to observations \citep[e.g.,][]{Offner11,Offner12b,Mairs13}. Such direct comparisons are important for assessing the “reality" of the simulations, to interpret observational data and to assess observational uncertainties . In addition to observational instrument limitations, chemistry and radiative transfer introduce additional uncertainties that are difficult to quantify without realistic models . Synthetic observations have previously been performed in the context of understanding outflow opening angles , observed morphology , and impact on spectral energy distributions . The immanent completion of ALMA provides further motivation for predictive synthetic observations. Although ALMA will have unprecedented sensitivity and resolution compared to existing instruments, by nature interferometry resolves out large-scale structure and different configurations will be sensitive to different scales. Atmospheric noise and total observing time may also effect the fidelity of the data. Previous synthetic observations performed by suggest that the superior resolution of full ALMA and the Atacama Compact Array (ACA) will be able to resolve core structure and fragmentation prior to binary formation. predicts that ALMA will be able to resolve complex outflow velocity structure and helical structure in molecular emission. In this paper we seek to quantify the accuracy of different ALMA configurations in recovering fundamental gas properties such as mass, line-of-sight momentum, and energy. We use the casa software package to synthetically observe protostellar outflows in the radiation-hydrodynamic simulations of . By modeling the emission at different times, inclinations, molecular lines, and observing configurations we evaluate how well physical quantities can be measured in the star formation process. In section §[Methods] we describe our methods for modeling and observing outflows. In section §[results] we evaluate the effects of different observational parameters on bulk quantities. We discuss results and summarize conclusions in §[Conclusions].

INTRODUCTIONLABELPLACEHOLDER1ID [still needed] This paper presents observations of the X-ray Binary taken simultaneously in X-rays with the _Chandra Observatory_, in radio with the _Jansky VLA_, and in optical and infrared with the SMARTS 1.3m telescope. Section [sect:obs] describes our observations in detail, Section [sect:sed] discusses the Spectral Energy Distribution for , Section [sect:correlation] discusses these results in the context of the radio/X-ray correlation for X-ray Binaries, and Section [sect:concl] contains our conclusions.

It has recently been proposed (Goodman et al. 2014) that long, skinny, infrared dark clouds may trace out the densest features of the Milky Way, which include spiral arms, and possible inter-arm tendrils. The features are so long and skinny that they are almost certainly caused and maintained by a global gravitational potential, so they are not likely to be self-gravitating molecular clouds. These “Bones of the Milky Way” could be used to help piece together the structure of the Galaxy, shedding light on age-old questions, such as the number of spiral arms in our Galaxy and their locations. We have searched for and identified a handful of candidate Bones: long, filamentary infrared-dark clouds found in position-velocity space where our current model of the Galaxy predicts spiral arms should lie. Utilizing archival data, we have confirmed the location of these Bone candidates in the Galactic mid-plane and within 5 km/s of a spiral arm. We propose to use the IRAM 30-m to create the first ever high-resolution CO map (1mm) of a candidate “Bone of the Milky Way,” simultaneously with a suite of dense gas tracers at 3mm with IRAM. Capitalizing on IRAM’s unique ability to map CO over large areas at high angular resolution while simultaneously obtaining kinematic information about the dense gas, we will provide the first measure of structure and kinematics toward these unique Galactic structures. Our total time request is XX hours to map XX sq. arcminutes at 1mm (¹³CO and C¹⁸O 2-1) and 3mm (HCO+, HCN 1-0, etc.) toward our most promising Northern-hemisphere candidate Bone, “BC1.”

INTRODUCTION Supermassive black holes (BHs) live at the heart of essentially all massive galaxies with bulges. BHs power active galactic nuclei (AGN) and are thought to be important agents in the evolution of their hosts. Using optical spectroscopy from the SDSS, WE HAVE ASSEMBLED THE LARGEST SAMPLE OF LOW MASS (DWARF) GALAXIES HOSTING MASSIVE BHS TO DATE (Reines et al. 2013). These dwarf galaxies have stellar masses comparable to the Magellanic Clouds ($M_{\rm stellar} ∼ 10^{8.5} − 10^{9.5} M_{\odot}$) and contain some of the least-massive BHs known in galaxy nuclei ($M_{\rm BH} ∼ 10^5 M_{\odot}$). Determining the impact of AGN on thier low-mass host galaxies will help constrain BH feedback and galaxy formation models at all mass scales. WE PROPOSE NEW 21 CM NEUTRAL HYDROGEN (HI) EMISSION OBSERVATIONS TO STUDY THE PROPERTIES OF THE LEAST-MASSIVE GALAXIES KNOWN TO CONTAIN MASSIVE BHS. By examining BH to HI scaling relations at the sparsely-populated low-mass end, these new observations will enable us to inspect the correlation of gas content and dynamical masses to the BH and galaxy properties of our BH hosts. In order to separate the effects of AGN feedback from environmental effects, we will compare our isolated dwarf galaxies that host BHs against the isolated control sample of Bradford, et al., (in prep.). The results of our study will provide vital information on the formation and evolution of the smallest galaxies hosting massive BHs as well as the effect of AGN feedback on the cold HI gas content of low mass galaxies.

INTRODUCTION Petigura et al. (2013) calculated the frequency of Earth-like planets ($R=1-2\Rearth$) in the habitable zone (HZ) of their host star to be 22 ± 8%, with their HZ defined to be $0.25-4.0\Fe$, where $\Fe$ is the incident flux Earth receives from the Sun. The authors created an independent transit search algorithm and fitting routine called TERRA and applied it to the _Kepler_ light curves of the “Best42k”, or the brightest (Kp = 10 − 15) 42,557 Sun-like stars (Teff = 4100 − 6100K, logg = 4.0 − 4.9) exhibiting the lowest photometric noise, selecting those stars on the main sequence or just starting the subgiant phase, according to the initial stellar parameters. After false positive checks and other vetting procedures, 603 “eKOIs” remained, in analogy to the _Kepler_ Objects of Interest (KOIs). The key method that allows Petigura et al. (2013) to calculate the occurrence rate of Earth-like planets in the HZ is a thorough analysis of their completeness. They measured completeness by injecting 40,000 planets at different periods and planet radii into the light curves of the actual _Kepler_ light curves of the Best42k stars. They then applied TERRA to check how many of their injected transits they could recover. They are then able to correct for transiting planets missed by their TERRA code by dividing the number of planets recovered by the completeness value. One can then correct this number by the geometric probability that a planet would transit: PT = R*/a, where R* is the stellar radius and a is the semi-major axis of the planet. They use these corrections to calculate the frequency of planets in the inner HZ, which they define as $1-4\Fe$, where they claim a high enough completeness to get an accurate measurement of the occurrence rate of Earth-like planets. Their estimate of the occurrence rate for Earth-like planets in the inner HZ is 11 ± 4%. For the outer HZ, which they define to be $0.25-1.00\Fe$, they must rely on an extrapolation. Petigura et al. (2013) find a roughly constant occurrence rate in equally binned log(P), which translates into a roughly constant occurrence rate in equally binned log(F). Therefore, since $1-4\Fe$ and $0.25-1\Fe$ are equally spaced in log(F) (a factor of 4), the occurrence rate in the outer HZ is also 11 ± 4%. That makes the overall occurrence rate in the HZ 22 ± 8%. We aim to use the data available in Petigura et al. (2013) to redo the analysis as best we can by attempting to calculate the occurrence rate ourselves with different assumptions. For example, a HZ extending to $4\Fe$ is almost certainly too hot to be habitable for most terrestrial worlds, although particularly dry planets may be an exception. Another problem is that the completeness drops drastically at the exact point where the inner HZ begins. As such, Petigura et al. (2013) had to extrapolate to achieve an occurrence rate for their outer HZ, $0.25-1\Fe$, which is actually where the bulk of the HZ is according to many HZ calculations, such as Kopparapu et al. (2013). We would like to explore different definitions of what is habitable, what is Earth-like, and the methods to calculate the occurrence rate in the full HZ.