SCIENTIFIC JUSTIFICATION _The ‘Scientific Justification’ section of the proposal (see Section 9.1) should include a description of the scientific investigations that will be enabled by the final data products, and their importance_ _6 page limit, total proposal + figures can be 11._ One of the most powerful observational tools for constraining the physics governing galaxy formation and evolution is morphology. The structural features of a galaxy are known to have close relationships with its physical properties; eg. the link between star formation rate and Hubble type or spiral arms , bars and AGN , bars and atomic gas content , [lots more possibilities of examples - help with more non-galaxy zoo examples?] It is known that the demographics of most morphological features are _not_, in general, constant as a function of redshift. This is not surprising, given that key elements involved in the formation of galaxies are also shown to change as the Universe evolves, eg. star formation is known to peak at z ∼ 1 and drop steadily thereafter. [few paragraphs of more descriptive examples of how galaxy physics is related to morphology + reasons for studying 0 < z < 2)] Obtaining morphological data for such large numbers of galaxies is a unique challenge, in that to date there is no system that can produce both accurate and complete morphologies using automated methods. This problem is especially present with increasing redshift, for two reasons. First, images of distant galaxies are less resolved, making it difficult to distinguish finer features in the image. Second, galaxy shapes become increasingly irregular in the early Universe, due to increased merger rate and the clumpy nature of star formation. As large telescopes become more capable of imaging these distant galaxies, we continue to discover for the first time new large-scale structures which do not exist at low z; this creates a difficulty in defining an automated categorization for these unique types. Until automated methods overcome these challenges, visual classification by humans remains the most accurate method of measuring galaxy morphology, especially for galaxies beyond the local Universe. Visual classification is of course not without its own challenges, which are time and efficiency. While humans produce more accurate and complete classifications than a computer, the time it takes to do so is overwhelming for the wealth of data becoming available by large surveys. The Galaxy Zoo project has developed a highly innovative method for bypassing the time drawback while maintaining the accuracy of visual classification. Displaying images of SDSS galaxies to volunteers via a simple and engaging web interface, www.galaxyzoo.org asks people to classify the images by eye. Within its first year, each of the ∼1 million SDSS galaxies had already been classified an average of 40 times through the efforts of hundreds of thousands of members of the general public providing ∼40 million classifications . In 2010, Galaxy Zoo moved beyond the local Universe by including ∼100, 000 HST galaxies in a project known as Galaxy Zoo: Hubble. All galaxies were classified at least 40 times by late 2012. This project enabled the first direct, morphologically accurate studies to be done on the evolution of galaxies, several of which have already been completed with the preliminary data, including bar fraction with redshift and passive disk fraction with redshift . These only represent a small fraction of the numerous possibilities for scientific investigation capable with these data; disk/spheroidal distinction, bars, spiral arms, clumpiness, and bulge dominance are a portion of the morphological information provided by this catalog (for the full list see Figure [fig:decision tree]). Our aim with this proposal is to develop the next phase of Galaxy Zoo:Hubble, which we will hereafter refer to as Galaxy Zoo:Hubble 2 (GZH2). The motivation for extending this project is twofold: First, although the visual classification methods have been immensely successful thus far in obtaining robust morphologies for large ( 100, 000) samples of galaxies, automation methods have improved since the first release in the form of powerful machine-learning algorithms. These alone are still not independently capable of accurate classification for galaxies at all redshifts, however _combining_ these methods with the current system of human classifications has been shown to reduce the classification time of galaxies by 80% (can we cite something/ provide a figure Melanie?), thereby significantly improving both the efficiency and accuracy of GZH classifications. The details for this process are explained in full in the Analysis Plan. Second, in addition to the original GZH galaxies, an additional XX,XXX HST galaxies will be added to the project to be classified by this new method. By combining machine-learning with human classifications, GZH2 will provide the most morphologically accurate data for the widest redshift range (to z ∼ 1.2) currently available. These data will enable countless new science projects involving galaxy evolution than has ever been capable to this level of accuracy. With the funding from this proposal, our team will focus on two science cases: clumpy galaxies (need better zinger description) and the mass-metallicity relation.

CDS&E: REAL-TIME, COMMENSAL FAST RADIO TRANSIENT SURVEYS WITH THE VERY LARGE ARRAY ** to do: systematic references to co-observing resources and commensal VLASS ** _:_ We propose a set of enhancements to the Jansky Very Large Array (VLA) to enable 24/7 surveys for fast radio transients. Large, single-dish radio telescopes have dedicated thousands of hours to surveys for millisecond-scale transients with the aim of capturing rare classes of cosmological transient, understanding the lifecycle of neutron stars, and measuring otherwise inaccessible properties of interstellar and intergalactic material. This field has been revitalized in the past decade with the discovery of new classes of transient. As the most sensitive radio interferometer on earth, the VLA will revolutionize this field with its ability to form sensitive images with unmatched spatial resolution. The core of the proposed system is a 32-node, GPU-accelerated compute cluster that will search images generated on timescales from 1 ms to 1 minute. Real-time processing will allow triggered recording of the parallel data stream for later analysis and the rapid announcement of candidates for follow-up observing. By integrating with a high-speed, duplicate data stream of the VLA, this system will turn each observation into a fast transient survey, ultimately encompassing thousands of hours per year. _:_ Interferometric imaging will do pioneering science with a mysterious new class of radio transients known as “fast radio bursts”. These millisecond transients have inferred distances that imply a cosmological origin and extreme luminosities. Such an event would open a new window on the intergalactic medium and cosmology. Only an interferometer can uniquely identify counterparts (e.g., a host galaxy or gamma-ray burst) well enough to constrain their nature and enable their use as cosmic probes. The proposed system will provide the first arcsecond localization of a burst and will detect more than 12 bursts over the course of the program. Similarly, the interferometric discovery and localization of other classes of millisecond transient will address topics ranging from the missing baryon problem to (sub)stellar magnetism to the search for exotic binary pulsar systems. Time-domain astronomy has been identified as a discovery frontier in the recent Decadal Review of Astronomy and Astrophysics. Real-time, commensal analysis creates discovery potential by searching an otherwise inaccessible data stream. Developing this system at the VLA will produce multiplicative improvement to scientific productivity for this already powerful telescope. _:_ The completed system will autonomously detect radio transients and drive follow-up observing across the electromagnetic spectrum. Co-observing with other observatories, such as the Long Wavelength Array and Skynet, opens novel science and public outreach opportunities. Additional computing power and flexible software at the VLA site will open new observing models. The data analysis software is open source, which allows any astronomer to reproduce VLA detections or integrate the software into other interferometric fast transient surveys. Consider the excitement of seeing a shooting star: a dynamic flash in what seems a static sky. We aim for our transient detection system to inspire similar recognition of the evolving and dynamic sky at timescales faster than the blink of an eye. Alerts will be announced for all new discoveries and will be visualized with movies, images, and spectra to engage the public at NRAO sites and via the web. Opportunities for student training will be available on topics such as transient astrophysics, interferometric algorithms, heterogeneous/high-performance computing, and front-end web development. These topics, and the data-intensive nature of this project, have increasing relevance for academic, commercial, and national security applications.

INTRODUCTION As we enter the advanced-detector era of ground-based gravitational-wave (GW) astronomy, it is critical that we understand the abilities and limitations of the analyses we are prepared to conduct. Of the many predicted sources of GWs, binary neutron-star (BNS) coalescences are paramount; their progenitors have been directly observed , and the advanced detectors will be sensitive to their GW emission up to ∼400 Mpc away . When analyzing a GW signal from a circularized compact binary merger, strong degeneracies exist between parameters describing the binary (e.g., distance and inclination). To properly estimate any particular parameter(s) of interest, the marginal distribution is estimated by integrating the joint posterior probability density function (PDF) over all other parameters. In this work, we sample the posterior PDF using software implemented in the LALINFERENCE library . Specifically we use results from LALINFERNCE_NEST , a nest sampling algorithm , and LALINFERENCE_MCMC , a Markov-chain Monte Carlo algorithm \citep[chapter 12]{Gregory2005}. Previous studies of BNS signals have largely assessed parameter constraints assuming negligible neutron-star (NS) spin, restricting models to nine parameters. This simplification has largely been due to computational constraints, but the slow spin of NSs in short-period BNS systems observed to date \citep[e.g.,][]{Mandel_2010} has also been used as justification. However, proper characterization of compact binary sources _must_ account for the possibility of non-negligible spin; otherwise parameter estimates will be biased . This bias can potentially lead to incorrect conclusions about source properties and even misidentification of source classes. Numerous studies have looked at the BNS parameter estimation abilities of ground-based GW detectors such as the Advanced Laser Interferometer Gravitational-Wave Observatory \citep[aLIGO;][]{Aasi_2015} and Advanced Virgo \citep[AdV;][]{Acernese_2014} detectors. assessed localization abilities on a simulated non-spinning BNS population. looked at several potential advanced-detector networks and quantified the parameter-estimation abilities of each network for a signal from a fiducial BNS with non-spinning NSs. demonstrated the ability to characterize signals from non-spinning BNS sources with waveform models for spinning sources using Bayesian stochastic samplers in the LALINFERENCE library . used approximate methods to quantify the degeneracy between spin and mass estimates, assuming the compact objects’ spins are aligned with the orbital angular momentum of the binary \citep[but see][]{Haster_2015}. simulated a collection of loud signals from non-spinning BNS sources in several mass bins and quantified parameter estimation capabilities in the advanced-detector era using non-spinning models. introduced precession from spin–orbit coupling and found that the additional richness encoded in the waveform could reduce the mass–spin degeneracy, helping BNSs to be distinguished from NS–black hole (BH) binaries. conducted a similar analysis of a large catalog of sources and found that it is difficult to infer the presence of a mass gap between NSs and BHs , although, this may still be possible using a population of a few tens of detections . Finally, and the follow-on represent an (almost) complete end-to-end simulation of BNS detection and characterization during the first 1–2 years of the advanced-detector era. These studies simulated GWs from an astrophysically motivated BNS population, then detected and characterized sources using the search and follow-up tools that are used for LIGO–Virgo data analysis . The final stage of the analysis missing from these studies is the computationally expensive characterization of sources while accounting for the compact objects’ spins and their degeneracies with other parameters. The present work is the final step of BNS characterization for the simulations using waveforms that account for the effects of NS spin. We begin with a brief introduction to the source catalog used for this study and in section [sec:sources]. Then, in section [sec:spin] we describe the results of parameter estimation from a full analysis that includes spin. In section [sec:mass] we look at mass estimates in more detail and spin-magnitude estimates in section [sec:spin-magnitudes]. In section [sec:extrinsic] we consider the estimation of extrinsic parameters: sky position (section [sec:sky]) and distance (section [sec:distance]), which we do not expect to be significantly affected by the inclusion of spin in the analysis templates. We summarize our findings in section [sec:conclusions]. A comparison of computational costs for spinning and non-spinning parameter estimation is given in appendix [ap:CPU].

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.”

There were flies in space. We looked at their gut microbes. Because, why not?

In this splinter session, ten speakers presented results on solar and stellar activity and how the two fields are connected. This was followed by a lively discussion and supplemented by short, one-minute highlight talks. The talks presented new theoretical and observational results on mass accretion on the Sun, the activity rate of flare stars, the evolution of the stellar magentic field on time scales of a single cycle and over the lifetime of a star, and two different approaches to model the radial-velocity jitter in cool stars that is due to the granulation on the surface. Talks and discussion showed how much the interpretation of stellar activity data relies on the sun and how the large number of objects available in stellar studies can extend the parameter range of activity models.

INTRODUCTION Kinetic temperature exerts a measurable effect on most physical processes, and is explicitly used as an input to model both plant water stress and evapotranspiration . Kinetic temperature exerts a measurable effect on most physical processes, and is explicitly used as an input to model ecological processes such as photosynthesis , leaf litter decomposition , and evapotranspiration . Evapotranspiration is a process of particular interest to farmers and water managers in arid drought prone regions such as California, where the 2012 nut and fruit crop receipts alone totaled 18.7 billion dollars (CDFA, 2013-2014). The economic impact from the 2014 California drought is not yet known, but caps on total water allotment (30% of 2013 levels) to the San Joaquin Valley forces difficult decisions for farmers: inefficient watering may bring a particular crop to harvest, at the cost of available water to other fields; water a crop too little and it will undergo cavitation and wilt, ruining the harvest. Severe cavitation due to under watering requires replanting, with loss of productivity stretching over years for perennial crops such as vineyards. Accurate modeling of temperature and evapotranspiration can provide farmers with robust estimates of water demand and enable more conservative agricultural water use to salvage a harvest or keep orchards alive, reducing the human impact of drought. While in situ measurements are valuable tools for farmers, the size and scope of agriculture25.4 million acres and 80,500 farms in 2012 for California alone (CDFA, 2013-2014)underscore the necessity for regional scale remotely sensed temperature estimates that are accurate. The accuracy of temperature estimates are particularly important for physical processes like evapotranspiration, which is driven by the temperature gradient between the air and leaves, and can be less than 1K . Current remotely sensed temperature estimates typically have errors on the order of 1K when averaged over all surface types ; however, errors up to 4K are typical for spectral greybodies such as vegetation , due to both uncertainty in emissivity and moister atmospheric profiles present over large contiguous vegetation patches. Errors as large as 3K-8K can occur over vegetation in humid conditions , and even in less humid mediterranean climates robust atmospheric correction of thermal data is essential to provide operational data to farmers and resource managers.

The redshifts and emission-line strengths for XXXX Galaxies in 29 fields of the WFC3 Infrared Spectroscopic Parallels (WISP) Survey are presented.