Richard A. Shaw |
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I have for many years cultivated a deep interest in the astrophysics of gaseous nebulae. This area of knowledge is central to the understanding a wide variety of phenomena, from active galaxies to novae, star-forming regions to planetary nebulae. Analyzing the narrow emission lines from these objects is a powerful means to measure physical properties and chemical abundances of the ionized gas. Some years back, I worked with Reggie Dufour to recast a FORTRAN program developed at Lick Observatory into a powerful package in IRAF called nebular, to analyze collisionally excited emission lines. It has evidently had a significant impact on research in this area (see Shaw & Dufour 1995, PASP, 107, 896). After 13 years, it is time to upgrade this software to a more modern language, add new features and ions, and to make it VO-enabled. I am now working with Arturo Manchado and (soon) a new post-doc on the next generation of nebular.
Planetary nebulae (PNe) are the most visible manifestations of a period of stellar evolution from the Asymptotic Giant Branch (AGB) to white dwarfs, a phase thought to be common for low- to intermediate-mass (1–8 M⊙) stars. While the duration of the prior phases of progenitor evolution range from a few times 108 to 1010 yr, the PN phase is comparatively brief: it is set on the one hand by the time it takes for the PN shell to disperse into the ISM (∼104 yr), and on the other by the very steep dependence of the evolution timescale for the central star (CS) on mass: τ ∝ M−9.6 (Iben & Renzini 1983), which amounts to a few tens of years for a star near the Chandrasekhar limit. In spite of their brightness in narrow emission lines, the brevity of this phase means that there are very few observable PNe per unit luminosity in any given stellar system. In the Galaxy there are fewer than 2500 known PNe (Parker, et al. 2006), only a few hundred of which have been studied in any detail.
In spite of their rarity, properties of PNe are used to support studies as diverse as understanding the details of post-main sequence stellar evolution (Herwig 2005), the rate of enrichment of the ISM in particular elements (Stasinska 2004), the star formation history of the Galaxy (Maciel & Costa 2003), and, through the construct of a PN luminosity function (PNLF), as a link in the chain of extra-galactic distance indicators (see, e.g., Ciardullo 1991). Fundamental understandings of this type rely upon inferences about the total population of PNe in stellar systems, particularly in the Galaxy. For example, given the total number of PNe and a model for their observability, one can derive birth-rates and death-rates for PNe, and compare them to corresponding rates for preceding and subsequent phases of evolution. Answers such to questions as what fraction of all stars produce an observable PN, what fraction are produced by binary systems with different degrees of post-main sequence interaction, and what fraction of the interstellar N and C came from PNe are central, yet are uncertain to a factor of at least a few to several. Turning to the PNe themselves, it is now clear that the amount and chemical composition of the dust that is created during the course of prior AGB evolution is reflected in the gas-phase abundances of PNe, which in turn are closely tied to the abundance of the host Galaxy (Stanghellini, et al. 2007). In addition, the chemistry of the dust appears to undergo significant change during the PN phase of evolution, which in turn can affect the makeup of the dust in the ISM over time if most AGB stars produce PNe. Macrostructures (shells, rims, halos, size, overall shape) reveal a great deal about their evolutionary state, the shaping mechanism (Balick & Frank 2002), and are good predictors of the balance of enriched elements that will be returned to the ISM (e.g., Stanghellini, et al. 2000). The origin of microstructures (e.g., ansae, jets, plumes, clumps, etc.) on the other hand is considerably less well understood (Corradi 2006). But in neither case do we know how common any given feature is, nor which of several plausible physical mechanisms typically dominate to create and sustain these structures, because up to now it has not been possible to conduct a thorough census of nebular and CS properties on a complete sample.
The difficult challenge of constructing a complete sample of PNe in the Galaxy can be completely overcome by instead focussing on PNe in the Magellanic Clouds. The advantages of this approach are many (see, e.g., Jacoby 2006; Shaw 2006), but the most important is that we know how far away they are (to ~10% accuracy). This is not so of Galactic PNe, where distances are rarely known to better than 50% (see, e.g., Stanghellini, Shaw, & Villaver 2008). Using most ground-based telescopes, PNe in the Magellanic Clouds are angularly too small to be resolved, but they are easily resolved with Hubble Space Telescope. My colleague Letizia Stanghellini and I have been awarded hundreds of orbits of HST time to study Magellanic Cloud PNe. To date nearly 150 Planetary nebulae in the Large and Small Magellanic Clouds have been imaged, which represents 25–30% of all known PNe in these systems (Shaw, et al. 2006). We found, among other things, that nearly half of all LMC PNe have a substantially asymmetric morphology, which is roughly double the rate seen in the SMC. This suggests that the macroscopic shaping mechanisms for PNe depend upon the metallicity of the host stellar system. This is not unexpected, as radiation pressure on dust grains formed at the surface of the AGB stars is thought to be the dominant factor in the envelope ejection, and higher mass loss rates are expected as metallicity increases (Willson 2000).
To probe the questions of the origin of PN shaping, the evolution of dust, and the early star-nebula interaction, my collaborators and I were awarded dozens of hours with Spitzer Space Telescope to obtain mid-IR (5–40 μ) spectra of 30 PNe in the Magellanic Clouds. I am also participating in ongoing Spitzer and HST programs to observe the 130 angularly smallest PNe in the Galaxy. The gas and dust ejected at prior to the PN phase contain elements that have been produced by nucleosynthesis, and then carried to the stellar surface by the convective dredge-up processes. These objects are drawn from a much more metal rich population than the LMC and SMC samples, and should shed light on the discrepancy between pre-PNe, which are invariably bipolar, and Galactic PNe, where only a third or so have that morphology. In the end, though, some mechanism is needed to produce an asymmetric distribution of ejected mass from the parent AGB star if the origin of asymmetric PNe is to be understood.
One major, unresolved question in PN research is to determine the number of PN that are produced by binary progenitors. I am involved in a major collaboration (PlaN-B) to identify PNe with close binary progenitors, and to test the hypothesis that binary systems are essential to produce asymmetric PN morphology. But often the scope of a question is too broad to address with a small number of targeted observations, and too costly in telescope time to justify a dedicated observing campaign. I have been working lately with key members of the SuperMACHO and OGLE-3 survey teams to study variability in Magellanic Cloud PNe, which could indicate duplicity in the central star. A spectacular, and unexpected result of variability in the nebula itself was discovered in RP916 (Shaw et al. 2007).
One of the expectations (or hopes?) from theory, based largely on momentum considerations, is that PNe with asymmetric morphology are shaped via interaction of the central star with a binary companion or massive planet, or of wind from the central star with a toroidal disk. Some have argued that all visible PNe may be produced by binary central stars. This works only if the central stars are, in fact, close binaries—which lends itself to observational verification. The SuperMACHO and OGLE-3 surveys observed a large area of the central LMC in broad continuum bands, with a nightly or few-night cadence, over 5 or more years. I've begun to examine the light curves from a complete sample of LMC PNe for indications of binary central stars. Although there are significant selection effects, there are also many signatures that suggest binarity, including outburst events, eclipses, variability within the nebula itself, and irregular light curves. In all, we detect variability in about 20 LMC PNe, which is comparable to the number known in the Galaxy. Planned follow-up photometric campaigns on the best candidates will clear up marginal cases, and will help characterize the binary systems. To complement the search for binary CSs, I am examining IR photometric properties of these PNe from the 2MASS and SAGE catalogs, in order to identify potential Giant binary companions through analysis of the Spectral Energy Distributions.
The operation, calibration, and performance monitoring of space-based instruments is a challenging task. Most NASA astronomy missions expend considerable effort in this area, and also in documenting the instrument performance for end users, since these efforts provide high leverage for the community to generate science results with their data. During my career I was part of a team that was responsible for the Space Telescope Imaging Spectrograph, one of the most heavily used instruments on HST. I participated in the definition, planning, and execution of the calibration plan, provided support to users in the planning, health & safety checking, and problem resolution. I also generated a portion of the calibration reference data, contributed material to the STIS Instrument Manual, the HST Data Handbook, and generated various STIS Instrument Science Reports on the calibration and performance of the instrument.
Accepting institutional responsibility for instrument signature characterization has been slow to catch on in the ground-based optical/IR community, except for the very largest of the publically operated observatories. Yet excellent user documentation of published data products, such as those offered in the NOAO Science Archive, is critical to establishing the pedigree of the observing systems and processing pipelines, and to their acceptance by a world-wide community that may not be familiar with ground-based observing. This was my motivation for compiling and editing the inaugural NOAO Data Handbook, which describes NOAO data products, their processing, and the means to discover and access the data. One chapter covers data from the wide-field Mosaic cameras (the most heavily used instruments); a new chapter on the recently commissioned NEWFIRM IR camera is in preparation.
I've been involved with astronomical data systems since 1988: first with the construction of pipelines for NASA's IUE satellite, later with the development of analysis software, pipelines, web-based exposure time calculators, and other software for Hubble Space Telescope. When I joined NOAO in 2001, one of my first endeavors was to put together a team to create the inaugural NOAO Science Archive. I've been deeply involved in organizing the Astronomical Data Analysis Software and Systems (ADASS) conference, which is the premiere forum for software-intensive systems in astronomy. I spent 15 years on the Program Organizing Committee, and served as chair of that group for 4 years; I also chaired the Local Organizing Committee in 2006 when 300 participants attended ADASS XVI in Tucson, AZ.
Data Management & Curation: Data from most ground-based telescopes are not collected with the intent of providing public access though an archive. Even for NOAO, which aspires to have a public archive of raw (and in some cases, reduced) data, shortcomings in the legacy data taking systems for all but the most recent few instruments greatly complicate any effort to manage the heterogenious, incomplete, and sometimes inaccurate metadata. To address these problems, I designed a system of Data Quality Assurance and data remediation for core metadata (Shaw et al. 2009). Here, core means metadata that describe data provenance and pedigree, as well as coverages in the VO-sense: spatial, spectral/bandpass, temporal, and brightness; see Shaw (2007) for details. With this restricted set it is possible to validate metadata, and in many cases correct them, using a variety of cross-checks, heuristics, third-party calibration software, etc.
LSST: To this day, data systems and archives in even the most sophisticated astronomical observatories are under-appreciated, yet they are becoming more critical to the scientific success of the observatories and the communities they serve. On no project is this more true than the planned Large Synoptic Survey Telescope, which will survey the entire accessible sky roughly once every 3 nights, to a depth of roughly 25th mag. This synoptic survey will transform astronomy, and will open up entirely new vistas to explore. In the process, many Tera-bytes of imaging data will be generated per night (a data volume comparable to the entire Sloan Digital Sky Survey), which will result in several Peta-bytes per year of data, catalogs, and database contents. The bulk of the data management, transport, reduction, calibration, and analysis will have to be fully automated if this project is to succeed. I participate on a team that is designing the Science Data Quality Analysis system, which (as the name implies) measures the realized data quality and the performance of the data management system with respect to expectations and real-time environmental factors. This system will enable evaluation of the observing strategy, the scientific quality of the accumulated data, and progress against the goals of the 10 yr survey.
With the explosive growth in digital astronomical data, the importance of standards for data interchange and interoperability is greatly magnified. I am a member of the IAU Working Group for the development and curation of the FITS (Flexible Image Transport System) standard. Recently, I was part of a small technical panel to edit and update the standard to FITS v3.0, which is a much more complete, up-to-date, and readable document than its predecessor. FITS is not the end of the story, of course. Standards for the serialization and exchange of structured data are in an advanced state of development within the International Virtual Observatory Alliance. Structured data, as embodied in VOTables, are routinely by many VO-aware applications in use today. And formalisms for the representation of semantic content (in machine-interpretable form) are in development within the VO and larger scientific communities. I have a continuing interest in the definition of data and service standards, and anticipate engaging in their development and use in the years to come.
Success in major astronomical projects, be they scientific or technical, requires solid leadership and, increasingly, skilled management. This is especially true today, as both scientific and technical collaborations in astronomy have grown in size, complexity, diversity in participating institutions, and budget. Over the last two decades or so the importance of software engineering to the astronomy discipline has grown many-fold, to the point that it is nearly on par with other fields such as optical and mechanical engineering, and detector technology. It is hard to imagine a large modern observatory without complex, software intensive components to manage enclosures, instruments, data-taking systems, and science data management and processing systems. Advances in computing technology, data processing and modelling techniques, and world-wide investment in data archives has also transformed the nature scientific research. I have over the past decade developed software management skills, including course work in software engineering, and seminars communication, project management, budget development, supervision, and delegation.
When I joined NOAO in 2001 I took on a management role in the Data Products Program, whose responsibilities included building software in support of Gemini data reduction, IRAF system support, participation in the construction of the Virtual Observatory, the establishment of an archive for science data, and the construction of calibration pipelines for wide-field imagers. I was responsible for staffing (the program grew from 6 staff members to 17 during my involvement), budget development (the program budget grew from roughly $1 M in 2001 to $1.7 M in 2005), and overall project oversight. This role also required establishing memoranda of understanding and good working relationships with partner organizations, including the University of Maryland, who contributed in-kind programming support for pipeline and archive development, and the National Center for Supercomputer Applications as a partner in long-haul data transport, storage, and processing. I was also responsible for policy development in the areas of data rights, and for conditions of use for data and web services.