Sherpa: a Mission-Independent Data Analysis Application

The ever-increasing quality and complexity of astronomical data underscores the need for new and powerful data analysis applications. This need has led to the development of Sherpa, a modeling and fitting program in the CIAO software package that enables the analysis of multi-dimensional, multi-wavelength data. In this paper, we present an overview of Sherpa's features, which include: support for a wide variety of input and output data formats, including the new Model Descriptor List (MDL) format; a model language which permits the construction of arbitrarily complex model expressions, including ones representing instrument characteristics; a wide variety of fit statistics and methods of optimization, model comparison, and parameter estimation; multi-dimensional visualization, provided by ChIPS; and new interactive analysis capabilities provided by embedding the S-Lang interpreted scripting language. We conclude by showing example Sherpa analysis sessions.Comment: To appear in Proc. SPIE Conf. 4477. 12 pages, 4 figure

Iris: an Extensible Application for Building and Analyzing Spectral Energy Distributions

Iris is an extensible application that provides astronomers with a user-friendly interface capable of ingesting broad-band data from many different sources in order to build, explore, and model spectral energy distributions (SEDs). Iris takes advantage of the standards defined by the International Virtual Observatory Alliance, but hides the technicalities of such standards by implementing different layers of abstraction on top of them. Such intermediate layers provide hooks that users and developers can exploit in order to extend the capabilities provided by Iris. For instance, custom Python models can be combined in arbitrary ways with the Iris built-in models or with other custom functions. As such, Iris offers a platform for the development and integration of SED data, services, and applications, either from the user's system or from the web. In this paper we describe the built-in features provided by Iris for building and analyzing SEDs. We also explore in some detail the Iris framework and software development kit, showing how astronomers and software developers can plug their code into an integrated SED analysis environment.Comment: 18 pages, 8 figures, accepted for publication in Astronomy & Computin

Managing Distributed Software Development in the Virtual Astronomical Observatory

The U.S. Virtual Astronomical Observatory (VAO) is a product-driven organization that provides new scientific research capabilities to the astronomical community. Software development for the VAO follows a lightweight framework that guides development of science applications and infrastructure. Challenges to be overcome include distributed development teams, part-time efforts, and highly constrained schedules. We describe the process we followed to conquer these challenges while developing Iris, the VAO application for analysis of 1-D astronomical spectral energy distributions (SEDs). Iris was successfully built and released in less than a year with a team distributed across four institutions. The project followed existing International Virtual Observatory Alliance inter-operability standards for spectral data and contributed a SED library as a by-product of the project. We emphasize lessons learned that will be folded into future development efforts. In our experience, a well-defined process that provides guidelines to ensure the project is cohesive and stays on track is key to success. Internal product deliveries with a planned test and feedback loop are critical. Release candidates are measured against use cases established early in the process, and provide the opportunity to assess priorities and make course corrections during development. Also key is the participation of a stakeholder such as a lead scientist who manages the technical questions, advises on priorities, and is actively involved as a lead tester. Finally, frequent scheduled communications (for example a bi-weekly tele-conference) assure issues are resolved quickly and the team is working toward a common visionComment: 7 pages, 2 figures, SPIE 2012 conferenc

Derivation and maintenance of mouse haploid embryonic stem cells.

Ploidy represents the number of chromosome sets in a cell. Although gametes have a haploid genome (n), most mammalian cells have diploid genomes (2n). The diploid status of most cells correlates with the number of probable alleles for each autosomal gene and makes it difficult to target these genes via mutagenesis techniques. Here, we describe a 7-week protocol for the derivation of mouse haploid embryonic stem cells (hESCs) from female gametes that also outlines how to maintain the cells once derived. We detail additional procedures that can be used with cell lines obtained from the mouse Haplobank, a biobank of >100,000 individual mouse hESC lines with targeted mutations in 16,970 genes. hESCs can spontaneously diploidize and can be maintained in both haploid and diploid states. Mouse hESCs are genomically and karyotypically stable, are innately immortal and isogenic, and can be derived in an array of differentiated cell types; they are thus highly amenable to genetic screens and to defining molecular connectivity pathways.UK Dementia Research Institute fellowship (MC_PC_17111)

The human Holliday junction resolvase GEN1 rescues the meiotic phenotype of a Schizosaccharomyces pombe mus81 mutant

A key step in meiotic recombination involves the nucleolytic resolution of Holliday junctions to generate crossovers. Although the enzyme that performs this function in human cells is presently unknown, recent studies led to the identification of the XPG-family endonuclease GEN1 that promotes Holliday junction resolution in vitro, suggesting that it may perform a related function in vivo. Here, we show that ectopic expression of GEN1 in fission yeast mus81Δ strains results in Holliday junction resolution and crossover formation during meiosis

Perspective Chapter: Validation of SMOS Satellite Soil Moisture Estimates Using Capacitance Probes over the Different Ecological Zones in Northern Ghana

Researchers assessed the performance of L2 satellite soil moisture estimates from the European Space Agency’s SMOS satellite using in-situ data from capacitance SM probes. The in-situ measurements are from monitoring stations (at 10, 20, 30 cm depth) at two sites, Yendi and Jirapa in the Northern part of Ghana, West Africa. They are in two different sub-ecological zones of the Savanna in the North of Ghana. These sub-ecological zones are Western Sudan Savanna (Jirapa) and Open Guinea Savanna (Yendi). The correlation between SMOS SM estimates and the in-situ measurements was observed to improve with depth. In addition, the 10 cm depths capacitance probe SM measurements were observed to agree relatively better with the SMOS SM estimates. The L2 SMOS SM estimates performed much better in the dry season compared to the rainfall season for both ascending and descending orbital estimates. The 10 cm depth SM measurements recorded the best RMSE in both the dry and rainfall seasons. The descending dry season RMSE for the two sites ranging between 0.045 and 0.058 m3/m3 was relatively close to the SMOS expected accuracy. However, the RMSE and MBE were observed to deteriorate with depth

Statistical Characterization of the Chandra Source Catalog

The first release of the Chandra Source Catalog (CSC) contains ~95,000 X-ray sources in a total area of ~0.75% of the entire sky, using data from ~3,900 separate ACIS observations of a multitude of different types of X-ray sources. In order to maximize the scientific benefit of such a large, heterogeneous data-set, careful characterization of the statistical properties of the catalog, i.e., completeness, sensitivity, false source rate, and accuracy of source properties, is required. Characterization efforts of other, large Chandra catalogs, such as the ChaMP Point Source Catalog (Kim et al. 2007) or the 2 Mega-second Deep Field Surveys (Alexander et al. 2003), while informative, cannot serve this purpose, since the CSC analysis procedures are significantly different and the range of allowable data is much less restrictive. We describe here the characterization process for the CSC. This process includes both a comparison of real CSC results with those of other, deeper Chandra catalogs of the same targets and extensive simulations of blank-sky and point source populations.Comment: To be published in the Astrophysical Journal Supplement Series (Fig. 52 replaced with a version which astro-ph can convert to PDF without issues.