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William O'Mullane

Publications and source records attributed to William O'Mullane.

26 records · Page 2Linked to original sources

The astrometric core solution for the Gaia mission. Overview of models, algorithms and software implementation

The Gaia satellite will observe about one billion stars and other point-like sources. The astrometric core solution will determine the astrometric parameters (position, parallax, and proper motion) for a subset of these sources, using a global solution approach which must also include a large number of parameters for the satellite attitude and optical instrument. The accurate and efficient implementation of this solution is an extremely demanding task, but crucial for the outcome of the mission. We provide a comprehensive overview of the mathematical and physical models applicable to this solution, as well as its numerical and algorithmic framework. The astrometric core solution is a simultaneous least-squares estimation of about half a billion parameters, including the astrometric parameters for some 100 million well-behaved so-called primary sources. The global nature of the solution requires an iterative approach, which can be broken down into a small number of distinct processing blocks (source, attitude, calibration and global updating) and auxiliary processes (including the frame rotator and selection of primary sources). We describe each of these processes in some detail, formulate the underlying models, from which the observation equations are derived, and outline the adopted numerical solution methods with due consideration of robustness and the structure of the resulting system of equations. Appendices provide brief introductions to some important mathematical tools (quaternions and B-splines for the attitude representation, and a modified Cholesky algorithm for positive semidefinite problems) and discuss some complications expected in the real mission data.

astro-ph.IM↗

IVOA Recommendation: IVOA Astronomical Data Query Language Version 2.00

This document describes the Astronomical Data Query Language (ADQL). ADQL has been developed based on SQL92. This document describes the subset of the SQL grammar supported by ADQL. Special restrictions and extensions to SQL92 have been defined in order to support generic and astronomy specific operations.

astro-ph.IM↗

Implementing the Gaia Astrometric Global Iterative Solution (AGIS) in Java

This paper provides a description of the Java software framework which has been constructed to run the Astrometric Global Iterative Solution for the Gaia mission. This is the mathematical framework to provide the rigid reference frame for Gaia observations from the Gaia data itself. This process makes Gaia a self calibrated, and input catalogue independent, mission. The framework is highly distributed typically running on a cluster of machines with a database back end. All code is written in the Java language. We describe the overall architecture and some of the details of the implementation.

astro-ph.IM↗

Using Java for distributed computing in the Gaia satellite data processing

In recent years Java has matured to a stable easy-to-use language with the flexibility of an interpreter (for reflection etc.) but the performance and type checking of a compiled language. When we started using Java for astronomical applications around 1999 they were the first of their kind in astronomy. Now a great deal of astronomy software is written in Java as are many business applications. We discuss the current environment and trends concerning the language and present an actual example of scientific use of Java for high-performance distributed computing: ESA's mission Gaia. The Gaia scanning satellite will perform a galactic census of about 1000 million objects in our galaxy. The Gaia community has chosen to write its processing software in Java. We explore the manifold reasons for choosing Java for this large science collaboration. Gaia processing is numerically complex but highly distributable, some parts being embarrassingly parallel. We describe the Gaia processing architecture and its realisation in Java. We delve into the astrometric solution which is the most advanced and most complex part of the processing. The Gaia simulator is also written in Java and is the most mature code in the system. This has been successfully running since about 2005 on the supercomputer "Marenostrum" in Barcelona. We relate experiences of using Java on a large shared machine. Finally we discuss Java, including some of its problems, for scientific computing.

cs.CE↗

ECSS in the eXtreme

The ESAC Gaia team engages in a form of eXtreme programming while the DPAC will follow a series of six month development cycles modeled on this approach. As a project within the European Space Agency the European Committee for Space Standardization (ECSS) standards are required. We present the bringing together of these realms.

astro-ph↗

There Goes the Neighborhood: Relational Algebra for Spatial Data Search

We explored ways of doing spatial search within a relational database: (1) hierarchical triangular mesh (a tessellation of the sphere), (2) a zoned bucketing system, and (3) representing areas as disjunctive-normal form constraints. Each of these approaches has merits. They all allow efficient point-in-region queries. A relational representation for regions allows Boolean operations among them and allows quick tests for point-in-region, regions-containing-point, and region-overlap. The speed of these algorithms is much improved by a zone and multi-scale zone-pyramid scheme. The approach has the virtue that the zone mechanism works well on B-Trees native to all SQL systems and integrates naturally with current query optimizers - rather than requiring a new spatial access method and concomitant query optimizer extensions. Over the last 5 years, we have used these techniques extensively in our work on SkyServer.sdss.org, and SkyQuery.net.

cs.DB↗

Extending the SDSS Batch Query System to the National Virtual Observatory Grid

The Sloan Digital Sky Survey science database is approaching 2TB. While the vast majority of queries normally execute in seconds or minutes, this interactive execution time can be disproportionately increased by a small fraction of queries that take hours or days to run; either because they require non-index scans of the largest tables or because they request very large result sets. In response to this, we added a multi-queue job submission and tracking system. The transfer of very large result sets from queries over the network is another serious problem. Statistics suggested that much of this data transfer is unnecessary; users would prefer to store results locally in order to allow further cross matching and filtering. To allow local analysis, we implemented a system that gives users their own personal database (MyDB) at the portal site. Users may transfer data to their MyDB, and then perform further analysis before extracting it to their own machine. We intend to extend the MyDB and asynchronous query ideas to multiple NVO nodes. This implies development, in a distributed manner, of several features, which have been demonstrated for a single node in the SDSS Batch Query System (CasJobs). The generalization of asynchronous queries necessitates some form of MyDB storage as well as workflow tracking services on each node and coordination strategies among nodes.

cs.DB↗