News | Kepler satellite and citizen planet hunters

April 15, 2011

Excerpt: While computers are terrific at high-volume data-processing, nothing beats the human eye for pattern-recognition – which is why a project dreamed up by Yale University astronomer Debra Fischer, a veteran planet hunter and Kepler project scientist, has turned out to be so extraordinarily useful. Called Planethunters.org, it lets ordinary folks with no scientific training at all help find planets the Kepler software has missed. It works so well that in just a few short months of operation, the more than 22,000 visitors to the website have found nearly 50 potential planets, which are being sent on to Kepler headquarters at the NASA Ames Research Center in California for followup.

Full story

Source: Yahoo / Time


Tools | An iPhone App for Variable Stars

January 16, 2011

Over the past few months, while I have been sadly neglecting the Data Mining for Astronomy website (apologies for that), I have been working in collaboration with my friend Mark McGettrick and the American Association of Variable Star Observers (AAVSO) to develop an iPhone app for Variable Stars, and other data-centric iPhone apps.

As we all know, in the past 10 years, the ubiquitous availability of data repositories, and the commensurate opportunities for statistical analysis and data-mining has transformed both astronomical and biomedical research. Our idea was to develop a reusable application framework that would enable us to “mobilize” datasets on to the Apple iOS platform. The underlying framework allows us, as developers, to define the meta-data content of a given dataset, and then to rapidly transform this into an iPhone app, giving users the ability to:

  • query the data
  • sort results, and
  • view the details of individual records.

So you describe the content of the dataset, and certain interfaces are generating automatically including filter / query controls and sorting criteria.   Presenting the details of a particular record does still require a certain degree of customization in order to render object attributes in a manner that a domain-expert would expect.    But we are hoping to develop, as part of the framework, certain pre-defined templates that will further reduce the coding effort involved.   As this is an astronomical application, we have also developed specific extensions to support object visibility based on the observer’s geographical location and date/time.  Going forward, we plan to make it possible to generate correlation plots, bar charts, and other visualizations, and to generate various types of statistical analyses, all towards the broader goal of creating a mobile data-mining framework for astronomical and biomedical applications.   So far, reviews of the app have been very positive!

Stay posted!

Details of a particular star

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UniMap – Identify objects in any astrophotograph

July 10, 2010

Imagine you have a non-descript photograph of a star field and you want to identify every light source in the image:  including stars, multiple stars, novae, asteroids, comets, galaxies and other deep sky objects.    That is exactly what a new program called UniMap can do!  The program performs this little piece of magic by first scanning the photograph for all detectable light sources, then attempting to cross-match the pattern of light sources against existing source catalogues.     You can significantly improve the performance of the identification algorithms by providing hints about what is in the photograph, for example, a constellation, star, deep-sky object and the field of view.  I should mention that the program is not quite production-ready, but the developer, Larry Lart, has made a “pre-alpha” release available to the general public for testing.   I spent some time testing UniMap on a random wide field photograph of the sky I had taken  years ago and the program worked quite well.   It represents a very impressive demonstration of what can be done with public access to astronomical catalogs (and a talent for software development!)


Cost-effective Catalina

September 25, 2009

The Catalina Sky Survey is a NASA-funded effort to identify near-earth objects, or NEOs, whose orbits cross the path of the Earth and are potentially hazardous. We have talked about NASA’s NEO program in a past posting. The Catalina is a relatively small operation responsible for 70 percent of NEO discoveries over the past three years. The survey team recently announced a new $890,000 NSF grant to expand the objectives of the effort to include optical transients whose brightness changes over time. This will be known as the Catalina Real-Time Transient Survey, or CRTS. To date, the CSS has identified over 700 of these objects, including supernovae, cataclysmic variables, and blazars.

From the press release:

The Catalina Real-Time Transient Survey will be the first and only fully public synoptic sky survey, team members say. It’s a bargain-rate boon to astronomers who are trying to figure out how to manage enormous data streams to be delivered by future synoptic sky survey telescopes, such as Pan-STARRS and the LSST, they add.

And quoting from the CRTS website itself:

The Catalina Real-Time Transient Survey is a synoptic astronomical exploration that covers tens of thousands of square degrees of the sky in order discover rare in interesting transient phenomina. The survey utilizes data taken by the three dedicated telescopes of the highly successful Catalina Sky Survey (CSS) NEO project. CRTS detects and openly publishes all transients within minute of observation so that all astronomers may follow ongoing events.

webschmidt_b

From the CSS website

What is so ground-breaking about this survey is not simply its mission, but also its laudable goal of making all data freely and immediately available to the public; exactly what is necessary to foster interdisciplinary work. Furthermore, the survey will provide a testing ground for technologies being developed for larger-scale surveys such as LSST and Pan-STARRS. Congratulations to the Catalina team for their continued success!


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