The AstroStat Slog » virtual observatory http://hea-www.harvard.edu/AstroStat/slog Weaving together Astronomy+Statistics+Computer Science+Engineering+Intrumentation, far beyond the growing borders Fri, 09 Sep 2011 17:05:33 +0000 en-US hourly 1 http://wordpress.org/?v=3.4 compressed sensing and a blog http://hea-www.harvard.edu/AstroStat/slog/2007/compressed-sensing-and-a-blog/ http://hea-www.harvard.edu/AstroStat/slog/2007/compressed-sensing-and-a-blog/#comments Thu, 25 Oct 2007 01:15:52 +0000 hlee http://hea-www.harvard.edu/AstroStat/slog/2007/compressed-sensing-and-a-blog/ My friend’s blog led me to Terrence Tao’s blog. A mathematician writes topics of applied mathematics and others. A glance tells me that all postings are well written. Especially, compressed sensing and single pixel cameras drags my attention more because the topic stimulates thoughts of astronomers in virtual observatory[1] and image processing[2] (it is not an exaggeration that observational astronomy starts with taking pictures in a broad sense) and statisticians in multidimensional applications, not to mention engineers in signal and image processing.

A particular interest of mine from his post is that compressed sensing could resolves bandwidth problems in astronomy and consequential sequential analysis on astronomical data (streaming data analysis). Overall, his list of applications at the end may enlighten scientists probing the sky with different waveband telescopes.

  1. see the slog posting “Virtual Observatory”
  2. see the slog posting “The power of wavedetect”
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model vs model http://hea-www.harvard.edu/AstroStat/slog/2007/model-vs-model/ http://hea-www.harvard.edu/AstroStat/slog/2007/model-vs-model/#comments Fri, 05 Oct 2007 17:38:23 +0000 vlk http://hea-www.harvard.edu/AstroStat/slog/2007/model-vs-model/ As Alanna pointed out, astronomers and statisticians mean different things when they say “model”. To complicate matters, we have also started to use another term called “data model”.

First, there is the physical model, which could mean either our understanding of what processes operate on a source (the physics part, usually involving PDEs), or the mathematical function that describes the emission as a function of observables like location, time, or energy (the astronomy part, usually the shape of the spectrum, or the time evolution in a light curve, etc.)

The data model on the other hand describes the organization of the observation. It is this which tells us that there is a fundamental difference between an effective area and a response matrix, and conversely, that the point spread function and the line response function are the same beast. This kind of thing, which I suppose is a computer science oriented view of the contents of a file, is crucial for implementing and running something like the Virtual Observatory.

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Beyond Google Sky http://hea-www.harvard.edu/AstroStat/slog/2007/beyond-google-sky/ http://hea-www.harvard.edu/AstroStat/slog/2007/beyond-google-sky/#comments Sat, 08 Sep 2007 18:31:42 +0000 vlk http://hea-www.harvard.edu/AstroStat/slog/2007/beyond-google-sky/ Google Sky is good for a quick look “what’s that you just saw over there?”, but not for anything more than that. Not yet anyway. Mind you, I think it is a good thing. It is easy to use, and definitely worth a look as an astronomy popularization tool. But there are a number of astro visualization programs that can (so to speak) beat the pants off Google Sky with one hand tied behind the back. Check these out (all open source):

XEphem : http://www.clearskyinstitute.com/xephem/
Celestia : http://www.shatters.net/celestia/
Stellarium : http://www.stellarium.org/

There are many more, of varying degrees of usefulness, user friendliness, and price. Your mileage will vary. But for sheer wow factor, hard to beat Celestia.

[Update 10/01]: The e-Astronomer considers how Google Sky could become more useful. Some interesting tie-ins to Virtual Observatory concepts.

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