The Astronomical Event Search Engine
eldavojohn writes "Google has signed on with the Large Synoptic Survey Telescope project that will construct a powerful telescope in Chile by 2013. Google's part will be to 'develop a search engine that can process, organize, and analyze the voluminous amounts of data coming from the instrument's data streams in real time. The engine will create "movie-like windows" for scientists to view significant space events.' Google's been successful on turning its search technology on several different media and realms. Will they be successful with helping scientists tag and catalog events in our universe?" The telescope will generate 30 TB of data a night, for 10 years, from a 3-gigapixel CCD array.
I actually did a small, insignificant portion of LSST's computation feasability study at LLNL during my internship there a couple summers ago. And yeah, the computational requirements were nothing to sneeze at. I'm not sure where they are at now, the specs changed seemingly every month, but when I left the CCD array was up to 3 gigapixels of 16 bit greyscale. I believe the observing cadence (at that time, again everything was changing on a regular basis) was two of those for the same piece of sky every 30 seconds. Wish I could have stayed... ahh well. I did get a really nice full-color research poster (that I had to design) out of it though!
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You can't compress this stuff unless you do it losslessly. Compression artifacts mess up photometry - if you're trying to compute apparent brightness, you need to factor in things like how bright the ambient sky is, and how much point sources get spread out (FWHM, seeing). That is, a point source that passes through the atmosphere looks like a normal probabliity distribution because of atmospheric distortions. So to get an apparent brightness, you have to correct for this effect. If compression artifacts are introduced, FWHM is thrown off, and you have no idea how "crisp" your image really is. That's why these data sets are so large. Quite literally, they're doing a pixel dump from their massive ccd all night. But hey, somehow I doubt they'll be using this telescope for anything but object detection. There's no reason to store it all except to compare a current picture to one in a base set, kinda like KAIT on stearoids.
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Africus aut Europaeus?
That's a lot of data, but it's less than 1/10 as much data as the Large Hadron Collider will put out, and the LHC is supposed to be coming online within a year, not in six years. By the time the Large Synoptic Survey Telescope comes online, the LHC may have produced more data than the Large Synoptic Survey Telescope will over the life of the project.
I'd be interested to know more about the data handling methods they have in place for the LHC. I don't think they'll be using Excel.
*Note the correct, non-Frudian-Slip spelling of "hadron"
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The shop I'm at has been working the image processing and data storage problem for PanSTARRS, another sky survey project that is a bit further along (they have a test scope up and running on Maui). It's interesting to me that both projects are at once using conventional solutions and thinking outside of the box.
Conventional: LSST will use a single large telescope and detector; PanSTARRS (as it stands) intends to use a dedicated compute cluster for data reduction.
Novel: LSST is leaning towards distributing its data reduction task over Google's huge server farm; PanSTARRS will use four off-the-shelf 1.8m telescopes, each with a 1.4GP detector, mounted together to image the same piece of sky, and merging the overlapping images in post processing.
When I was working on the project, one of PanSTARRS requirements was to finish analyzing one night's viewing before the following sunset. Early on, the principal investigators decided to solve the image storage issue by not storing them permanently. Instead, once the science for a night's imaging had been extracted (astrometry, LEO or supernova detection, etc), the original images would hit the bit bucket. Whether they've stuck with that I don't know.
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That's a lot of info.
No, that's a lot of data. Info is the result of analysing the data.