Note: This Thursday issue would normally be only for Premium subscribers, but it’s an important topic so I’m sending the bulk of it to free subbies as well, with most of the info “above the fold”. Enjoy!

The largest survey of the sky ever undertaken has now begun. The Vera C. Rubin Observatory’s monster 8.4-meter telescope has opened its eye and is now taking routine images of the night sky.

Does that not sound like that big a deal? What if I tell you the camera it’s using has 3.2 billion pixels — yes, billion — and takes an image of the sky every 40 seconds? And that the patch of sky it sees in every image is a rough circle 50 times the area of the full moon on the sky? And it will scan the entire southern sky in about three nights, then repeat the process for many years?

Yeah. This will be a game changer.

The idea is to look for transients, objects that change in brightness and/or position. That includes asteroids, comets, trans-Neptunian objects, flaring black holes, stars just orbiting the Milky Way’s center, and much, much more. And it will do this with very keen eyesight indeed, with a resolution (the ability to split two objects very close together) of just 0.3 arcseconds, which is a very tiny amount: the human eye has a resolution of about 60 arcseconds. Hubble has a resolution of 0.05 arcseconds, and it’s in space where there’s no atmosphere to muck up the images. So Rubin has excellent vision.

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Astronomers already released some test images last year, and they were spectacular, but the difference now is that the telescope is automatically surveying the sky, taking image after image. These can then be compared to look for anything that changed. This has to be done by computers, of course; no human could possibly go through that much data. That is how it was done back in the day; in the late 1920 and early 30s Clyde Tombaugh discovered Pluto by blinking back and forth between two photographs of the night sky, looking for anything that moved. I’ve done this sort of thing as well, and it’s incredibly tedious.

Now try it for three billion pixels. Yeah.

This Rubin survey is called the Legacy Survey of Space and Time^* , and here’s the first release image from it: 

I know, it just looks like a chunk of night sky, right? But that’s because I had to shrink it to a thousand pixels wide to fit this newsletter. The high-resolution image is — and I can hardly believe I’m writing this — 56,428 x 29,949 pixels. That’s 1.7 billion pixels. Holy moly. It’s a 9.4 gigabyte file, so it may take a while to download, too. I did, but it’s so big my ancient version of Photoshop gagged on it. I was able to get The GIMP to read a lower-res version (a mere 6.4 Gb) — barely — so I cropped out a tiny piece to display below. It’s actually over 3,000 pixels wide, but again I had to shrink it to fit here, so the original is actually far higher-resolution than this: 

Yegads. So many stars! And galaxies! That feathery mist you see is what’s called galactic cirrus (it used to be called integrated flux nebula, which is more fun); extremely tenuous dust and gas that is illuminated by background starlight. That stuff is faint, and to see it so clearly here is a testament to the power of this survey.

There’s another aspect to this as well, which is not being covered as much, but was mentioned in the press release. It’s about how deep the images can get. By that astronomers mean how faint an object you can see in the images.

When you take a single image, even a long exposure, there’s a problem with noise. This has many sources, but it means fluctuations in the brightness of an image caused by a combination of random processes and internal issues with the camera. An exposure of a faint source, for example, might only get a few photons per second. That stream is not perfectly consistent, though. It might have 5 photons in the first second, but 3 in the next, then 10. That’s called photon noise, and for the super nerds among you it’s a Poissonian process. The fluctuations have a statistical relation, which goes by the square root of the number seen.

If you see, say, 100 photons total, then you expect a standard deviation of 10 photons, which means that the difference between seeing 90 and 110 photons isn’t statistically significant. But if you see 10,000 photons, the square root of that is 100, so in that case 9,900 and 10,100 photons is the expected random range seen, which is much tighter percentage-wise even though the numbers themselves are larger. So the <tl;dr> of this is, the more photons you get, the smaller the random fluctuations are, and the cleaner your image is. 

The folks at NOIRLab (who are the caretakers of the Rubin data) provided a nice example of this:

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