binarystargazer

Most of the artifacts you see are actually asteroids. We don't take all the colors at once when making an image. The ccds just count photons that fall on them, so we have giant glass filters that allow specific wavelengths through. We then image the fields multiple times with multiple filters and then map the wavelengths of light into color images (see other post about trying to make them as perceptually correct as possible). However, because taking multiple images over time means that things which are changing (i.e. moving asteroids) not not appear at the same places when we combine them. Most of the time these time changing effects get filtered out in the combination step, but sometimes if they are bright enough, or persistent enough the make it through.

As an FYI, you can right click in the sky viewer and it will show the coordinates of the object, and there is a button to copy a shareable link that will take anyone right to where you are looking in the sky.

If you click on the search icon, there are some quick links to fields across the sky so you don't need to scroll as much. There are some interface tweaks and ui stuff that will be coming down stream that will help with some of this as well.

I have a publication that will be done soon™. I have been preparing it for a while, but I keep finding edge cases to fix, and ways to make things even better that I keep changing things fast enough that I need to re-work the paper. The code to produce it will all be open source, and I am even working on making it an independent package you can install separately from the rest of our software stack, specifically so other places can easily install and use it in all sorts of environments.

It's funny you mention HDR, I am _just_ about finished with the HDR extension to the image processing code. What you see in the sky viewer is all standard SDR formats. As you suspect it makes a HUGE difference. Once this is all done we will be working on rolling out many different ways to experience it. The HDR code path will also be part of the package and is not much different to use than the standard stuff.

Reading your comment has gotten me a little more energized to make more progress on this this morning.

We are getting pretty far outside my area of expertise / knowledge on this topic here, but I know I and others agree with you here. There is a Rubin Observatory data access policy out there. Don't quote me on the exact specifics but I believe that most colleges and research institutions already have a mechanism to enable data access setup, or can get one. This is mostly an id auth type thing to make sure those accessing have data rights. There is a policy where people not associated with those can request access too, but I am not sure the procedure and would not be qualified to weigh in on anything more specific.

They are both fairly rare, and or like you said wrong scale (for this data release at least). There is actually one in this field, but it is below the noise floor of this image, it is very small and very faint. There will be others in the future that will be easier to see. By the end of our survey we will have about 40,000 sq deg (a bit over half the night sky) looking like what you see here.

Be sure you and your daughter click the search icon, there are a few other fields of stuff you can check out. The links in the search will take you there without needing to scroll around the big black sphere.

I hope your daughter enjoys it, and we have a few activities at https://rubinobservatory.org/education/first-look-lasting-im... including a coloring book.

You want to check out the early science release info at https://rubinobservatory.org/for-scientists/resources/early-... . This is all early science from preliminary data. It is mostly to help people ramp up developing their software against the type of things they will be seeing in the future. There some known issues and gotchas outlined in the release. Hopefully this will be enough to whet your appetite. The data seen in this sky viewer is part of the Data Preview 2.

I’m the person in the chain that takes the scientific data and maps it into these color images used in the viewer (among other responsibilities). I spent a long time researching and developing the software that as close as possible maps the data into human perception. It means so much to see people out there appreciating our work, and following what Rubin will achieve. So that you for taking your time to check it out!

You are not wholly wrong! There is both a supporting structure for the mirror, AND a glass lens in front of the sensor to further flatten the incoming light.

The interesting thing about the spikes in our images is that they stay fixed in image plane coordinates, not sky coordinates. So as the night sky moves (earth rotates) the spikes rotate relative to the sky leading to a star burst pattern over multiple exposures.

The filters used for this range from near infrared to near uv. We used 4 different filters in all (for this image, the telescope has more). In general yes to fully appreciate all the color information as a human we need to generate different color combos so our eyes can pick up different contrasts.

However, what we strive for is being accurate to "if your eyes COULD see like this, it would look like this". To the best our our ability of course. We did a lot of research into human perception to create this and tired to map the information of color and intensity in a similar way to how your brain constructs that information into an image.

Let me tell you, I did not appreciate how deep a topic this was before starting, and how limited our file formats and electronic reproduction capabilities are for this. The data has such a range of information (in color and intensity) it is hard to encode into existing formats that most people are able to display. I really want to spend some time to do this in modern HDR (true HDR, not tone-mapping) where the brightness can actually be encoded separately than just RGB values. The documentation on these (several competing) formats is a bit all over the place though.

Edit: I wanted to edit to add, if anyone reading this is an expert in HDR formats and or processing, I'd live to pick your brain a bit!

Image creator here. We do dark field subtraction, as well as many other instrumental calibrations. What you are seeing is the fundamental photon noise. Because it is statistical in nature, you can never completely eliminate it. We could have chosen to put the black point in the image at a much higher flux level, but if you go to a high enough signal to noise level that you see no grain anywhere, you would miss out on so many interesting things that are still quite obvious to make out but are only 2-3 sigma above the noise.

Image creator here. Now imagine, when the survey is done, we will be able to see even fainter objects and image an area of the sky 1000x times this size.

Image creator here. This is such a massive dataset, most of the image processing needed to be custom written software pipelines. It not really practical for every pixel to be hand inspected. A few defects (and bright asteroids) imprinted through. It really hard to decide what is a real weird thing in the universe, and what is some sort of instrumental effect. We try to not pre-decide on what we think we should be seeing and filter for those by using things such as using classifiers. That leaves us with heuristics based on temporal information, size (is it smaller than a point spread function), and other related things. On large numbers of objects and pixels 1 in a thousand or 1 in a million outliers are bound to occur.

I agree their results are also great! We do go a bit deeper, but he big difference it the speed we are able to build these images. We are able to image a larger area of the sky in each exposure, and are able to collect more light. This will lets us build images like this one in a few hours of observation, and build up an equivalent image of the entire southern hemisphere.

I'm the Rubin team member responsible for mapping the data into RGB images. I have been a long time reader of hacker news, but finally made an account to comment on this. I wanted to thank everyone here for their interest and taking their time to check out these images. Seeing everyone interested and engaged makes all the long hours worth it.