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The latest data release from the Gaia space observatory came out at 11am this morning, containing the positions of about 1.8 billion stars, and distances to 1.5 billion stars.
Earlier in the week, I was lucky enough to be allowed to interview the people in Cambridge who did the data analysis ahead of the release (I had to give them rather a lot of reassurances I wouldn’t break their embargo!).
The result was a 45-minute podcast, which I was allowed to release at 11am today: https://in-the-sky.org/news.php?id=20201203_04_100
Great excuse to open the champagne – I trust you enjoyed it!
Seriously – I see it is the ‘Early’ EDR3 that is released rather than DR3. Am hoping the photometric data is a big step-up from DR2, which itself was remarkably good. I just heard from the podcast that this will be the case – am thinking of switching to G magnitudes as standard in future work since this is a very good match with unfiltered observations and for comets and asteroids it makes for a very good match. We can always convert to some other photometric system if we know the relevant colour index. Great news.
Just checked:
The G-band photometric uncertainties in EDR3 are ~0.3 mmag for G<13, 1 mmag at G=17, and 6 mmag at G=20 mag.
In Data Release 2 from 2018 April, uncertainties were ~1.0 mmag for G<13, to around 20 mmag at G=20.
So that is a big improvement!Thanks for the clarification of G mag being a good match to unfiltered CCD photometry. I wasn’t 100% sure until now. There is a G* mag which is not the same as G ?
I’ll do some further tests of mags from my Watec 910 with IR/UV blocker. They look to be a reasonable match but I haven’t done a thorough check.
EDR3 is welcomed by many, but the occultation community is awaiting the improved asteroid orbits in the release of Gaia DR3.
Alex.
The G-band was never part of the standard Johnson-Cousins system, and so my understanding is that it’s not particularly standardised. In fact, professional observatories now tend to all have their own bespoke sets of filters, and so you can’t directly compare a PanSTARRS g with an SDSS g, for example. Though they’re very similar.
As I understand it, the Gaia G-band is indeed the unfiltered response of its CCD. Though, of course, Gaia doesn’t have any atmospheric extinction, so it won’t be a perfect match to anything you can get on the ground.
If one is being really pedantic, there are multiple different revisions of the Gaia G-band, as each data release includes improved instrumental corrections (which depend on colour). If you google for Gaia photometry you can find plenty of long gory papers about the process.
Papers exist on how to convert between the Gaia G, RP and BP measurements to other wide-band systems such as Johnson-Cousins. For example, see Appendix C and its two tables from https://arxiv.org/pdf/2012.01916.pdf for a detailed account.
I have a large number of unfiltered images with stars between 8th and 22nd magnitude, taken with two different CCD cameras. Perhaps I should measure them and see how well they correlated with DR3 values.
It is worth noting that while the G magnitudes are excellent, there are known small issues for bright blue stars and faint red stars. Details can be found in Riello et al 2020.
The bright blue stars are G<13 and BP-RP<0.1, appear to have an ‘anomaly’ of up to a few mmags.
The Gaia web pages provide Python to correct the systematic in fainter G magnitudes, G>13. This is not a major problem and in most cases will be very small except for redder stars. For example it can reach about the 1% level for about BP-RP>2, though at the extreme red end can reach 2.5%. I’m using a few million Gaia sources, and in my sample the official correction adjusted 1% of the stars by 1% in G. There is mention in the paper of a separate table in the Gaia archive for corrected G-band photometry, though I’ve not seen that yet and I wonder if it will appear in the coming days.
There also appears to be parallax zero point bias by magnitude, colour and position (Lindegren et al 2020). Again a Python script is provided to calculate this bias.
If anyone is interested in the Python corrections, then the source code can be found on the Gaia webpages here: https://www.cosmos.esa.int/web/gaia/edr3-code
This is not intended to take away anything from the Gaia results, which are amazing. It is usual for a major survey to have some small issues to be aware of, especially noting this is just an interim data release.
Andy
I think people here in Cambridge would say it’s an indication of just how good the Gaia data now is that all these biases can be measured and corrected.
None of these effects were measurable before, because they were entirely hidden in random noise. The measurements are now so stable and repeatable that these systematic skews start becoming apparent.
This is one of the reasons why so much work goes into every Gaia data release, and why successive data releases can’t simply come out at the push of a button. When you get rid of all the random noise, what’s left is the systematic noise, and that’s where the really hard work begins.
I work on the PLATO mission, and we’re seeing similar trends there. We set E2V the challenge of building the lowest-noise CCD they’ve ever made. What happened last year when they got rid of all the random thermal noise? They discovered entirely new leakage current patterns which no mission has ever seen before, because they’d always been entirely hidden in the noise before.
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