local linear regressions

For some reason, even though I dislike deep learning, I love local linear regressions. My friends tell me that RELU networks are locally linear, so I am really just a hypocrite. Anyway, today Adrian Price-Whelan and I built a regression in which we find nearest neighbors (among the training-set objects) in the space of ESA Gaia DR3 Bp/Rp spectral coefficients and, among those neighbors, we fit a locally linear model to predict the parallax of the test object. Technically we use a clever trick called the ”schmag“ but which should probably be called the reduced parallax, in which we correct the parallax into the inverse of the square root of the luminosity. Why? It's so we can use the parallax errors fairly, and include training-set objects with negative parallaxes.

Hill I will die on: If you cut your sample to high SNR parallaxes or positive parallaxes, you will bias any regressions you do to predict parallaxes or distances or distance moduli!


Gaia Hike, day 5

Today was day 5 of the Gaia Hike. Jason Hunt and I looked at a file of kinematic information prepared by Adrian Price-Whelan (Flatiron) to look at the possibility that the Milky Way has a low-amplitude counter-rotating disk of stars. We found nothing. This was in contrast to what Claudia Bielecki and Federico Sestito were finding—with a similar file created by George Kordopatis. By the time I had to leave the meeting, we hadn't resolved the discrepancy. It's interesting either way!


Gaia Hike, day 4

On day 4 of the Gaia Hike, Neige Frankel (CITA) and I tried to look for the signature of the Snail (the vertical phase spiral in the Milky Way stellar kinematics) in metallicity. It's visible in the Gaia Collaboration chemical cartography paper. But it's not trivial to find it. We got a tiny hint of it using RVS metallicities, and we resolved to try some more tomorrow. We also figured out that it should be there even if the Snail is a late production of a late interaction: Abundance gradients FTW.


Gaia Hike, day 3

Today was the literal hike day of the Gaia Hike. I couldn't go, for uninteresting technical reasons. So instead I spent my time preparing hack projects for those who are looking for straightforward hack ideas and want to learn. I got stuck many times and Adrian Price-Whelan (Flatiron) helped me un-stick. I guess straightforward isn't straightforward! Anyway, I produced this document which contains hack ideas. It is just a start, just a stub, but maybe it will be useful?


Gaia Hike, day 2

Today was day two of the Gaia Hike at UBC. The results of yesterday's discussions and hacking were discussed in the morning and then we moved to tutorials about how to use the ESA Gaia data responsibly. From my own personal perspective, the highlight was a big tutorial from George Seabroke (UCL) on the high-resolution RVS spectra. His presentation went through all the properties and issues with the data, including things like overlapping spectra on the focal plane. It was really impressive, incredibly useful, extremely detailed, and an amazing representation of how complex and challenging a mission like Gaia is. Congratulations to the entire DPAC for pulling this off!


Gaia Hike, day 1

Today was the first day of the Gaia Hike hosted at UBC and led by Neige Frankel (CITA). The day started with business cards (short intro talks from everyone), followed by an attempt to find common themes across participants. Once the themes were identified, we split into groups to talk about what we might do this week with the ESA Gaia DR3 data. I ended up in a mapping and visualization group, which was fun, and (of course!) we closed out the day hacking on a piece of the data on stellar parameters, trying to figure out why the stellar parameters don't look exactly as we expect.


coordinate freedom?

I spent the weekend recovering from the Gaia Fete. During my recovery day, I worked on very long-term projects. For example, I spent some time working on how to express the following issue in my work (with Villar) on exact symmetries:

The mathematics and computer-science communities call these exact symmetries “equivariances” and they are imagining that the data or the laws of physics are precisely equivariant in the sense that if you (say) rotate all the inputs, you get a rotated output. But this is not the main reason that we write the laws of physics in terms of exact symmetries! We write the laws of physics in terms of invariants because we want our laws of physics to be coordinate free. This is required even when the laws aren't equivariant! But I have trouble making this distinction clearly, since the mathematical implementations of the two symmetries are identical. There's some cool philosophy here: Does coordinate freedom enforce symmetries? What would it even look like for the laws of physics to be asymmetric but coordinate free?