[It's been a hard 2020. Apologies for my violations of the Rules to the right. I can assure you that it has been for a good set of reasons.]
I spent part of my research day listening to Adrian Price-Whelan (Flatiron) talk out a few different job talks. His challenge is to explain why we can learn things about the dark matter with streams. And explain why we can't! That is, streams are complicated.
In the latter part of our conversation I asked him if he could find APOGEE exposures of accelerating stars that are accelerating so strongly (from a binary orbit, say) that we could measure the velocity difference between the first half of the exposure and the second half. Why? Because the APOGEE observations are taken “up the ramp”; this makes it possible to split them after the fact. Any up-the-ramp imager takes data that can be sub-framed after the fact, which leads to all sorts of possible time-domain projects! Let's figure that out.
In Stars & Exoplanets Meeting today, we had a discussion about getting ready for ESA Gaia EDR3. What should we be doing? And Megan Ansdell (Flatiron) told us about using shallow-ish convolutional neural networks to find stellar flares in the presence of astrophysical noise.
Kind of like looking at streaking objects in an image. But WISE, which samples up the ramp, does not have enough bandwidth to transmit the individual samples, so only a slope image calculated onboard is transmitted. Still, the SUTR makes for non-uniform exposure of streaking objects. The ends of a streak are less heavily exposed.
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