conversations

Not much research today, but I did have conversations with Lauren Anderson (Flatiron) about deconvolving the observed (by Gaia TGAS and APASS) color-magnitude diagram of stars, with Leslie Greengard (Flatiron) and Alex Barnett (Dartmouth) about cross-over activities between CCA and CCB at Flatiron, and with Kyle Cranmer (NYU) about his immense NSF proposal.

deconvolution of labels

Lauren Anderson (CCA) and I discussed the state of our project to put spectroscopic parameters onto photometrically discovered stars using colors and magnitudes from APASS, parallaxes from Gaia TGAS, and spectroscopic parameters from the RAVE-on Catalog. We want to take the nearby neighbors in color-magnitude space and deconvolve their noisy spectroscopic parameters to make a less noisy estimate for (what you might call) the test objects. We have been using extreme deconvolution (Bovy et al.) for this, deconvolving the labels for the nearest neighbors (weighted by a likelihood). That is, find neighbors first, deconvolve second. After hours staring at the white board, we decided that maybe we should just deconvolve all the inputs up front, and do inference under the prior created by that deconvolution. Question: Is this computationally feasible?

substructures, spots, gender, filtering, and more

Today was the usual action-packed day at the CCA. Before the group meetings, Lauren Anderson (CCA) showed me work on stellar twins in photometric (APASS + Gaia) space, and how similar they are in RAVE-on spectroscopic parameters. It looks like she might be able to put (through a machine-learning-like method) spectroscopic parameters on every star in TGAS. This would be yet another data-driven model of stars.

At stars group meeting, Tjitske Starkenburg (CCA) and Keith Hawkins (Columbia) discussed this paper about chocolates which seems to be the only paper so far about new substructures in the Gaia data. There was some discussion about how they converted parallax to distance (apparently Binney has an opinion), and how the sub-structure is found via a cross-correlation between the data and random realizations. The evidence is a bit weak. However, some of the substructures look worth following up in chemistry and in other stellar samples.

This was followed by Michael Gully-Santiago (formerly Kavli, Beijing) showing his work on figuring out the ages and masses of really young (few Myr) stars, and (more ambitiously) getting the spectra of star spots on their surfaces! His project is very related to our spectroscopic binary work: How to measure a cold spot on a hot star? His approach is to modify the (Czekala et al) Starfish code to also fit for cold patches (at the same metallicity and logg as the main surface). For his particular case (LkCa-something), he finds a preference for a spot temperature of 2700-ish K covering 80-ish percent (!) of the star. This was followed and interrupted by lots of discussion about stellar binaries, long-term evolution, longitude effects, and so on.

Between group meetings, Sandro Tacchella (ETHZ) talked about his paper on gender bias in astronomy. The paper gathers good data, and is (properly) limited in its conclusions. It ends with a relatively sophisticated causal inference that is fairly convincing that women are cited less than men for papers with otherwise similar properties. This involved building a predictive model for citations. That led to a good discussion!

In the cosmology group meeting at the end of the day, Kris Sigurdson (UBC, NYU) spoke about CHIME 21-cm observations and foreground mitigation. Foregrounds should be smooth in the frequency direction, unlike the narrow-band 21-cm emission. We discussed the differences between filtering-like (or K-L-like) techniques that deliver minimum-variance modes, and subtraction-like techniques that try to build an explicit model of the foregrounds. We vowed to continue the discussion.