Dr Tomer Yavetz

Today Tomer Yavetz (Columbia) defended his PhD, which was in part about the dynamics of stellar streams, and in part about macroscopically quantum-mechanical dark matter. The dissertation was great. The stellar-stream part was about stream morphologies induced by dynamical separatrices in phase space: If the stars on a stream are on orbits that span a separatrix, all heck breaks loose. The part of the thesis on this was very pedagogical and insightful about theoretical dynamics. The dark-matter part was about fast computation of steady-states using orbitals and the WKB approximation. Beautiful physics and math! But my favorite part of the thesis was the introduction, in which Yavetz discusses the point that dynamics—even though we can't see stellar orbits—does have directly observable consequences, like the aforementioned streams and their morphologies (and also Saturn's rings and the gaps in the asteroid belt and the velocity substructure in the Milky Way disk). After the defense we talked about re-framing dynamics around this idea of observability. Congratulations, and it has been a pleasure!

optimization is terrible

I had a great conversation this morning with Kiyan Tavangar (Chicago) and Adrian Price-Whelan (Flatiron) about finding a dynamical model for the GD-1 stellar stream and the (purported) compact mass perturber that distorted the stream. They are building a likelihood function and trying to optimize in the kinematic parameters of the perturber. But it's hard! Because every model involves a full forward model for the stream, and how do you compare a particle simulation to a set of observed stars? We've worked on problems like this for years, and we don't have extremely satisfying answers. But the question we talked about today is: Even once you have a good likelihood function implementation: How to initialize the optimization? My position is that optimization needs to be principled, but initialization of that optimization can be arbitrarily nasty. We discussed nasty options. My experiene is that optimization is the hardest part of many of the projects I've done in my life.

streams in external galaxies

Sarah Pearson (NYU), Adrian Price-Whelan (Flatiron), and I met today to discuss fitting tidal streams (and especially cold stellar streams) discovered around external galaxies. We are starting with the concept of the stream track, and therefore we need to turn imaging we have of external galaxies into some description of the stream track in some coordinate system that makes sense. We spent time discussing that. We're going to start with some hacks. This isn't unrelated to the work I have been discussing on microscopy of robots: We want to make very precise measurements, but in very heterogeneous, complex imaging.

is leading-order time dependence spirally?

Independently, Kathryn Johnston (Columbia) and David Spergel (Flatiron) have pointed out to me that if you have a Hamiltonian dynamical system that is slightly out of steady-state, you can do a kind of expansion, in which the steady-state equation is just the zeroth order term in an expansion. The first-order term looks like the zeroth-order Hamiltonian acting on the first-order perturbation to the distribution function, plus the first-order perturbation to the Hamiltonian acting on the zeroth-order distribution function (equals a time derivative of the distribution function). That's cool!

Now couple that idea with the fact that a steady-state Hamiltonian system is a set of phase-mixed orbits nested in phase space (literally a 3-torus foliation of 6-space). Isn't this first-order equation the equation of a winding-up spiral mode? I think it is! If so, it might unite a bunch of phenomenology, from cold stellar streams to spiral structure in the disk to The Snail. I discussed all this with Adrian Price-Whelan (Flatiron).

stream finding

Stars and Exoplanets meeting at Flatiron (well on xoom, really) was all about finding stellar streams. Matt Buckley (Rutgers) talked about repurposing to the astrophysical domain machine-learning methods employed in high-energy physics experimental data to find anomalies. Sarah Pearson (Flatiron) talked about building things that evolve from Hough transforms. In both cases we (the audience) argued that the projects should make catalogs of potential streams with low (non-conservative) thresholds: After all, it is better to find low-mass streams plus some junk than it is to miss them: Every stream is potentially uniquely valuable.

Gaia EDR3

Today ESA Gaia EDR3 dropped! It was a fun day; the data are more precise and less noisy! I'm involved in a few different projects with the data. With Hunt (Flatiron) and Price-Whelan (Flatiron) I am looking at the local velocity-space structure in the disk, and seeing if we can classify features by looking at how they vary spatially around the Solar position. With Eilers (MIT) I am going to update our spectrophotometric distance estimates to APOGEE luminous red giants. With Bonaca (Harvard) I will find out if we can improve the kinematics and orbit identification of stellar streams. None of these projects got very far today, but we did make this visualization!

getting ready for EDR3: cold streams

ESA Gaia EDR3 is next week! I have been trying to get ready in various ways. Today Ana Bonaca (Harvard) showed me remarkable evidence that the cold stellar streams in the Milky Way halo are clustered in kinematic space, maybe also with the halo globular clusters! We discussed things to do in this area. It's perfect for EDR3 because if the clustering is real, it should improve with the improved precision of the EDR3 data.

Oort constants and the first-order MySpace

Today we realized or re-realized that the linear terms in our MySpace project (the project to find the coordinate transformation that maximizes the informative-ness of the velocity sub-structure in the Milky Way disk) are just the Oort constants, or a generalization thereof. But since they maximize the velocity structure, they don't necessarily mean, for us, what Oort expected them to mean. We also got the method working to first order. Or I should say that Adrian Price-Whelan (Flatiron) did. He made use of jax, the auto-differentiation package for Python. It's impressive.

rebooting MySpace

Some people of a certain age will know what it means when you say that MySpace is dead. But the statement is wrong! Today Jason Hunt (Flatiron) rebooted an old project by Price-Whelan and mine called MySpace. The motivation for our reboot: The upcoming ESA Gaia EDR3.

The idea is to figure out how the velocity-space structure (the moving groups, as it were) in the local disk varies with position, with a data-driven model, and then interpret the variations with position in terms of dynamical properties of the Milky Way. Hunt's innovation is to apply this same procedure to simulations as well as data, and use the output to classify the velocity substructure (classify as in: Does it come from resonances or disrupting clusters or what?). We discussed some of the math and optimization involved. Because we phrase this as the fitting of an expansion.

MySpace for Gaia eDR3

I talked to Jason Hunt (Flatiron) this afternoon about things we might do with the ESA Gaia early-DR3 data (December 2020), which will be similar to DR2 but with improved parallaxes and proper motions. In 2022 we'll get the complete DR3, which contains lots of qualitatively new data and measurements. But in the meantime, eDR3 is great for projects that we did—or tried to do—in DR2 but were limited by proper-motion precisions (especially, since proper motions get better by a lot). One such project is work Hunt did with Bovy on velocity substructure in the disk. So I pitched to him the MySpace project that Price-Whelan and I formulated a while back. I have an intuition that it should work well with the new data.

Is the snail two snails?

Friday mornings in NYC usually start with a free-form meeting on the 11th floor of Flatiron. Today Spergel, Johnston, Gandhi, and Price-Whelan were all at the table. We began by discussing some of the accomplishments that have set the tone and agenda of the data-group and dynamics-group activities at Flatiron. Then we started to discuss what I call The Snail: The phase spiral found by Antoja in the ESA Gaia DR2 data. As my loyal reader knows, we are trying to use it to infer the dynamical properties of the Milky Way disk. And we would also like to use it to infer things about events in the recent past of the Milky Way. We discussed the possibility (suggested by the observations) that The Snail is not just one event but really two. It looks different when you look at stars with different angular momenta (different guiding centers, and hence different histories in their orbits around the Milky Way). In general the question is: Do Snails created in simulated galaxies look anything like the Snail we have?

splitting exposures after the fact

[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.

disk–halo (and halo–halo) mean-velocity differences

I had a meeting with Emily Cunningham (Flatiron) to discuss any projects of mutual interest. She has been looking at simulations of the Milky Way (toy simulations) in which the LMC and SMC fall in. These simulations get tidally distorted by the infall, and various observational consequences follow. For example, the disk ends up having a different mean velocity than the halo! And for another, different parts of the halo move relative to one another, in the mean. Cunningham's past work has been on the velocity variance; now it looks like she has a project on the velocity mean! The predictions are coming from toy simulations (from the Arizona group) but I'm interested in the more general question of what can be learned from spatial variations in the mean velocity in the halo. It might put strong constraints on the recent-past time-dependence.

substructure, phases, EPRV

Nora Shipp (Chicago) has been in town this week, working with Adrian Price-Whelan to find halo substructures and stellar streams around the Milky Way. The two of them made beautiful animations, paging through distance slices, showing halo stellar density (as measured by a color-magnitude matched filter). There are lots of things visible in those animations! We discussed the point that what makes overdensities appear to the human eye is their coherence through slices.

That made me think of things that Bill Freeman (MIT) and his lab does with amplifying small signals in video: Should we be looking for small overdensities with similar tricks? Freeman's lab uses phase transforms (like Fourier transforms and more localized versions of those) to detect and amplify small motions. Maybe we should use phase transforms here too. That led Price-Whelan and me to hack a little bit on this image pair by Judy Schmidt, which was fun but useless!

Late in the day, Megan Bedell (Flatiron), Lily Zhao (Yale), Debra Fischer (Yale), and I all met to discuss EXPRES data. It turns out that what the EXPRES team has in terms of data, and what they need in terms of technology, is incredibly well aligned with what Bedell and I want to do in the EPRV space. For example, EXPRES has been used to resolve the asteroseismic p-modes in a star. For another, it has made excellent observations of a spotty star. For another, it has a calibration program that wants to go hierarchical. I left work at the end of the day extremely excited about the opportunities here.

code from the deep past

I had an amusing email from out of the blue, asking me to dig up the IDL (yes, IDL) code that I (and Blanton and Bovy and Johnston and Roweis and others) wrote to analyze the local velocity field using the ESA Hipparcos data. Being a huge supporter of open science, I had to say yes to this request. I dug through old cvs repositories (not svn, not git, but cvs) and found the code, and moved it to Github (tm) here. I didn't truly convert the cvs repo to git, so I erased history, which is bad. But time is precious, and I could always fix that later. I hereby apologize to my co-authors!

All this illustrates to me that it is very good to put your code out in the open. One reason is that then you don't have to go digging like this; a simple google search would have found it! Another is that when you know your code will be out in the open, you are (at least slightly) more likely to make it readable and useable by others. I dug up and threw to the world this code, but will anyone other than the authors ever be able to make any use of it? Or even understand it? I don't know.

calibrating a fiber spectrograph

I had my weekly call with Ana Bonaca (Harvard) this morning, where she updated me on our look at systematic effects in the radial-velocity measurements we are getting out of Hectochelle. We see very small velocity shifts in stellar radial velocities across the field of view that seem unlikely to be truly in the observed astrophysical stellar systems we are observing. At this point, Bonaca can show that these velocity shifts do not appear in the sky lines; that is, the calibration (with arc lamps) of the wavelengths on the detector is good.

All I have left at this point is that maybe the stars illuminate the fibers differently from the sky (and arc lamps) and this difference in illumination is transmitted to the spectrograph. I know how to test that, but it requires observing time; we can't do it in the data we have in hand right now. This is an important thing for me to figure out though, because it is related to how we commission and calibrate the fiber robot for SDSS-V. Next question: Will anyone give us observing time to check this?

setting the scope for the next GD-1 paper

Today (and really over the last few days as well) I had a long discussion with Ana Bonaca (Harvard) about the results of our spectroscopy in the GD-1 stellar-stream fields. As my loyal reader knows, Bonaca, Price-Whelan, and I have a prediction for what the radial velocities should look like in the stream, if it is a cold stream that has been hit by a massive perturber. Our new velocity measurements (with the Hectochelle instrument) are not the biggest and best possible confirmation of that prediction!

However, our velocities are not inconsistent with our predictions either. The question is: What to say in our paper about them? We listed the top conclusions of the spectroscopy, and also discussed the set of figures that would bolster and explain those conclusions. Now to plotting and writing.

Along the way to understanding these conclusions, I think Bonaca has found a systematic issue (at extremely fine radial-velocity precision) in the way that the Hectochelle instrument measures radial velocities. I hope we are right, because if we are, the GD-1 stream might become very cold, and our velocity constraints on any perturbation will become very strong. But we will follow up with the Hectochelle team next week. It's pretty subtle.

Liouville

I spent my little bit of research time today working on the paper by Matt Buckley (Rutgers) about observing and using as a tool the conservation of phase-space density that is guaranteed by Hamiltonian dynamics.

Dr Taki

Today was a beautiful and accomplished PhD defense at NYU by Anna-Maria Taki (NYU). Taki is a particle phenomenologist who is looking at signatures of dark matter in the ESA Gaia data. She is concentrating on methods that relate to gravitational lensing: In addition to magnification changes, lensing can induce artificial proper motions and artificial accelerations in the stars. Indeed, Jupiter and Saturn have huge gravitational-lensing signatures at Gaia precision, and they are calibrated out. But if there are dark-matter substructures (say) between us and the SMC or LMC, we could see them in principle as anomalies in the Gaia data. Taki has developed matched filters and statistical techniques for finding the signatures. No detections yet! But there is a hope that an end-of-mission Gaia search could be very interesting.

In the discussion over champagne, I discussed with various people the idea that Taki's work could inspire a new small-explorer class NASA mission. If you could show that such a mission could definitively rule out the main predictions of lambda-CDM, that would be a competitive proposal, I think. And a beautiful experiment.

The day ended with a great and fun PhD candidacy exam by Paul McNulty (NYU). He is using data science and information theory to understand how neural activity relates to motor function in fruit-fly larvae. We discussed the sense in which such work is physics. It is, of course! But it's interesting how interdisciplinary physics has become.

what can you learn from a stream around another galaxy?

My day started with Ana Bonaca (Harvard) telling me about an external-galaxy stream, a stream around an external galaxy found by the Dragonfly telescope. She was able to make a nice model of it! And that fit required that the dark-matter halo be flattened (which is interesting). But what we discussed was (you guessed it) information theory: What can you learn about an external galaxy from seeing a stream in imaging? And what if you get a few radial velocities along that stream? This is a great set of questions, and builds on work we have been doing since the pioneering papers of Johnston and Helmi so many years ago.