The tiny bit of research I did today was work on a Decadal Survey (Astro2020) white paper on changes we might make to the Decadal Survey process itself. The challenge is to write this constructively and with the appropriate tone. I don't want to be sanctimonious!
Nick Pingel (ANU) came by Flatiron and impressed us all with discussions of ASKAP, which is one of the pathfinders to the SKA. The most impressive thing I learned is that the feeds for the telescope array are themselves dipole arrays, so you can synthesize multiple beams at each telescope, and then synthesize an aperture for each beam. That's a great capability for the array, but of course is also an engineering challenge. He said scary things about what the calibration looks like. It really made me wish I had got closer to radio astronomy in my life!
At Stars and Exoplanets Meeting today, Wolfgang Kerzendorf spoke about a novel idea for peer review (for telescope-time proposals, but it could be applied to funding proposals or paper refereeing too): When you submit a proposal, you are sent K proposals to review. And the reviews thus obtained are combined in a sensible way to perform the peer review. This approach is scalable, and connects benefit (funding opportunity) to effort (reviewing). That's a good idea, and crystallizes some things I have been trying to articulate for years.
Kerzendorf's contribution, however, is to make a technology that makes this whole problem simpler: He wants to use natural-language processing (NLP) to help the organizations match proposals to reviewers. He showed snippets from a paper that shows that a simple NLP implementation, looking for similarity between proposal texts and proposers' scientific literature, does a reasonable job of matching reviewers to proposals that they feel comfortable to review. This is a great set of issues, and connects also to the discussions in our community about blind reviewing.
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.
Fridays are the good days at Flatiron. We have the Astronomical Data Group internal meeting (which operates by extremely odd and clever rules, not designed nor enforced by me) and the new Dynamics Group internal meeting. In the latter Robyn Sanderson (Penn) brought her entire group from Penn. Students working with the ESA Gaia data. One thing the group is finding is that certain stars have dynamics that are far more sensitive to dynamical (potential) parameters than others. This is something that Bovy and I were arguing long ago: The dynamical model of the Milky Way will not rest equally on all Gaia stars: Some will be critical. That's either obvious or deep. Or both! (I'm loving that phrase these days.)
Late in the day, Rodrigo Luger (Flatiron) and I trapped Leslie Greengard (Flatiron) and Alex Barnett (Flatiron) into a conversation about performing line integrals of spherical harmonics along curves that are themselves solutions of spherical-harmonic equations. In a typical astronomy–math interaction, we spent most of our time describing the problem, and then the answer is either: That's trivial! or That's hard! Unfortunately the answer wasn't That's trivial! But they did give us some good ideas for how to think about the problem.
One funny thing Greengard asked, which resonated with me (no pun intended): He said: Can you convert this math question into a physics question? Because if you can, it probably has a simple answer! You see how odd that is? That if your equation represents a physics problem, it is probably simple to solve. And yet it seems like it is exactly right. That's either deep or wrong or scary. I think maybe the latter.
Today I had the great honor of meeting Ingrid Daubechies (Duke), who is a pioneering and accomplished mathematician, known for some of the fundamental work on wavelets and representations that have been incredibly important in data. For example, the JPEG standard is based on her wavelets! She gave a talk at the end of the day on teeth. Yes teeth. It turns out that the shapes of tooth surfaces tell you simultaneously about evolution and diet. And she has worked out beautiful ways to first get distances between surfaces. Like metric distances in surface space. And then join those distances up into local manifolds. It could have relevance to things we have been thinking about for a non-parametric version of The Cannon. It was a beautiful talk, with the theme or message that you do better in your science if you use mathematical tools that are matched well to the structure of your problem. That message is either obvious or deep. Or both! What a privilege to be there.
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.
Today was a day of applied math. In one instance, Rodrigo Luger (Flatiron) reformulated all of Doppler Imaging (and the Rossiter–McLaughlin effect) into a simpler form using a model that is (essentially) the outer product of spherical harmonics on the surface of the star and a Fourier-transform basis in the spectral domain. This permits him to do the operations of Doppler imaging extremely fast and with no explicit numerical integrals on the surface of the star. We'd like to implement this in some mash up of Starry and wobble.
In another instance, Kathryn Johnston (Columbia) realized (or really this kind of thing is obvious to her) that my project with Suroor Gandhi (NYU) to model The Snail (the vertical phase spiral in the local Milky Way disk) can be implemented in a potential expansion, expanding in powers away from a simple harmonic oscillator potential. That is much more general than what we were doing, and contains what we were doing within it as a special case. That led to all sorts of talk about what kinds of expansions we might be able to do. Like can we expand a non-equilibrium galaxy in small terms away from an equilibrium galaxy? That's something that Johnston was talking about on Friday in her weekly Dynamics Group meeting.
I sometimes work long days, but I try not to fill my weekend with working. This weekend, however, I had promised myself that I would take the notes from the SDSS-V review I led in Denver and turn them into a draft report for the project. I can't believe it, but I succeeded!
Are you going to be on a review panel? I have advice (unsolicited advice, which I try not to give, but after this weekend, I can't help myself):
Make sure you do lots of writing while in session. If you just listen and talk for the period of the review, you leave the review with nothing written, and then you have to reconstruct it from memory and your notes. Instead, schedule executive-session writing time during the review and come away from the review with everyone's notes and comments compiled into one jointly editable document. I learned this from Mike Hauser (formerly STScI), who chaired the Spitzer Oversight Committee for many years.
Act fast. If you don't write your report immediately, you will never write it. So kill your procrastination and write the hell out of it immediately. And then your panel members will be so shocked at your turnaround time, they will be inspired to act fast themselves. They will take the draft you write fast and turn it into a final version.
Be helpful and constructive. Think carefully about and (more importantly) discuss with the team precisely what they want out of the report and what they can do. Make sure you are answering the questions they want answered, and that the answers you give can be implemented usefully and without huge burden. Report from reviews are about the future not the past.
I love the SDSS-V Project and Collaboration and I want both to succeed. I very much hope that what we have written will help them meet their goals.
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.
Today was day two of the SDSS-V Multi-object spectroscopy review. We heard about the spectrographs (APOGEE and BOSS), the full software stack, observatory staffing, and had an extremely good discussion of project management and systems engineering. On this latter point, we discussed the issue that scientists in academic collaborations tend to see the burdens of documenting requirements and interfaces as interfering with their work. Project management sees these things as helping get the work done, and on time and on budget. We discussed some of the ways we might get more of the project—and more of the scientific community—to see the systems-engineering point of view.
The panel spent much of the day working on our report and giving feedback to the team. I am so honored to be a (peripheral) part of this project. It is an incredible set of sub-projects and sub-systems being put together by a dream team of excellent people. And the excellence of the people cuts across all levels of seniority and all backgrounds. My day ended with conversations about how we can word our toughest recommendations so that they will constructively help the project.
One theme of the day is education: We are educators, working on a big project. Part of what we are doing is helping our people to learn, and helping the whole community to learn. And that learning is not just about astronomy. It is about hardware, engineering, documentation, management, and (gasp) project reviewing. That's an interesting lens through which to see all this stuff. I love my job!
Today was day one of a review of the SDSS-V Multi-object spectroscopy systems. This is not all of SDSS-V but it is a majority part. It includes the Milky Way Mapper and Black-Hole Mapper projects, two spectrographs (APOGEE and BOSS), two observatories (Apache Point and Las Campanas), and a robotic fiber-positioner system. Plus boatloads of software and operations challenges. I agreed to chair the review, so my job is to lead the writing of a report after we hear two days of detailed presentations on project sub-systems.
One of the reasons I love work like this is that I learn so much. And I love engineering. And indeed a lot of the interesting (to me) discussion today was about engineering requirements, documentation, and project design. These are not things we are traditionally taught as part of astronomy, but they are really important to all of the data we get and use. One of the things we discussed is that our telescopes have fixed focal planes and our spectrographs have fixed capacities, so it is important that the science requirements both flow down from important scientific objectives, and flow down to an achievable, schedulable operation, within budget.
There is too much to say in one blog post! But one thing that came up is fundraising: Why would an institution join the SDSS-V project when they know that we are paragons of open science and that, therefore, we will release all of our data and code publicly as we proceed? My answer is influence: The SDSS family of projects has been very good at adapting to the scientific interests of its members and collaborators, and especially weighting those adaptations in proportion to the amount that people are willing to do work. And the project has spare fibers and spare target-of-opportunity capacity! So you get a lot by buying into this project.
Related to this: This project is going to solve a set of problems in how we do massively multiplexed heterogeneous spectroscopic follow-up in a set of mixed time-domain and static target categories. These problems have not been solved previously!
I spent time today on an airplane, writing in the papers I am working on with Jessica Birky (UCSD) and Megan Bedell (Flatiron). And I read documents in preparation for the review of the SDSS-V Project that I am leading over the next two days in a Denver airport hotel.
This morning on my weekly call with Eilers (MPIA) we discussed the new scope of a paper about spiral and bar structure in the Milky Way disk. Back at the Gaia Sprint, we thought we had a big result: We thought we would be able to infer the locations of the spiral-arm over-densities from the velocity field. But it turned out that our simple picture was wrong (and in retrospect, it is obvious that it was). But Eilers has made beautiful visualizations of disk simulations by Tobias Buck (AIP), who shows very similar velocity structure and for which we know the truth about the density structure. These visualizations say that there are relationships between the velocity structure and the density structure, but that it evolves. We tried to write a sensible scope for the paper in this new context. There is still good science to do, because the structure we see is novel and spans much of the disk.
In my small amount of true research time today, I wrote an abstract for the information-theory (or is it data-analysis?) paper that Bedell and I are writing about extreme-precision radial-velocity spectroscopy. The question is: What is the best precision you can achieve, and what data-analysis methods saturate the bound? The answer depends, of course, on the kinds of noise you have in your data! Oh, and what counts as noise.
In an absolutely excellent Stars and Exoplanets Meeting, Rodrigo Luger (Flatiron) had everyone in the room (and that's more than 30 people) say what they plan to get done this summer!
Following that, Melissa Ness (Columbia) talked about the different alpha elements and alpha enhancement: Are all alpha elements enhanced the same way? Apparently models of type-Ia supernovae say that different alpha elements should form in different parts of the supernova, so it is worth looking to see if there are abundance differences in different alphas. The generic expectation is that there should be a trend with Z. She has some promising results from APOGEE spectra.
Mike Blanton (NYU) talked about how we figure out how to perform a set of multi-epoch, multi-fiber spectroscopic surveys in SDSS-V. He has a product called Robostrategy which tries to figure out whether a set of targets (with various requirements on signal-to-noise and repeat visits and cadence and so on) is possible to observe with the two observatories we have, in a realistic set of exposures. That's a really non-trivial problem! And yet it appears that Blanton may have working code. I'm impressed, because integer programming is hard.
And Shuang Liang (Stony Brook) showed us that it is possible to calibrate u-band observations using the main-sequence turn-off, as long as you account for the differences between the disk and the halo. He has developed empirical approaches, and he has good evidence that his calibration based on the MSTO is better than other more traditional methods!
I had conversations today with Megan Bedell (Flatiron) and Kate Storey-Fisher (NYU) about titles for their respective papers. I am slowly developing a whole theory of writing papers, which I wish I had thought about more when I was earlier in my career. I made many mistakes! My view is that the most important thing about a paper is the title. Which is not to say that you should choose a cutesy title. But it is to say that you should make sure the person scanning a listing of papers can estimate very accurately what your paper is about.
I then think the next most important thing is the abstract. Write it early, write it often. Don't wait until the paper is done to write the abstract! The abstract sets the scope. If you have too much to put into one abstract, split your paper in two. If you don't have enough, your paper needs more content. And unless you are very confident that there is a better way, obey the general principles (not necessarily the exact form) underlying the A&A structure of context, aims, methods, results.
Then the next most important thing is (usually) the figures and captions. My model reader looks at the title. If it's interesting, the reader looks at the abstract. If that's interesting, they look at the figures. If all that is interesting, maybe they will read the paper. Since we want our papers to be read, and we want to respect the time of our busy colleagues, we should make sure the title, abstract, and figures-plus-captions are well written, accurate, unambiguous, interesting, and useful.
So I spent time today working on titles.
One amusing conversation today was between Ben Pope (NYU) and myself about whether hot stars are more or less likely to host planets with live. We believe (it's not extremely well established yet) that there are more habitable planets around M-type stars than G-type (and there is probably a relatively smooth function of temperature). So why do we live around a G star? Is it because there is more free energy per photon? I have assumed that this is why. But we realized that we can make this argument quantitative. One question that I have is this: Is this argument anthropic? Or is it just the simple observation that Earth hosts life? I think it is anthropic, because it has something to do with whether our place is special.
I spent the weekend finally finishing a response to referee on my paper on using spectroscopy and photometry to get precise stellar distances. It was a very constructive, helpful, and positive report, so it really is embarrassing that it took me this long to finish. But it's done and we will resubmit on Monday. Somehow in my dotage, it gets hard to do the things I must do for myself. I am motivated to meet my obligations to others, but it is hard to meet those that help primarily me.