extracting DNA

I spent the morning today at a conference for educators and education students at Queens College. It was great! I went to a session on classroom biology, in which we extracted DNA from a strawberry, using only household chemicals (detergent, salt, and alcohol). It was great, and I worked with two really cool lab partners, both Queens College first-year undergraduates.

water forces on bacteria

Today we had a really great colloquium by Ned Wingreen (Princeton), about water forces on bacteria and how communities of bacteria can be seen as an active material. He showed theory and data for simple experiments in which they can change the osmotic pressure on a wet surface where bacteria are moving. They can tune the water-driven forces on the bacteria and change their behaviors.

After that, at wine and cheese, David Grier (NYU) showed me (and lots of students) a home-built device that levitates (or really traps) tiny objects using acoustic waves. It was awesome.

six-quark state?

Today was a great blackboard talk at CCPP by Glennys Farrar (NYU) about a possible six-quark state in QCD. She has been thinking about this for a decade or so, because it might have implications for dark matter and issues in QCD. Today she focused on the latter: There are terms in the g−2 calculation for the muon that can be estimated either with lattice QCD or by integrating some observed branching ratios from experiment. These two methods disagree, and the observational method disagrees (more strongly) with the g−2 measurement. But Farrar shows that if there is a long-lived 6-quark state, it can potentially affect the QCD calculation (implicitly) but would be evaded by the branching-ratio measurements (because it would evade all event triggers). Her model requires some good luck with QCD parameters and bound states, but if that luck holds, she can pull dark matter into the standard model and solve some precision-measurement issues! After her talk we discussed a bit about just how hard lattice QCD is. It's absurd!

next-generation cosmology?

Today Juna Kollmeier (Carnegie) convened a tiny meeting with Dalal, Percival, and me to discuss the next generation of cosmology missions and projects. We wandered around metrics, around data-analysis methods (forward modeling?), and new hardware, but didn't come up with much specific to say, yet. But Kollmeier is right to be thinking forward, because the landscape is changing and the most interesting objects of cosmological research are evolving on time-scales shorter than project execution. Of course that's always the case for interesting disciplines!

Terra Hunting Science Meeting, day 1

Today was the first day of the Terra Hunting science meeting. We made great progress on target selection, which was our primary goal. We decided that we should only consider stars that have sufficient visibility from the observatory and sufficient brightness to deliver sufficient photons to provide precisely enough measured radial-velocity variations over a decade to meet our planet-detection goals. That is, we should make the parent sample of our final selection to be stars where we at least have enough photons to detect an Earth. That is an obvious and simple point, but this was the first meeting where we really clearly identified it, and started to figure out how that flows down to a target list. It turns out that there aren't huge numbers of stars that even meet this strict requirement. And of course we spent lots of time talking about all the reasons that we won't get photon-limited radial-velocities, so our final target list must be much more restricted, probably.

attacks; efficiency

My research day started with a conversation with Teresa Huang (JHU) and Soledad Villar (JHU) about the regressions that are used to determine stellar parameters. Huang has shown that different machine-learning methods (which are generally over-parameterized) obtain very different gradients in their explicit or implicit functions that connects labels (stellar parameters) to features (stellar spectra), and very different from those indicated by the physical models we have of stellar atmospheres. These differences can be exploited for attack.

Later, Megan Bedell (Flatiron) and I spent time designing projects that are aimed at maximizing the efficiency of radial-velocity exoplanet searches. The idea is: You have a finite amount of telescope time allocated over a fixed (long) interval. How do you assign observation slots to stars to maximize expected yield (or any other statistic you care about)? The answer is going to depend strongly on what we assume about the noise properties of the measurements we make.

Simons-NSBP Scholars program

Today was the final wrap-up presentations from the new partnership between the Simons Foundation (and especially Simons Observatory) and the National Society of Black Physicists that made the S-NSBP Scholars program. Scholars were paid to spend the summer interning in various physics projects. The wrap-up lightning talks were incredibly broad and impressive. But the organizer of the program, Kasey Wagoner (Princeton), asked the Scholars to say something in their lightning talks about what they learned or what the program meant to them, and some of the responses were pretty impressive. My student was Winston Harris (MTSU), who (my loyal reader knows) did work on making exoplanet detection more efficient. The Astronomical Data Group here at Flatiron hosted four Scholars, and the whole program included dozens.

how to schedule radial-velocity measurements?

This summer I have been working with Winston Harris (MTSU) on the efficiency with which we can detect planets using an RV survey or with RV data. He has some nice results, some of which he presented at Stars & Exoplanets meeting today. After this, Megan Bedell (Flatiron) and I discussed the question: What are the simplest questions we can ask about detecting planets by RV observations? We have questions about the distribution / cadence of the observations, given a finite, pre-defined survey window. But we also have questions about the cadence in relation to the coherence times of the various noise processes: It should be different to take many observations within one coherence time vs taking observations separated by many coherence times. My intuition is not as rich as I'd like it to be here.

forward modeling of asteroseismic modes—for exoplanets

As my loyal reader knows, I have four separate projects with Bonaca, Feeney, Casey, and Bedell to forward-model asteroseismic modes, with Bonaca concentrating on ground-based data, Feeney on principled Bayes, Casey on ESA Gaia, and Bedell on removing the modes as nuisances when we want to find planets. Today Bedell and I discussed where we are at, and came up with some things to try. In Sun-like stars, the modes have days-ish coherence times (apparently) and the modes have minutes-ish periods. So there are different regimes as your exposure cadence ranges from minutes to days to weeks. We have some qualitative predictions, and we are trying to make quantitative results that will influence survey design in the near future (especially for Terra Hunting Experiment and NASA NEID).

One funny thing about quasi-periodic (as in: finite coherence-time) oscillation processes is that they can be generated as a subset of Gaussian Processes, if you have good kernel machinery. We do! Another funny thing is that a GP can fit anything it is asked to fit! It literally has infinity free parameters (yes, literally). But the more appropriate kernels will do better (we hope) at predicting held-out data.

automating discovery

It was a very low-research day! But I did get in an hour with Bedell (Flatiron), discussing our plan to automate some aspects of exoplanet detection and discovery. The idea is: If we can operationalize and automate discovery, we can use that to perform experimental design on surveys. Surveys that we want to optimize for exoplanet yield. We discussed frequentist vs Bayesian approaches.

experimental design for exoplanet discovery

I spent time today writing a new paper stub (as is my wont). I re-framed the project Bedell (Flatiron) and I are working on in planet detection into a project on experimental (survey or project) design. After all, if you want to perform experimental design trades, you need a system that can tell you what you could or would observe or detect. So these questions: How do you discover an exoplanet? and How do I design my survey? are very intimately related. It's just a stub; we'll see if Bedell likes it.

#sdss2020, day 3+1

If yesterday was day 3, then the one-day working meeting on Monday regarding SDSS-IV was day zero, and today—a working meeting for SDSS-V—was day 3+1. The highlight for me today was a discussion led by Hans-Walter Rix (MPIA) and Kevin Covey (WWU) of what we might do with extra fiber–visits.

SDSS-V is a robot-positioned multi-object fiber-fed spectroscopic survey, with both optical and infrared spectrographs. It works in a few modes, but most of them involve jumping around the sky, taking (relatively) short spectroscopic observations of hundreds of stars at a time. The operations are complex: There are multiple target categories with different cadence requirements, and there are positional constraints on what the fiber robots can do. All this means that there are many, many (like millions of) unassigned fiber–visits.

The range of projects proposed was breathtaking, from Cepheids to microlensing events to nearby galaxy redshifts to quasar catalogs. And all of them so clever and thought-out that they were all compelling. And this wasn't even an official call for proposals: It was just a brainstorming session. Towards the end, there were some ideas (that I loved) about taking a union of the star-oriented suggestions and making a project with excellent data volume and legacy value. I love this Collaboration.

Want a piece of this? Consider buying in. Send me email if you want to discuss that, for yourself or for your institution.

what constitutes an exoplanet discovery?

Over the last few days, Megan Bedell (Flatiron) and I have been discussing the criteria that go into a detection of an exoplanet, or what things need to be true for a detection or discovery to be considered made. We are thinking of discoveries with the Terra Hunting Experiment or other radial-velocity surveys. We identified three-ish condtions:

One condition is that the amplitude be significantly different from zero; that is, the null is ruled out. Another is that the planet be characterizable: that is, the orbital parameters can be estimated to some level of precision. A third is that the planetary explanation of the signal be preferred at some confidence over other qualitatively different explanations, like stellar variabilities, stellar rotation, or signals faked by beats from other planets.

I presented these criteria at Astronomical Data Group meeting, and Dan Foreman-Mackey (Flatiron) said that he disagreed with every aspect of it. But we didn't (yet) find out why.

homework problem

This week Megan Bedell (Flatiron) assigned me a homework problem, which is to work out the information theory (or whatever) that will tell us how sensitive a particular radial-velocity survey is to exoplanets. I started to write this down as a problem and a solution today. It might evolve into a paper if we have enough to say!

data-driven model of spectra; observing strategies

Today some actual work happened, although only a tiny bit! I spoke with Adam Wheeler (Columbia) about our project to find a local, low-dimensional representation of LAMOST spectra, which can then be used to find abundance outliers. The model is a linear latent-variable model, but executed locally among the K nearest neighbors in the training set near the test object. It is unsupervised, because it doesn't rely on any labels (except the knowledge of where in the spectrum each element has lines). I'm interested in whether approaches like this could be built up into a full abundance system, with clever self-calibration.

I met with Megan Bedell (Flatiron) who has been playing around with observing strategies for Terra Hunting Experiment. We would like to demonstrate that randomized observing strategies bring more information than regular observing strategies. But if we simulate the data as having white (uncorrelated) noise of known variance, the sensitivity of the data to planets of various periods depends only (or almost only) on the total exposure time and total survey duration, and barely on how the observations are scheduled. So what gives? I think the big deal is correlated noise: If the spectrographs drift in their calibration properties in some correlated way over time during the survey, then the regular data will alias those drifts into periodic signals. Or that's my conjecture. I'm not confident in it, but we can test it. Oh and by the way: You always have low-level correlated drifts in your instrument calibration, which are below the calibration precision but large enough that they can affect your results when you combine many thousands of exposures over many years.

spectrograph calibration: Which centroiding is best?

Lily Zhao (Yale) and I looked at the different centroiding methods, indexed by two integers: One integer is how many pixels to use near the peak of each line for the peak fitting. The other is what order of polynomial fitting (to the logarithm of the flux; quadratic in log flux is Gaussian in flux). She made many diagnostic plots and statistics. Now: How to decide which setting of the two integers is best? We tentatively settled on the mean absolute difference of pairs of frames that are taken within the same day (or night really). This uses an assumed stability of the spectrograph, but I think it's safe, because it's hard to imagine that our centroiding will correct for true spectrograph drifts! More soon; if this works, we can further improve the EXPRES pipelines.

Oregon, falsifiability, and the LIGO project

Today was my first day of a two-day visit to Ben Farr (Oregon) and the University of Oregon. I got lots of work done during the travel phases of the day, because I have a NASA proposal due while I'm here in Oregon! Nothing like a deadline.

I had a great day. Highlights included a discussion with James Schombert (Oregon) about various philosophical matters related to falsification. He explicitly brought up my paper about plausibility and science, which I had nearly forgotten! It's nice to know that people are finding it useful still. I really wrote it to get some things off my chest, things that had been troubling me since graduate school in the 1990s. In that paper I argue that we prefer theories that are both observationally reasonable and also theoretically reasonable; there isn't really such a thing as purely empirical falsification. At least not in the observational sciences.

But of course the main theme of my visit was LIGO. The lure of discussing this project with Farr is what brought me here. We postponed our ideas for new projects until tomorrow and, maybe surprisingly, spent our time talking about university-based project management! Because although LIGO is well funded to build hardware and deliver strain measurements, what is done with those to detect and characterize systems and populations is left to the science community, which is a looser collaboration, and which must raise most of its money externally. And, like with the SDSS family of projects, relies on essentially volunteer efforts from many ornery faculty. That's an interesting set of problems in organizational management, psychology, and political science!

forecasting tools; beautiful spectrograph calibration

Our five-person (Bedell, Hogg, Queloz, Winn, Zhao) exoplanet meeting continued today, with Winn (Princeton) working out the elements needed to produce a simulator for a long-term EPRV monitoring program with simple observing rules. He is interested in working out under what circumstances such a program can be informative about exoplanets in regimes that neither Kepler nor existing EPRV programs have strongly constrained, like near-Earth-masses on near-Earth-orbits around near-Sun stars. And indeed we must choose a metric or metrics for success. His list of what's needed, software-wise, is non-trivial, but we worked out that every part of it would be a publishable contribution to the literature, so it could be a great set of projects. And a very useful set of tools.

Zhao (Yale) showed me two-dimensional calibration data from the EXPRES instrument illuminated by their laser-frequency comb. It is astounding. The images are beautiful, and every single line in each image is at a perfectly known (from physics!) absolute wavelength. This might be the beginning of a very new world. The instrument is also beautifully designed so that all the slit (fiber, really, but it is a rectangular fiber) images are almost perfectly aligned with one of the CCD directions, even in all four corners of the image. Not like the spectrographs I'm used to!

do we need to include the committee in our model?

Josh Winn (Princeton) and Lily Zhao (Yale) both came in to Flatiron for a couple of days today to work with Megan Bedell (Flatiron), Didier Queloz (Cambridge), and me. So we had a bit of a themed Stars and Exoplanets Meeting today at Flatiron. Winn talked about various ways to measure stellar obliquities (that is, angles between stellar-rotation angular momentum vectors and planetary system angular-momentum vectors). He has some six ways to do it! He talked about statistical differences between vsini measurements for stars with and without transiting systems.

Zhao and Queloz talked about their respective big EPRV programs to find Earth analogs in radial-velocity data. Both projects need to get much more precise measurements, and observe fewer stars (yes fewer) for longer times. That's the direction the field is going, at least where it concerns discovery space. Queloz argued that these are going to be big projects that require patience and commitment, and that it is important for new projects to control facilities, not just to apply for observing time each semester! And that's what he has with the Terra Hunting Experiment, in which Bedell, Winn, and I are also partners.

Related to all that, Zhao talked about how to make an observing program adaptive (to increase efficiency) without making it hard to understand (for statistical inferences at the end). I'm very interested in this problem! And it relates to the Queloz point, because if a time allocation committee is involved every semester, any statistical inferences about what was discovered would have to model not just the exoplanet population but also the behavior of the various TACs!

spectroscopy, Earth-finding

At mid-day I spun out an extended fantasy with Andy Casey (Monash) about a general and generalizable spectroscopic software toolkit that could do data analysis, spectral extraction, parameter estimation, and radial-velocity measurement in arbitrary two-dimensional spectrograph imaging. One of the related ideas is to build low-dimensional descriptions of the calibration of the spectrograph to pool calibration data and reduce pressure on calibration observations. Another idea is to avoid going to one-d spectra, except when necessary (almost never necessary). Another is never to deconvolve to high resolution (spectro-perfectionism is a deconvolve–reconvolve method, to which I object). Etc. It would be a lot of work, but it could revolutionize the business.

Late in the day I had a conversation with Megan Bedell (Flatiron) about possible high-level goals for the Terra Hunting Experiment, which is finding Earth analogs. Some of the goals might be about discovery rate (or future-discounted discovery rate) and some might be about statistics (what is the abundance of Earth analogs?). Different high-level objectives lead to different operational decisions. Interesting. And hard.