CPM rises from the ashes

I had a great call today with So Hattori (NYUAD) and Dan Foreman-Mackey (Flatiron), about Hattori's reboot of the causal pixel model by Dun Wang (that we used in NASA Kepler data) for new use on NASA TESS data. Importantly, Hattori has generalized the model so it can be used in way more science cases than we have looked at previously, including supernovae and tidal disruption events. And his paper is super-pedagogical, so it will invite and support (we hope) new users. Very excited to help finish this up!

NSF center proposal

I spent some time today discussing a possible NSF Center on real-time data analysis with Ashley Villar (Columbia) and Tyler Pritchard (NYU), based on the wide-ranging grass-roots interest we found in time-domain astrophysics we have discovered in NYC this pandemic. NSF Centers are big projects!

time-domain astronomy in Gotham

Today, Tyler Pritchard (NYU) and I assembled a group of time-domain-interested astrophysicists from around NYC (and a few who are part of the NYC community but more far-flung). In a two-hour meeting, all we did was introduce ourselves and our interests in time domain, multi-messenger, and Vera Rubin Observatory LSST, and then discuss what we might do, collectively, as a group. Time-domain expertise spanned an amazing range of scales, from asteroid search to exoplanet characterization to stellar rotation to classical novae to white-dwarf mergers with neutron stars, supernovae, light echoes, AGN variability, tidal-disruption events, and black-hole mergers. As we had predicted in advance, the group recognized a clear opportunity to create some kind of externally funded “Gotham” (the terminology we often use for NYC-area efforts these days) center for time-domain astrophysics.

Also, as we predicted, there was more confusion about whether we should be thinking about a real-time event broker for LSST. But we identified some themes in the group that might make for a good project: We have very good theorists working, who could help on physics-driven multi-messenger triggers. We have very good machine-learners working, who could help on data-driven triggers. And we have lots of non-supernovae (and weird-supernova) science cases among us. Could we make something that serves our collective science interests but is also extremely useful to global astrophysics? I think we could.

funding! and interpolation!

Kate Storey-Fisher (NYU) got great news today. Her NASA FINESST proposal was funded! So she gets paid for the next three years. And she did it herself. Funding is one of the most challenging, confusing, disheartening, and complicated parts of this job. I don't like it, but it's reality. Congratulations, Storey-Fisher

On my student-research call, I worked on interpolating complex numbers with Avery Simon (NYU). We have a set of phase transforms of two very similar images, which return, for components, complex amplitudes (or amplitudes and phases, if you like). Now the question is: How to interpolate between these images, or their phase transforms? We want to test the hypothesis (put forward in computer-vision research like this) that interpolating in complex phase is way better in many respects than interpolating naively.

#AAS235, day 2

My personal life relented slightly and I got to Hawaii for a bit of the 235th Meeting of the American Astronomical Society. It is great to see the whole community (or a very large part of it) in one place at one time; I'm still a believer in these meetings, after all these years (I've been attending pretty regularly since 1994). Oh no, has this become “old-fogey research blog”?

Because I arrived today I only saw a few talks, one of which was my student Storey-Fisher (NYU), who explained how we can estimate the two-point correlation function without binning the data into bins. She did a good job of summarizing the benefits, which are legion: We lower the bias and the variance over the traditional methods, and we can work in function spaces that are appropriate to our science questions, for just two examples. I can't wait to be submitting this paper.

Her talk was followed by an excellent talk by Shajib (UCLA) about gravitational lensing and the Hubble-Constant controversy. He showed that the lensing results are falling in line with the late-time supernova-based Hubble Constant measurements, not the CMB and BAO measurements. And his biggest systematic in his time-domain analyses is (as expected) the foreground “mass sheet” degeneracy. He is getting close to achieving one of the dreams of this field (that I have had with Phil Marshall, for example), which is to automate the fitting of non-trivial strong gravitational lens systems, including lensing galaxy, and multiple source galaxies. Beautiful stuff.

And at this meeting there was so much more, almost infinitely more!

#MLringberg2019, day 1

Today was the first day of Machine Learning Tools for Research in Astronomy in Ringberg Castle in Germany. The meeting is supposed to bring together astronomers working with new methods and also applied methodologists to make some progress. There will be a different mix of scientific presentations, participant-organized discussions, and unstructured time. Highly biased, completely subjective highlights from today included the following:

Michelle Ntampaka (Harvard) showed some nice results on using machine-learning discriminative regressions to improve cosmological inferences (the first of a few talks we will have this week along these lines). She emphasized challenges and lessons learned, which was useful to the audience. Among these, she emphasized the value she found in visualizing the weights of her networks. And she gave us some sense of her struggles with learning rate schedule, which I think is probably the bane of almost every machine learner!

Tom Charnock (Paris) made an impassioned argument that the outputs of neural networks are hard to trust if you haven't propagated the uncertainties associated with the finite information you have been provided about the weights in training. That is, the weights are a point estimate, and they are used to make a point estimate. Doubly bad! He argued that variational and Bayesian generalizations of neural networks do not currently meet the criteria of full error propagation. He showed some work that does meet it, but for very small networks, where Hamiltonian Monte Carlo has a shot of sampling. His talk generated some controversy in the room, which was excellent!

Morgan Fouesneau (MPIA) showed how the ESA Gaia project is using ideas in machine learning to speed computation. Even at one minute per object, they heat up a lot of metal for a long time! He showed that when you use your data to learn a density in the data space for different classes, you can make inferences that mitigate or adjust for class-imbalance biases. That's important, and it relates to what Bovy and I did with quasar target selection for SDSS-III.

Wolfgang Kerzendorf (Michigan State) spoke about his TARDIS code, which uses machine learning to emulate a physical model and speed it up. But he's doing proper Bayes under the hood. One thing he mentioned in his talk is the “expanding photosphere method” to get supernova distances. That's a great idea; whatever happened to that?

black holes and nucleosynthesis

Today Selma de Mink (Harvard) gave a great and energizing Astrophysics Seminar at NYU. She talked about many things related to the extremely massive-star progenitors of the estremely massive black holes being observed in merger by LIGO. One assumption of her talk, which is retrospectively obvious but was great, is that the vast majority of LIGO events should be first-generation mergers. A second merger is very unlikely, dynamically. But that wasn't her point: Her point was that the masses that LIGO sees will constrain how very massive stars evolve. In particular, she showed that there is a strong prediction of a mass gap: There can't be black holes formed by stellar evolution in the mass range 45 to 150 solar masses. The physics is all about pair-instability supernovae from very low-metallicity stars. But the details of this black-hole mass gap depend on some nuclear reaction rates, so she concludes that LIGO will make nucleosynthetic measurements! The LIGO data probably already do. It's a new world!

finding very long signals in very short data streams

So many things. I love Wednesdays. Here's one: I spent a lot of the day working with Adrian Price-Whelan (Flatiron) on our issues with The Joker. We found some simple test cases, we made a toy version that has good properties, we compared to the code. Maybe we found a sign error!? But all this is in service of a conceptual data-analysis project I want to think about much more: What can you say about signals with periodicity (or structure) on time scales far, far longer than the baseline of your observations? Think long-period companions in RV surveys or Gaia data. Or the periods of planets that transit only once in your data set. Or month-long asteroseismic modes in a giant star observed for only a week. I think it would be worth getting some results here (and I am thinking information theory) because I think there will be some interesting scalings (like lots of things might have precisions that scale better (faster I mean) than the square-root of time baseline).

In Stars & Exoplanets meeting at Flatiron, many cool things happened! But a highlight for me was a discovery (reported by Saurabh Jha of Rutgers) that the bluest type Ia supernovae are more standardizeable (is that a word?) candles than the redder ones. He asked us how to combine the information from all supernovae with maximum efficiency. I know how to do that! We opened a thread on that. I hope it pays off.

alphas, robots, u-band

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!

binary stars and lots more

Today was a very very special Stars meeting, at least from my perspective! I won't do it justice. Carles Badenes (Pitt) led us off with a discussion of how much needs to be done to get a complete picture of binary stars and their evolution. It's a lot! And a lot of the ideas here are very causal. For example: If you find that the binary fraction varies with metallicity, what does it really vary with? Since, after all, stellar age varies with metallicity, as do all the specific abundance ratios. And also star-formation environment! It will take lots of data and theory combined to answer these questions.

Andreas Flörs (ESO) spoke about the problem of fitting models to the nebular phase of late-time supernovae, where you want to see the different elements in emission and figure out what's being produced and decaying. The problem is: There are many un-modeled ions and the fits to the data are technically bad! How to fix this. We discussed Gaussian-process fixes, both stationary and non-stationary. And also model elaboration. And the connection between these two!

Helmer Koppelman (Kapteyn) showed some amazing structure in the overlap of ESA Gaia data and various spectroscopic surveys (including LAMOST and APOGEE and others). He was showing visualizations in the z-max vs azimuthal-action plane. We discussed any ways it could be selection effects. It could be; it is always dangerous to plot the data in derived (rather than more closely observational) properties.

Tyson Littenberg (NASA Marshall) told us about white-dwarf–white-dwarf (see what I did with dashes there?) binaries in ESA LISA. He has performed an information-theoretic analysis for a realistic Milky Way simulation. He showed that many binaries will be very well localized; many thousands will be clearly detected; and some will get full 6-d kinematics because the chirp mass will be visible. Of course there are simplifying assumptions about the binary environments and accelerations, but there is no doubt that it will be incredible. Late in the day we discussed how you might model all the sea of sources that aren't individually detectable. But that said, everything to many tens of kpc in the MW will be visible, so incompleteness isn't a problem until you get seriously extragalactic. Amazing!

binaries

Great Astro Seminar today by Carles Badenes (Pitt), who has been studying binary stars, in the regime that you only have a few radial-velocity measurements. In this regime, you can tell that something is a binary, but you can't tell what its period or velocity amplitude is with any precision (and often almost no precision). He showed results relevant to progenitors of supernovae and other stellar explosions, and also exoplanet populations. Afterwards, Andy Casey (Monash) and I continued the discussion over drinks.

topological gravity; time domain

Much excellent science today. I am creating a Monday-morning check-in and parallel working time session for the undergraduates I work with. We spoke about box-least-squares for exoplanet transit finding, about FM-radio demodulators and what they have to do with timing approaches to timing-based planet finding, scientific visualization and its value in communication, and software development for science.

At lunch, the Brown-Bag talk (my favorite hour of the week) was by two CCPP PhD students. Cedric Yu (NYU) spoke about the topological form of general relativity. As my loyal reader could possibly know, I love the reformulation of GR in which you take the square-root of the metric (the tetrad, in the business). Yu showed that if you augment this with some spin fields, you can reformulate GR entirely in terms of topological invariants! That's amazing and beautiful. It relates to some cool things relating geometry and topology in old-school math. Oliver Janssen (NYU) spoke about the wave function of the Universe, and what it might mean for the initial conditions. There is a sign ambiguity, apparently, in the argument of an exponential in the action! That's a big deal. But the ideas are interesting because they force thinking about how quantum mechanics relates to the entire Universe (and hence gravity).

In addition to all this, today was the first-ever meeting of the NYU Time Domain Astrophysics group meeting, which brings together a set of people at NYU working in the time domain. It is super diverse, because we have people working on exoplanets, asteroseismology, stellar explosions, stellar mergers, black-hole binaries, tidal disruption events, and more. We are hoping to use our collective wisdom and power to help each other and also influence the time-domain observing projects in which many of us are involved.

augmented reality, M dwarfs, and TESS

At Stars Meeting at Flatiron, Wolfgang Kerzendorf (NYU) showed a nice demo of an idea we have been kicking around, which is to use augmented reality to visualize data in the space. It was just a demo, but it was promising! After that, Rocio Kiman (CUNY) showed her work on M-dwarf and L-dwarf age indicators and their inter-relations. She showed that flaring dwarfs tend to be larger in radius, which might be evidence of having magnetic pressure changing their structures.

In the afternoon, I discussed NASA TESS proposal ideas with Tyler Pritchard (NYU) and Maryam Modjaz (NYU), who are interested in using TESS to do supernova and explosive-transient science. I was planning on doing something with the CPM that was developed by Dun Wang (formerly NYU) for making image differences in TESS-like time-domain data. We tentatively decided to join forces, and we will properly decide tomorrow.

candidate Williamson

Today Marc Williamson (NYU) passed (beautifully, I might say) his PhD Candidacy exam. He is working on the progenitors of core-collapse supernovae, making inferences from post-peak-brightness spectroscopy. He has a number of absolutely excellent results. One is (duh!) that the supernovae types seem to form a continuum, which makes perfect sense, given that we think they come from a continuous process of envelope loss. Another is that the best time to type a supernova with spectroscopy is 10-15 days after maximum light. That's new! His work is based on the kind of machine-learning I love: Linear models and linear support vector machines. I love them because they are convex, (relatively) interpretable, and easy to visualize and check.

One amusing idea that came up is that if the stripped supernova types were not in a continuum, but really distinct types, then it might get really hard to explain. Like really hard. So I proposed that it could be a technosignature! That's a NASA neologism, but you can guess what it means. I discussed this more late in the day with Soledad Villar (NYU) and Adrian Price-Whelan (NYU), with whom we came up with ideas about wisdom signatures and foolishness signatures. See twitter for more.

Also with Villar I worked out a very simple toy problem to think about GANs: Have the data be two-d vectors drawn from a trivial distribution (like a 2-d Gaussian) and have the generator take a one-d gaussian draw and transform it into fake data. We were able to make a strong prediction about how the transform from the one-d to the two-d should look in the generator.

SCIMMA workshop, day 2

I officially don't go to meetings on the weekend! That said, I did go to day 2 of a workshop on multi-messenger astrophysics (and, in particular, the field's computing and information infrastructure needs) at Columbia University today. A lot happened, and there were even some fireworks, because there are definitely disagreements among the physicists, the computer scientists, the information scientists, and the high-performance computing experts about what is important, what is hard, and what is in whose domain! I learned a huge amount today, but here are two highlights:

In its current plan (laid out at the meeting by Mario Juric of UW), the LSST project officially doesn't do any scientific analyses; it is only a data source. In this way it is like ESA Gaia. It is trying to do a lot of social engineering to make sure the community organizes good data-analysis and science efforts around the LSST data outputs and APIs. Famously and importantly, it will produce hundreds of thousands to millions of alerts per night, and a lot of the interest is in how to interact with this firehose, especially in multi-messenger, where important things can happen in the first seconds of an astrophysical event.

During Juric's talk, I realized that in order for us to optimally benefit from LSST, we need to know, in advance, where LSST is pointing. Everyone agreed that this will happen (that is, that this feed will exist), and that (relative to the alerts stream) it is a trivial amount of data. I hope this is true. It's important! Because if you are looking for things that happen on the sky, you learn more if you happen to find one that happens inside the LSST field while LSST is looking at it. So maybe looking under the lamp-post is a good idea!

The LCOGT project was represented by Andy Howell (LCOGT). He talked about what they have learned in operating a heterogeneous, global network of telescopes with diverse science goals. He had various excellent insights. One is that scheduling requires very good specification of objectives and good engineering. Another is that openness is critical, and most break-downs are break-downs of communication. Another is that there are ways to structure things to reward generosity among the players. And so on. He talked about LCOGT but he is clearly thinking forward to a future in which networks become extremely heterogeneous and involve many players who do not necessarily all trust one another. That's an interesting limit!

are jets beamed? correlation function slowness

Today Kate Alexander (Harvard) gave the Astro Seminar. She talked about the observational properties of jets across wavelength but especially in the radio. And unresolved jets, understood through their spectral energy distributions. One point which came up is that there does still seem to be a beaming puzzle: The models of the observations imply high beaming factors, but off-axis examples are very hard to find. So is the model ruled out? MacFadyen (NYU) implied yes, even though he is one of the principal authors of the theories! I think this is a super-important area for multi-messenger and time-domain astrophysics.

Before lunch, Kate Storey-Fisher (NYU) and I had an absolutely great discussion with Roman Scoccimarro (NYU) about our correlation function estimator. He started off very skeptical and ended up a huge fan, which was fun to see, because I am pretty stoked about it! But then he said something off-topic but super-interesting: He has a standard experience on huge projects of the following form: While the correlation-function team is waiting for the data center to compute the correlation-function estimator (which involves an enormous pair-count operation in data and (much more importantly) random catalogs), he computes the power spectrum for the same data sample on his laptop! And yet the correlation function and the power spectrum are (in principle) the same information! What gives?

The answer—which I have to say I haven't fully figured out yet—is in part that the standard power-spectrum estimation doesn't consider explicitly the off-diagonal (k not equal to k-prime) mode cross-correlations, and in part that the standard power-spectrum estimation assumes that the window function is simple enough that a random catalog is not necessary. Those are huge approximations! However, if they are good enough for the power spectrum on baryon-acoustic scales, then they must be good enough for the correlation function on those same scales and maybe we can build a far, far faster estimator?

gravitational wave inferences

Thursdays are low-research days! But I did have a great conversation with Bonaca (Harvard) about the paper we are writing on the GD-1 stellar stream. We talked about the discussion section: What can we say about black-hole models for the gravitational perturbation we observe? What can we say about the population of perturbers from this one perturbing event?

At the end of the day, Will Farr (Flatiron) gave the Departmental Colloquium about gravitational-wave events, with a focus on statistical inference issues. He made some nice points, including that if Advanced LIGO works according to plans, it will generate enough black-hole and neutron-star inspiral events to solve a bunch of cosmological questions, like the Hubble Constant, whether there are pair-instability supernovae and at what masses, and how black-hole binaries form. That is, it will be routine, high-throughput astronomy! Farr is one of the people responsible for the excellent statistical inference underlying the LIGO results.

linear models for the win

Christina Eilers (MPIA) and I have been debating what photometry and colors to put into our linear model for distance estimation or distance-modulus estimation. And then we realized: It is a general linear model! So we should just put in all photometry and the code will decide what colors to create and use. We did, and the model improved for the stars behind the most dust. Just a reminder: We don't explicitly extinction-correct anything! We ask the model to figure out extinction on its own, by training on a sample that has stars at different extinctions.

In the afternoon I had a conversation with Maryam Modjaz (NYU) and Marc Williamson (NYU) about applying PCA and other simple machine-learning techniques to their library of supernova spectra across type and phase. They have some nice results, that show that the first few PCA components do a good job of separating types, and they can show that the separation quality is a function of time (relative to maximum light, or the explosion). We discussed using something like a purely linear support vector machine to do classification that would be highly interptetable. As my loyal reader knows, I am happy to sacrifice some performance for interpretability.

SNe and GRBs

On my first day in Heidelberg, I attended a colloquium talk by Maryam Modjaz (NYU), about exploding stars. She has very nice results on the metallicities of the environments (galaxy hosts) of supernovae and gamma-ray bursts. She can show that the type Ic broad-lined supernovae are different in chemical environments than the type Ic normal supernovae, and she can show that the SNe associated with GRBs are Ic broad-lined. So the non-GRB type Ic broad-lined supernovae are very likely the counterparts of off-axis gamma-ray bursts. The gamma-ray bursts without gamma rays! This is exciting, because it will bolster the model for GRBs and constrain the beaming.

#wetton18, day 2

The Wetton Workshop opened today with amazing talks by Udalski and Wyrzykowski about the OGLE project and data. It is truly incredible what has been achieved in this survey, which was designed with a very forward-looking goal of detecting microlensing by compact objects in the dark sector. The project detected all kinds of other expected and unexpected time-domain phenomena. These talks were followed by Alexander Scholz (St Andrews) providing some philosophical basis for looking for and at anomalies in data streams. He gave the good advice (and OGLE is a great example of this) to look at timescales or wavelengths or precisions where no-one has looked before. Hear, hear! (He is also the lead of the WETI project, of which I am a big fan.)

There were too many things that I loved today; I can't list them all here! But one personal highlight was an exciting talk by Thomas Wevers about the Gaia alerts system, which is putting Gaia data on-line in real time when stars vary strongly, or when new sources appear on the sky. It produces a few alerts a day, and the data dump includes the epoch photometry and the raw Bp-Rp low-resolution spectra! This got me extremely excited: I haven't seen any Bp-Rp spectra yet, and there are now thousands online. I resolved to look at them asap. Wevers warned us that the spectra are not calibrated in any sense: Not in wavelength or in photometrically.